From 2ad0f7c62a0823a36abfbfa9ed9bffd29cdaf33d Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Thu, 10 Sep 2026 11:43:17 -0400
Subject: [PATCH 01/15] Measure the surface-code threshold with a matched prior
 and a dense grid

The previous sweep decoded every rate with a fixed prior of 0.1 on a
0.01-spaced grid, and the crossing of the curves sat at about p = 0.10,
at the lower edge of the literature band. The decoder is now given the
channel's rate as its prior at every point (bias_prob = p), the grid is
dense around the crossing (0.08, 0.09, 0.095, 0.10, 0.105, 0.11, 0.12,
0.13), the aggregation cell prints the full table and the crossings of
neighbouring sizes by linear interpolation, and the plot draws the
L=5/L=7 crossing, the notebook's threshold estimate, next to the
literature band. Outputs are cleared here and regenerated at full scale.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 418 +++++-------------------
 1 file changed, 84 insertions(+), 334 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 71abd897..abe9abe1 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -2655,12 +2655,12 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, a bond dimension the $L = 7$ decoder is converged at, and enough shots to resolve the crossing. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes a couple of hours at full scale."
+    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, a bond dimension the $L = 7$ decoder is converged at, a grid that is dense around the crossing, and enough shots to resolve it. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes many hours at full scale."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2026-09-10T03:58:47.023088Z",
@@ -2669,269 +2669,7 @@
      "shell.execute_reply": "2026-09-10T14:04:05.701392Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  12%|█▎        | 1/8 [01:07<07:50, 67.23s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  25%|██▌       | 2/8 [02:30<07:41, 76.91s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  38%|███▊      | 3/8 [03:57<06:47, 81.54s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  50%|█████     | 4/8 [05:29<05:42, 85.63s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  62%|██████▎   | 5/8 [07:05<04:27, 89.24s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  75%|███████▌  | 6/8 [08:43<03:04, 92.23s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64:  88%|████████▊ | 7/8 [10:26<01:35, 95.86s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [12:12<00:00, 98.98s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [12:12<00:00, 91.56s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  12%|█▎        | 1/8 [14:56<1:44:32, 896.02s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  25%|██▌       | 2/8 [31:02<1:33:43, 937.26s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  38%|███▊      | 3/8 [47:20<1:19:41, 956.22s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  50%|█████     | 4/8 [1:04:02<1:04:56, 974.09s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  62%|██████▎   | 5/8 [1:20:42<49:10, 983.40s/it]  "
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  75%|███████▌  | 6/8 [1:37:36<33:08, 994.02s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64:  88%|████████▊ | 7/8 [1:55:40<17:03, 1023.16s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [2:13:00<00:00, 1028.68s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [2:13:00<00:00, 997.58s/it] "
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  12%|█▎        | 1/8 [58:08<6:46:56, 3488.01s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  25%|██▌       | 2/8 [1:56:21<5:49:09, 3491.52s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  38%|███▊      | 3/8 [2:54:23<4:50:34, 3486.99s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  50%|█████     | 4/8 [3:52:26<3:52:20, 3485.23s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  62%|██████▎   | 5/8 [4:50:00<2:53:42, 3474.03s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  75%|███████▌  | 6/8 [5:48:49<1:56:25, 3492.78s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64:  88%|████████▊ | 7/8 [6:44:37<57:25, 3445.31s/it]  "
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [7:40:04<00:00, 3407.81s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [7:40:04<00:00, 3450.57s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "from multiprocessing import Pool\n",
     "from mdopt.examples.decoding.quantum_surface import run_single_experiment\n",
@@ -2950,13 +2688,14 @@
     ")\n",
     "SEED = 123\n",
     "\n",
-    "# Parameters\n",
+    "# Parameters. The decoder's bias is the channel's rate at every point.\n",
     "tolerances = [0]\n",
-    "biases = [0.1]\n",
     "cuts = [0]\n",
     "max_bond_dims = [64]\n",
     "error_rates = (\n",
-    "    [0.05, 0.10, 0.13] if FAST else [0.05, 0.07, 0.08, 0.09, 0.10, 0.11, 0.12, 0.13]\n",
+    "    [0.08, 0.10, 0.13]\n",
+    "    if FAST\n",
+    "    else [0.08, 0.09, 0.095, 0.10, 0.105, 0.11, 0.12, 0.13]\n",
     ")\n",
     "\n",
     "for LATTICE_SIZE in lattice_sizes:\n",
@@ -2984,42 +2723,42 @@
     "    # counted as a failure, not dropped: hard shots raise more often than easy\n",
     "    # ones, so leaving them out would understate the logical error rate.\n",
     "    for CHI_MAX in max_bond_dims:\n",
-    "        for BIAS in biases:\n",
-    "            for TOLERANCE in tolerances:\n",
-    "                for CUT in cuts:\n",
-    "                    for ERROR_RATE in tqdm(\n",
-    "                        error_rates, desc=f\"L={LATTICE_SIZE}, chi={CHI_MAX}\"\n",
-    "                    ):\n",
-    "                        args = [\n",
-    "                            (\n",
-    "                                LATTICE_SIZE,\n",
-    "                                CHI_MAX,\n",
-    "                                error,\n",
-    "                                BIAS,\n",
-    "                                \"Bitflip\",\n",
-    "                                True,\n",
-    "                                TOLERANCE,\n",
-    "                                CUT,\n",
-    "                                \"Optimised\",\n",
+    "        for TOLERANCE in tolerances:\n",
+    "            for CUT in cuts:\n",
+    "                for ERROR_RATE in tqdm(\n",
+    "                    error_rates, desc=f\"L={LATTICE_SIZE}, chi={CHI_MAX}\"\n",
+    "                ):\n",
+    "                    BIAS = ERROR_RATE\n",
+    "                    args = [\n",
+    "                        (\n",
+    "                            LATTICE_SIZE,\n",
+    "                            CHI_MAX,\n",
+    "                            error,\n",
+    "                            BIAS,\n",
+    "                            \"Bitflip\",\n",
+    "                            True,\n",
+    "                            TOLERANCE,\n",
+    "                            CUT,\n",
+    "                            \"Optimised\",\n",
+    "                        )\n",
+    "                        for error in errors[LATTICE_SIZE, ERROR_RATE]\n",
+    "                    ]\n",
+    "                    if NUM_PROCESSES == 1:\n",
+    "                        results = [run_single_experiment(*arg) for arg in args]\n",
+    "                    else:\n",
+    "                        with Pool(NUM_PROCESSES) as pool:\n",
+    "                            results = pool.starmap(\n",
+    "                                run_single_experiment, args, chunksize=8\n",
     "                            )\n",
-    "                            for error in errors[LATTICE_SIZE, ERROR_RATE]\n",
-    "                        ]\n",
-    "                        if NUM_PROCESSES == 1:\n",
-    "                            results = [run_single_experiment(*arg) for arg in args]\n",
-    "                        else:\n",
-    "                            with Pool(NUM_PROCESSES) as pool:\n",
-    "                                results = pool.starmap(\n",
-    "                                    run_single_experiment, args, chunksize=8\n",
-    "                                )\n",
-    "                        key = (LATTICE_SIZE, CHI_MAX, ERROR_RATE, BIAS, TOLERANCE, CUT)\n",
-    "                        flags = np.asarray([failure for _, failure in results], dtype=float)\n",
-    "                        undecoded[key] = int(np.isnan(flags).sum())\n",
-    "                        failures_statistics[key] = np.where(np.isnan(flags), 1.0, flags)\n"
+    "                    key = (LATTICE_SIZE, CHI_MAX, ERROR_RATE, BIAS, TOLERANCE, CUT)\n",
+    "                    flags = np.asarray([failure for _, failure in results], dtype=float)\n",
+    "                    undecoded[key] = int(np.isnan(flags).sum())\n",
+    "                    failures_statistics[key] = np.where(np.isnan(flags), 1.0, flags)\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2026-09-10T14:04:05.703869Z",
@@ -3028,25 +2767,45 @@
      "shell.execute_reply": "2026-09-10T14:04:05.711625Z"
     }
    },
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Every shot decoded; no failure was counted from a raised decode.\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
+    "CHI_MAX, TOLERANCE, CUT = max_bond_dims[0], tolerances[0], cuts[0]\n",
+    "\n",
+    "\n",
+    "def key_of(lattice_size, error_rate):\n",
+    "    return (lattice_size, CHI_MAX, error_rate, error_rate, TOLERANCE, CUT)\n",
+    "\n",
+    "\n",
     "for LATTICE_SIZE in lattice_sizes:\n",
-    "    for CHI_MAX in max_bond_dims:\n",
-    "        for BIAS in biases:\n",
-    "            for TOLERANCE in tolerances:\n",
-    "                for CUT in cuts:\n",
-    "                    for ERROR_RATE in error_rates:\n",
-    "                        key = (LATTICE_SIZE, CHI_MAX, ERROR_RATE, BIAS, TOLERANCE, CUT)\n",
-    "                        failure_rates[key] = np.mean(failures_statistics[key])\n",
-    "                        error_bars[key] = sem(failures_statistics[key])\n",
+    "    for ERROR_RATE in error_rates:\n",
+    "        key = key_of(LATTICE_SIZE, ERROR_RATE)\n",
+    "        failure_rates[key] = np.mean(failures_statistics[key])\n",
+    "        error_bars[key] = sem(failures_statistics[key])\n",
+    "\n",
+    "# The numbers behind the plot, and the crossings of neighbouring sizes by\n",
+    "# linear interpolation of their difference between grid points. The crossing\n",
+    "# of the two largest sizes is the threshold estimate this notebook can make.\n",
+    "print(\"logical error rate (standard error) per lattice size and rate\")\n",
+    "print(\"p      \" + \"\".join(f\"{p:>16.3f}\" for p in error_rates))\n",
+    "for L in lattice_sizes:\n",
+    "    print(\n",
+    "        f\"L={L:<3d}  \"\n",
+    "        + \"\".join(\n",
+    "            f\"{failure_rates[key_of(L, p)]:>9.4f}({error_bars[key_of(L, p)]:.4f})\"\n",
+    "            for p in error_rates\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "crossings = {}\n",
+    "for small, large in zip(lattice_sizes[:-1], lattice_sizes[1:]):\n",
+    "    gap = [failure_rates[key_of(large, p)] - failure_rates[key_of(small, p)] for p in error_rates]\n",
+    "    for (p0, g0), (p1, g1) in zip(zip(error_rates, gap), zip(error_rates[1:], gap[1:])):\n",
+    "        if g0 < 0 <= g1:\n",
+    "            crossings[small, large] = p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",
+    "            print(f\"L={small} and L={large} cross at p = {crossings[small, large]:.4f}\")\n",
+    "            break\n",
+    "    else:\n",
+    "        print(f\"L={small} and L={large} do not cross on this grid\")\n",
     "\n",
     "raised = {key: n for key, n in undecoded.items() if n}\n",
     "if raised:\n",
@@ -3059,7 +2818,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "execution": {
      "iopub.execute_input": "2026-09-10T14:04:05.712862Z",
@@ -3068,18 +2827,7 @@
      "shell.execute_reply": "2026-09-10T14:04:06.573945Z"
     }
    },
-   "outputs": [
-    {
-     "data": {
-      "image/png": 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",
-      "text/plain": [
-       "<Figure size 350x300 with 1 Axes>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
+   "outputs": [],
    "source": [
     "import matplotlib as mpl\n",
     "from matplotlib import colormaps\n",
@@ -3091,8 +2839,6 @@
     "    \"xtick.labelsize\": 8, \"ytick.labelsize\": 8,\n",
     "})\n",
     "\n",
-    "CHI_MAX, BIAS, TOLERANCE, CUT = 64, 0.1, 0, 0\n",
-    "\n",
     "fig, ax = plt.subplots(figsize=(3.5, 3.0), constrained_layout=True)\n",
     "\n",
     "cmap = colormaps[\"viridis_r\"]\n",
@@ -3101,8 +2847,8 @@
     "for index, lattice_size in enumerate(lattice_sizes):\n",
     "    ax.errorbar(\n",
     "        error_rates,\n",
-    "        [failure_rates[lattice_size, CHI_MAX, er, BIAS, TOLERANCE, CUT] for er in error_rates],\n",
-    "        yerr=[error_bars[lattice_size, CHI_MAX, er, BIAS, TOLERANCE, CUT] for er in error_rates],\n",
+    "        [failure_rates[key_of(lattice_size, er)] for er in error_rates],\n",
+    "        yerr=[error_bars[key_of(lattice_size, er)] for er in error_rates],\n",
     "        fmt=\"o--\",\n",
     "        label=rf\"$L = {lattice_size}$\",\n",
     "        linewidth=1.5, markersize=4, capsize=2,\n",
@@ -3112,6 +2858,10 @@
     "# Code-capacity bit-flip thresholds of the surface code from the literature:\n",
     "# 10.3% for minimum-weight perfect matching, 10.9% for optimal decoding.\n",
     "ax.axvspan(0.103, 0.109, color=\"gray\", alpha=0.2, linewidth=0, label=\"threshold (lit.)\")\n",
+    "if len(lattice_sizes) > 1 and (lattice_sizes[-2], lattice_sizes[-1]) in crossings:\n",
+    "    p_cross = crossings[lattice_sizes[-2], lattice_sizes[-1]]\n",
+    "    ax.axvline(p_cross, color=\"black\", linewidth=0.8, linestyle=\":\",\n",
+    "               label=rf\"$L={lattice_sizes[-2]}$/$L={lattice_sizes[-1]}$ crossing, {100 * p_cross:.1f}\\%\")\n",
     "\n",
     "ax.set_yscale(\"log\")\n",
     "ax.set_xlabel(r\"Physical error rate $p$\")\n",
@@ -3127,7 +2877,7 @@
    "id": "b0dda13e",
    "metadata": {},
    "source": [
-    "Below the shaded band the curves fan out in the right order: at a fixed physical error rate the larger code fails less often, and the gap widens as $p$ decreases. Above it the order reverses, the larger code failing more often. The curves cross inside the band, at the code-capacity bit-flip threshold of the surface code, which lies between the minimum-weight-matching value of 10.3% and the optimal-decoding value of 10.9%. The logarithmic axis is what makes the low-$p$ fan-out visible; on a linear axis it collapses into the origin. A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them."
+    "Below the crossing the curves fan out in the right order: at a fixed physical error rate the larger code fails less often, and the gap widens as $p$ decreases. Above it the order reverses, the larger code failing more often. The crossing of the two largest sizes, printed by the aggregation cell and drawn as the dotted line, is this notebook's estimate of the code-capacity bit-flip threshold of the surface code; the shaded band is the literature range, from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. With $L \\le 7$ the finite-size drift of the crossing is still visible (the $L = 3$/$L = 5$ crossing sits below the $L = 5$/$L = 7$ one), so the estimate from the largest pair is the one to read. The logarithmic axis is what makes the low-$p$ fan-out visible; on a linear axis it collapses into the origin. A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them."
    ]
   }
  ],

From 402960cfdd263b461a7b6e1c0e653fb6374797ca Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Thu, 10 Sep 2026 11:47:27 -0400
Subject: [PATCH 02/15] Update the notebook run-time estimates

classical_ldpc now takes about 4 h (its BP comparison cell 1.25 h on five
workers) and quantum_surface about 13 h (the threshold sweep about 10 h);
the pipeline page says how the worker pools are sized and that concurrent
workers on this laptop run about three times slower per shot than a lone
process.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 docs/source/notebook_pipeline.rst      | 31 +++++++++++++++-----------
 examples/decoding/classical_ldpc.ipynb |  2 +-
 2 files changed, 19 insertions(+), 14 deletions(-)

diff --git a/docs/source/notebook_pipeline.rst b/docs/source/notebook_pipeline.rst
index 848504a1..300bdb1b 100644
--- a/docs/source/notebook_pipeline.rst
+++ b/docs/source/notebook_pipeline.rst
@@ -46,13 +46,12 @@ Regenerating the results
 notebook afterwards; the next push to ``main`` opens the sync PR, and the docs
 follow once it is merged.
 
-Expect this to take hours. Measured on an M-series laptop, one notebook at a
-time (``classical_ldpc`` is the one estimate here -- it has not yet completed
-a full run):
+Expect this to take hours. Measured on an M-series laptop (10 cores), one
+notebook at a time:
 
-===========================  =================
+===========================  ==================================================
 notebook                     full run
-===========================  =================
+===========================  ==================================================
 ``main_component``           4 s
 ``ground_state``             11 s
 ``mps-rand-circ``            26 s
@@ -61,14 +60,20 @@ notebook                     full run
 ``quantum_five_qubit``       43 s
 ``maxbonddim``               1.2 h
 ``quantum_three_qubit``      1.6 h
-``quantum_surface``          4.9 h
-``classical_ldpc``           ~2.5 h (estimate)
-===========================  =================
-
-The shot counts in the four expensive notebooks were chosen to land in that
-range. They were once far larger -- ``quantum_surface`` alone needed 33 hours,
-which nobody was going to run -- so the results here are deliberately noisier
-than a cluster campaign would give. The thesis figures come from the scripts in
+``classical_ldpc``           ~4 h (the BP comparison cell alone 1.25 h)
+``quantum_surface``          ~13 h (the threshold sweep alone ~10 h)
+===========================  ==================================================
+
+The last two notebooks end with a cell that regenerates its data through a
+pool of worker processes (all but two cores by default;
+``MDOPT_NB_PROCESSES`` overrides it). Their times above are with five
+workers; note that concurrent workers on this laptop run about three times
+slower per shot than a single process, because they share the efficiency
+cores, so a lone-process estimate understates them badly. The shot counts in
+the expensive notebooks were chosen to keep them at this scale -- the surface
+threshold sweep once needed 33 hours in the natural qubit order, which nobody
+was going to run -- so the results here are deliberately noisier than a
+cluster campaign would give. The thesis figures come from the scripts in
 ``mdopt/examples/decoding/plotting/`` and their cluster datasets, not from these
 notebooks.
 
diff --git a/examples/decoding/classical_ldpc.ipynb b/examples/decoding/classical_ldpc.ipynb
index e33b00ce..61bff1bb 100644
--- a/examples/decoding/classical_ldpc.ipynb
+++ b/examples/decoding/classical_ldpc.ipynb
@@ -2337,7 +2337,7 @@
    "source": [
     "We see what we expect: the decoder is able to correct more errors with less truncation. This is a good sign that the decoder is working as expected.\n",
     "\n",
-    "Finally, let us compare the MPS-MPO decoder with belief propagation, the standard decoder for LDPC codes, on identical codes and identical received words: for every shot a fresh random (3,4)-regular code is drawn, a codeword is sent through the binary symmetric channel, and both decoders see the same corrupted word. Belief propagation (`ldpc`, product-sum, 80 iterations) is run inline, the MPS-MPO decodes go through the campaign worker in parallel. Nothing is loaded from disk; the cell takes about half an hour at full scale."
+    "Finally, let us compare the MPS-MPO decoder with belief propagation, the standard decoder for LDPC codes, on identical codes and identical received words: for every shot a fresh random (3,4)-regular code is drawn, a codeword is sent through the binary symmetric channel, and both decoders see the same corrupted word. Belief propagation (`ldpc`, product-sum, 80 iterations) is run inline, the MPS-MPO decodes go through the campaign worker in parallel. Nothing is loaded from disk; the cell takes about an hour and a quarter at full scale on five worker processes."
    ]
   },
   {

From 67a97e674d3212732f347d1139e63390e41ea1b4 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Thu, 10 Sep 2026 22:39:46 -0400
Subject: [PATCH 03/15] Regenerate the matched-prior threshold sweep at full
 scale

L = 3, 5, 7 at chi = 64 (RCM order), 3000 shots per point, decoder prior
equal to the channel rate. Logical error rates (standard error ~0.006):
  p:     0.080  0.090  0.095  0.100  0.105  0.110  0.120  0.130
  L=3:   0.105  0.123  0.120  0.136  0.148  0.146  0.184  0.213
  L=5:   0.088  0.108  0.125  0.138  0.148  0.158  0.211  0.238
  L=7:   0.072  0.111  0.124  0.140  0.154  0.191  0.227  0.281
Crossings by linear interpolation: L=3/L=5 at p = 0.0938, L=5/L=7 at
p = 0.0887, both below the literature band (10.3-10.9%). With the fixed
prior of 0.1 the previous sweep crossed at about 0.10; the matched prior
did not move the crossing up but down, and L = 7 is now above L = 5 from
p = 0.105 on. Every shot decoded. Outputs committed as measured.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 334 ++++++++++++++++++++++--
 1 file changed, 311 insertions(+), 23 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index abe9abe1..37c2f258 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T03:58:46.362171Z",
-     "iopub.status.busy": "2026-09-10T03:58:46.361844Z",
-     "iopub.status.idle": "2026-09-10T03:58:47.021736Z",
-     "shell.execute_reply": "2026-09-10T03:58:47.021381Z"
+     "iopub.execute_input": "2026-09-10T15:43:04.980878Z",
+     "iopub.status.busy": "2026-09-10T15:43:04.980463Z",
+     "iopub.status.idle": "2026-09-10T15:43:05.759612Z",
+     "shell.execute_reply": "2026-09-10T15:43:05.759222Z"
     }
    },
    "outputs": [],
@@ -2655,21 +2655,283 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, a bond dimension the $L = 7$ decoder is converged at, a grid that is dense around the crossing, and enough shots to resolve it. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes many hours at full scale."
+    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, a bond dimension the $L = 7$ decoder is converged at, a grid that is dense around the crossing, and enough shots to resolve it. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about ten hours at full scale on five worker processes."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T03:58:47.023088Z",
-     "iopub.status.busy": "2026-09-10T03:58:47.022985Z",
-     "iopub.status.idle": "2026-09-10T14:04:05.702189Z",
-     "shell.execute_reply": "2026-09-10T14:04:05.701392Z"
+     "iopub.execute_input": "2026-09-10T15:43:05.760698Z",
+     "iopub.status.busy": "2026-09-10T15:43:05.760590Z",
+     "iopub.status.idle": "2026-09-11T02:24:44.708755Z",
+     "shell.execute_reply": "2026-09-11T02:24:44.708216Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  12%|█▎        | 1/8 [00:57<06:39, 57.05s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  25%|██▌       | 2/8 [02:02<06:12, 62.09s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  38%|███▊      | 3/8 [03:11<05:25, 65.02s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  50%|█████     | 4/8 [04:24<04:33, 68.36s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  62%|██████▎   | 5/8 [05:50<03:43, 74.56s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  75%|███████▌  | 6/8 [07:15<02:36, 78.07s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64:  88%|████████▊ | 7/8 [08:44<01:21, 81.66s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64: 100%|██████████| 8/8 [10:15<00:00, 84.66s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=3, chi=64: 100%|██████████| 8/8 [10:15<00:00, 76.90s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  12%|█▎        | 1/8 [16:20<1:54:23, 980.46s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  25%|██▌       | 2/8 [34:50<1:45:40, 1056.76s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  38%|███▊      | 3/8 [52:16<1:27:39, 1051.91s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  50%|█████     | 4/8 [1:10:43<1:11:34, 1073.74s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  62%|██████▎   | 5/8 [1:28:43<53:47, 1075.94s/it]  "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  75%|███████▌  | 6/8 [1:45:56<35:22, 1061.36s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64:  88%|████████▊ | 7/8 [2:04:12<17:52, 1072.60s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64: 100%|██████████| 8/8 [2:23:11<00:00, 1093.71s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=5, chi=64: 100%|██████████| 8/8 [2:23:11<00:00, 1073.94s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  12%|█▎        | 1/8 [1:04:49<7:33:43, 3889.13s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  25%|██▌       | 2/8 [2:10:10<6:30:49, 3908.29s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  38%|███▊      | 3/8 [3:15:34<5:26:16, 3915.40s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  50%|█████     | 4/8 [4:13:56<4:10:08, 3752.18s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  62%|██████▎   | 5/8 [5:12:39<3:03:28, 3669.62s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  75%|███████▌  | 6/8 [6:11:21<2:00:38, 3619.46s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64:  88%|████████▊ | 7/8 [7:09:42<59:40, 3580.60s/it]  "
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64: 100%|██████████| 8/8 [8:08:11<00:00, 3557.70s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\r",
+      "L=7, chi=64: 100%|██████████| 8/8 [8:08:11<00:00, 3661.41s/it]"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
    "source": [
     "from multiprocessing import Pool\n",
     "from mdopt.examples.decoding.quantum_surface import run_single_experiment\n",
@@ -2758,16 +3020,31 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T14:04:05.703869Z",
-     "iopub.status.busy": "2026-09-10T14:04:05.703713Z",
-     "iopub.status.idle": "2026-09-10T14:04:05.711929Z",
-     "shell.execute_reply": "2026-09-10T14:04:05.711625Z"
+     "iopub.execute_input": "2026-09-11T02:24:44.711917Z",
+     "iopub.status.busy": "2026-09-11T02:24:44.711795Z",
+     "iopub.status.idle": "2026-09-11T02:24:44.719401Z",
+     "shell.execute_reply": "2026-09-11T02:24:44.719057Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "logical error rate (standard error) per lattice size and rate\n",
+      "p                 0.080           0.090           0.095           0.100           0.105           0.110           0.120           0.130\n",
+      "L=3       0.1053(0.0056)   0.1233(0.0060)   0.1203(0.0059)   0.1360(0.0063)   0.1483(0.0065)   0.1457(0.0064)   0.1840(0.0071)   0.2133(0.0075)\n",
+      "L=5       0.0877(0.0052)   0.1083(0.0057)   0.1250(0.0060)   0.1377(0.0063)   0.1483(0.0065)   0.1580(0.0067)   0.2113(0.0075)   0.2377(0.0078)\n",
+      "L=7       0.0717(0.0047)   0.1107(0.0057)   0.1240(0.0060)   0.1400(0.0063)   0.1540(0.0066)   0.1910(0.0072)   0.2270(0.0076)   0.2807(0.0082)\n",
+      "L=3 and L=5 cross at p = 0.0938\n",
+      "L=5 and L=7 cross at p = 0.0887\n",
+      "Every shot decoded; no failure was counted from a raised decode.\n"
+     ]
+    }
+   ],
    "source": [
     "CHI_MAX, TOLERANCE, CUT = max_bond_dims[0], tolerances[0], cuts[0]\n",
     "\n",
@@ -2818,16 +3095,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T14:04:05.712862Z",
-     "iopub.status.busy": "2026-09-10T14:04:05.712791Z",
-     "iopub.status.idle": "2026-09-10T14:04:06.574373Z",
-     "shell.execute_reply": "2026-09-10T14:04:06.573945Z"
+     "iopub.execute_input": "2026-09-11T02:24:44.720273Z",
+     "iopub.status.busy": "2026-09-11T02:24:44.720222Z",
+     "iopub.status.idle": "2026-09-11T02:24:45.147221Z",
+     "shell.execute_reply": "2026-09-11T02:24:45.146873Z"
     }
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 350x300 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
    "source": [
     "import matplotlib as mpl\n",
     "from matplotlib import colormaps\n",

From aa0096c6bfbe12576008a9b2eebc71d979c7254e Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Fri, 11 Sep 2026 22:28:15 -0400
Subject: [PATCH 04/15] Estimate the threshold crossing by a weighted fit and
 report every sign change

The gap between neighbouring sizes changes sign more than once on this grid
(L=5/L=7: three sign changes), so the first interpolated crossing was an
arbitrary, noise-driven choice. The crossing now comes from a weighted
least-squares line through the gap, with its uncertainty from the fit's
covariance (L=5/L=7: 0.0937 +/- 0.0032), and every raw sign change is
listed; a pair without a unique sign change says so. The plot marks the
fitted crossing with its uncertainty band. Outputs of the two cells were
regenerated from the committed table.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 58 ++++++++++++++++++-------
 1 file changed, 42 insertions(+), 16 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 37c2f258..532bf180 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -3039,8 +3039,10 @@
       "L=3       0.1053(0.0056)   0.1233(0.0060)   0.1203(0.0059)   0.1360(0.0063)   0.1483(0.0065)   0.1457(0.0064)   0.1840(0.0071)   0.2133(0.0075)\n",
       "L=5       0.0877(0.0052)   0.1083(0.0057)   0.1250(0.0060)   0.1377(0.0063)   0.1483(0.0065)   0.1580(0.0067)   0.2113(0.0075)   0.2377(0.0078)\n",
       "L=7       0.0717(0.0047)   0.1107(0.0057)   0.1240(0.0060)   0.1400(0.0063)   0.1540(0.0066)   0.1910(0.0072)   0.2270(0.0076)   0.2807(0.0082)\n",
-      "L=3 and L=5 cross at p = 0.0938\n",
-      "L=5 and L=7 cross at p = 0.0887\n",
+      "L=3 and L=5: fitted crossing p = 0.0988 +/- 0.0033 (slope 0.956); sign changes of the gap on the grid: 0.0938, 0.1050\n",
+      "  -> no unique crossing on the grid; only the fit is reported\n",
+      "L=5 and L=7: fitted crossing p = 0.0937 +/- 0.0032 (slope 1.059); sign changes of the gap on the grid: 0.0887, 0.0935, 0.0965\n",
+      "  -> no unique crossing on the grid; only the fit is reported\n",
       "Every shot decoded; no failure was counted from a raised decode.\n"
      ]
     }
@@ -3059,9 +3061,13 @@
     "        failure_rates[key] = np.mean(failures_statistics[key])\n",
     "        error_bars[key] = sem(failures_statistics[key])\n",
     "\n",
-    "# The numbers behind the plot, and the crossings of neighbouring sizes by\n",
-    "# linear interpolation of their difference between grid points. The crossing\n",
-    "# of the two largest sizes is the threshold estimate this notebook can make.\n",
+    "# The numbers behind the plot. The threshold estimate for each pair of\n",
+    "# neighbouring sizes comes from a weighted least-squares line through the\n",
+    "# difference of their logical error rates, gap(p) = LER(large) - LER(small):\n",
+    "# the root of the line is the crossing, and the fit's covariance gives its\n",
+    "# uncertainty. The raw sign changes of the gap between grid points are\n",
+    "# listed as well; with statistical errors of this size the gap can change\n",
+    "# sign more than once, so a single interpolated crossing is not meaningful.\n",
     "print(\"logical error rate (standard error) per lattice size and rate\")\n",
     "print(\"p      \" + \"\".join(f\"{p:>16.3f}\" for p in error_rates))\n",
     "for L in lattice_sizes:\n",
@@ -3075,14 +3081,32 @@
     "\n",
     "crossings = {}\n",
     "for small, large in zip(lattice_sizes[:-1], lattice_sizes[1:]):\n",
-    "    gap = [failure_rates[key_of(large, p)] - failure_rates[key_of(small, p)] for p in error_rates]\n",
-    "    for (p0, g0), (p1, g1) in zip(zip(error_rates, gap), zip(error_rates[1:], gap[1:])):\n",
-    "        if g0 < 0 <= g1:\n",
-    "            crossings[small, large] = p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",
-    "            print(f\"L={small} and L={large} cross at p = {crossings[small, large]:.4f}\")\n",
-    "            break\n",
-    "    else:\n",
-    "        print(f\"L={small} and L={large} do not cross on this grid\")\n",
+    "    gap = np.array([failure_rates[key_of(large, p)] - failure_rates[key_of(small, p)] for p in error_rates])\n",
+    "    sigma = np.array(\n",
+    "        [np.hypot(error_bars[key_of(large, p)], error_bars[key_of(small, p)]) for p in error_rates]\n",
+    "    )\n",
+    "    sign_changes = [\n",
+    "        p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",
+    "        for (p0, g0), (p1, g1) in zip(zip(error_rates, gap), zip(error_rates[1:], gap[1:]))\n",
+    "        if (g0 < 0 <= g1) or (g0 > 0 >= g1)\n",
+    "    ]\n",
+    "    # Weighted linear fit gap = a + b p; crossing p_c = -a / b.\n",
+    "    design = np.vstack([np.ones(len(error_rates)), np.asarray(error_rates)]).T\n",
+    "    weights = 1.0 / sigma\n",
+    "    coef, *_ = np.linalg.lstsq(design * weights[:, None], gap * weights, rcond=None)\n",
+    "    cov = np.linalg.inv((design * weights[:, None]).T @ (design * weights[:, None]))\n",
+    "    a, b = coef\n",
+    "    p_c = -a / b\n",
+    "    grad = np.array([-1.0 / b, a / b**2])\n",
+    "    p_c_err = float(np.sqrt(grad @ cov @ grad))\n",
+    "    crossings[small, large] = (p_c, p_c_err, sign_changes)\n",
+    "    changes = \", \".join(f\"{x:.4f}\" for x in sign_changes) or \"none\"\n",
+    "    print(\n",
+    "        f\"L={small} and L={large}: fitted crossing p = {p_c:.4f} +/- {p_c_err:.4f} \"\n",
+    "        f\"(slope {b:.3f}); sign changes of the gap on the grid: {changes}\"\n",
+    "    )\n",
+    "    if len(sign_changes) != 1:\n",
+    "        print(f\"  -> no unique crossing on the grid; only the fit is reported\")\n",
     "\n",
     "raised = {key: n for key, n in undecoded.items() if n}\n",
     "if raised:\n",
@@ -3107,7 +3131,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -3147,9 +3171,11 @@
     "# 10.3% for minimum-weight perfect matching, 10.9% for optimal decoding.\n",
     "ax.axvspan(0.103, 0.109, color=\"gray\", alpha=0.2, linewidth=0, label=\"threshold (lit.)\")\n",
     "if len(lattice_sizes) > 1 and (lattice_sizes[-2], lattice_sizes[-1]) in crossings:\n",
-    "    p_cross = crossings[lattice_sizes[-2], lattice_sizes[-1]]\n",
+    "    p_cross, p_err, _ = crossings[lattice_sizes[-2], lattice_sizes[-1]]\n",
+    "    ax.axvspan(p_cross - p_err, p_cross + p_err, color=\"black\", alpha=0.12, linewidth=0)\n",
     "    ax.axvline(p_cross, color=\"black\", linewidth=0.8, linestyle=\":\",\n",
-    "               label=rf\"$L={lattice_sizes[-2]}$/$L={lattice_sizes[-1]}$ crossing, {100 * p_cross:.1f}\\%\")\n",
+    "               label=rf\"$L={lattice_sizes[-2]}$/$L={lattice_sizes[-1]}$ fitted crossing, \"\n",
+    "                     rf\"{100 * p_cross:.1f}$\\pm${100 * p_err:.1f}\\%\")\n",
     "\n",
     "ax.set_yscale(\"log\")\n",
     "ax.set_xlabel(r\"Physical error rate $p$\")\n",

From 6e7c45fe1a7942731798fecec134017063262f97 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Fri, 11 Sep 2026 23:20:35 -0400
Subject: [PATCH 05/15] Make the surface-code prose match the plots and the
 printed numbers

The convergence text claimed the curves move right with the bond
dimension; the plot shows chi=64 and 128 on top of each other, chi=16 and
32 within a standard error of them, and only chi=8 departing. The
threshold text claimed the curves cross inside the literature band and
that the L=3/L=5 crossing sits below the L=5/L=7 one; the fitted L=5/L=7
crossing is 9.4 +/- 0.3%, below the band, and the L=3/L=5 one is higher at
9.9 +/- 0.3%. The text now describes the order of the curves rate by rate,
the fit and the three sign changes it replaces, the shortfall against the
band and the bond-dimension sweep that would settle it, and the measured
run time (eleven hours: ten minutes, two and a half hours, eight hours).

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 12 +++++++++---
 1 file changed, 9 insertions(+), 3 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 532bf180..5377bb08 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -2648,14 +2648,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Great, so, we see the convergence in bond dimension (given bitflip noise, we converege to optimal decoding at the bond dimension equal to $2^6$ where $6$ is the maximum number of leg crossings encountered while applying MPOs, thus the curves with bond dimensions $2^6$ and $2^7$ are identically the same). Besides, we see how the curve moves to the right as we increase the bond dimension cutoff which is expected behaviour."
+    "The $\\chi_{\\max} = 64$ and $\\chi_{\\max} = 128$ curves lie on top of each other at every rate: for bit-flip noise the decoder is exact once the bond dimension reaches $2^6$, where $6$ is the largest number of leg crossings met while applying the MPOs on this lattice, so nothing changes beyond it. The $\\chi_{\\max} = 32$ and $16$ curves are within one standard error of the converged one everywhere; only $\\chi_{\\max} = 8$ departs from it, by about one standard error around $p = 0.07$ to $0.09$, where truncation happens to make the decoder look slightly better rather than worse. With 500 shots per point the error bars are about $\\pm 0.015$, so this is the resolution at which \"converged\" is meant here.\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, a bond dimension the $L = 7$ decoder is converged at, a grid that is dense around the crossing, and enough shots to resolve it. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about ten hours at full scale on five worker processes."
+    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, the bond dimension at which the $L = 3$ sweep above is converged ($\\chi_{\\max} = 64$), a grid that is dense around the crossing, and enough shots to resolve it. Whether $L = 7$ is converged at this bond dimension is not established by the sweep above (its MPOs have more leg crossings than those of $L = 3$), and the discussion after the plot comes back to this. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about eleven hours at full scale on five worker processes (ten minutes for $L = 3$, two and a half hours for $L = 5$, eight for $L = 7$).\n"
    ]
   },
   {
@@ -3191,7 +3191,13 @@
    "id": "b0dda13e",
    "metadata": {},
    "source": [
-    "Below the crossing the curves fan out in the right order: at a fixed physical error rate the larger code fails less often, and the gap widens as $p$ decreases. Above it the order reverses, the larger code failing more often. The crossing of the two largest sizes, printed by the aggregation cell and drawn as the dotted line, is this notebook's estimate of the code-capacity bit-flip threshold of the surface code; the shaded band is the literature range, from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. With $L \\le 7$ the finite-size drift of the crossing is still visible (the $L = 3$/$L = 5$ crossing sits below the $L = 5$/$L = 7$ one), so the estimate from the largest pair is the one to read. The logarithmic axis is what makes the low-$p$ fan-out visible; on a linear axis it collapses into the origin. A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them."
+    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.2%, $L = 5$ at 8.8%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, at $p = 0.095$ all three coincide within their errors, and from $p = 0.10$ upwards the order is reversed and the gap widens, the larger code failing more often. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
+    "\n",
+    "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.4 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points; with standard errors of 0.5 to 0.8 percentage points per point the sign changes three times on this grid, which is why a single interpolated crossing would be an arbitrary choice and the fit is used instead.\n",
+    "\n",
+    "The estimate sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. The $L = 3$/$L = 5$ crossing ($9.9 \\pm 0.3\\%$) is higher than the $L = 5$/$L = 7$ one, so the finite-size drift does not point towards the band either. The most likely reason is the bond dimension: $\\chi_{\\max} = 64$ is converged for $L = 3$ but has not been shown to be for $L = 5$ and $L = 7$, and truncation on the larger lattices costs the decoder accuracy exactly where the crossing is decided. A sweep of $\\chi_{\\max}$ at $L = 7$ around $p = 0.09$ to $0.10$ is the measurement that would settle it.\n",
+    "\n",
+    "A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them.\n"
    ]
   }
  ],

From 400b56b63fe264c6e66d82434ef676634c4b1374 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Fri, 11 Sep 2026 23:27:48 -0400
Subject: [PATCH 06/15] Take the gap's standard error from the paired per-shot
 differences

Every lattice size draws its shots from the same seed, so shot i of one
size shares its random prefix with shot i of the next and the two logical
error rates are correlated; the crossing fit's weights now use the standard
error of the paired per-shot differences instead of the quadrature sum of
two independent errors. The printed uncertainties refresh at the next
regeneration (the per-shot data is not stored in the notebook); the
current ones, computed as if independent, are conservative.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 16 ++++++++++++----
 1 file changed, 12 insertions(+), 4 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 5377bb08..741b6217 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -3065,9 +3065,13 @@
     "# neighbouring sizes comes from a weighted least-squares line through the\n",
     "# difference of their logical error rates, gap(p) = LER(large) - LER(small):\n",
     "# the root of the line is the crossing, and the fit's covariance gives its\n",
-    "# uncertainty. The raw sign changes of the gap between grid points are\n",
-    "# listed as well; with statistical errors of this size the gap can change\n",
-    "# sign more than once, so a single interpolated crossing is not meaningful.\n",
+    "# uncertainty. Every size draws its shots from the same seed, so shot i of\n",
+    "# one size shares its random prefix with shot i of the next; the gap's\n",
+    "# standard error is therefore that of the paired per-shot differences, not\n",
+    "# the quadrature sum of two independent errors. The raw sign changes of the\n",
+    "# gap between grid points are listed as well; with statistical errors of\n",
+    "# this size the gap can change sign more than once, so a single\n",
+    "# interpolated crossing is not meaningful.\n",
     "print(\"logical error rate (standard error) per lattice size and rate\")\n",
     "print(\"p      \" + \"\".join(f\"{p:>16.3f}\" for p in error_rates))\n",
     "for L in lattice_sizes:\n",
@@ -3083,7 +3087,11 @@
     "for small, large in zip(lattice_sizes[:-1], lattice_sizes[1:]):\n",
     "    gap = np.array([failure_rates[key_of(large, p)] - failure_rates[key_of(small, p)] for p in error_rates])\n",
     "    sigma = np.array(\n",
-    "        [np.hypot(error_bars[key_of(large, p)], error_bars[key_of(small, p)]) for p in error_rates]\n",
+    "        [\n",
+    "            sem(np.asarray(failures_statistics[key_of(large, p)], dtype=float)\n",
+    "                - np.asarray(failures_statistics[key_of(small, p)], dtype=float))\n",
+    "            for p in error_rates\n",
+    "        ]\n",
     "    )\n",
     "    sign_changes = [\n",
     "        p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",

From 781bbb2d77f63a2c5b1c0e6fa1e771526b516eda Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Sun, 13 Sep 2026 13:26:38 -0400
Subject: [PATCH 07/15] Describe the reversed ordering as noisy and drop the
 unsupported truncation explanation

Above p=0.10 the larger code fails more often at every rate but one tie,
yet the separation is not monotone (L=5/L=7 gap 3.3, 1.6, 4.3 points at
0.11, 0.12, 0.13), so the text no longer claims the gap widens. The two
crossing intervals overlap, so no finite-size drift is claimed either.
The closing paragraph blamed the below-band crossing on truncation at
chi=64; a same-shot comparison at L=7 with chi 64, 128 and 256 (same
noise, prior and RCM ordering) finds no significant difference, so that
explanation is replaced by the result, together with the prior
sensitivity the same comparison found.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 741b6217..7be7ee0a 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -3199,11 +3199,11 @@
    "id": "b0dda13e",
    "metadata": {},
    "source": [
-    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.2%, $L = 5$ at 8.8%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, at $p = 0.095$ all three coincide within their errors, and from $p = 0.10$ upwards the order is reversed and the gap widens, the larger code failing more often. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
+    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.2%, $L = 5$ at 8.8%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, and at $p = 0.095$ and $0.10$ all three coincide within their errors. Above $p = 0.10$ the larger code fails more often at every rate except for a tie between $L = 3$ and $L = 5$ at $p = 0.105$, but the separation does not grow steadily: the $L = 5$/$L = 7$ gap is 3.3 percentage points at $p = 0.11$, 1.6 at $p = 0.12$ and 4.3 at $p = 0.13$. The reversal itself is clear; its size from one rate to the next is at the level of the statistical errors. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
     "\n",
     "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.4 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points; with standard errors of 0.5 to 0.8 percentage points per point the sign changes three times on this grid, which is why a single interpolated crossing would be an arbitrary choice and the fit is used instead.\n",
     "\n",
-    "The estimate sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. The $L = 3$/$L = 5$ crossing ($9.9 \\pm 0.3\\%$) is higher than the $L = 5$/$L = 7$ one, so the finite-size drift does not point towards the band either. The most likely reason is the bond dimension: $\\chi_{\\max} = 64$ is converged for $L = 3$ but has not been shown to be for $L = 5$ and $L = 7$, and truncation on the larger lattices costs the decoder accuracy exactly where the crossing is decided. A sweep of $\\chi_{\\max}$ at $L = 7$ around $p = 0.09$ to $0.10$ is the measurement that would settle it.\n",
+    "The estimate sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. The $L = 3$/$L = 5$ crossing ($9.9 \\pm 0.3\\%$) is higher than the $L = 5$/$L = 7$ one, and the two intervals overlap, so this run does not resolve a finite-size drift in either direction. The shortfall is not explained by truncation: a same-shot comparison at $L = 7$, run outside this notebook with the same noise, prior and qubit ordering, found no significant change in the failure rate between $\\chi_{\\max} = 64$, $128$ and $256$ at $p = 0.10$ and $0.11$. The same comparison found the decoder sensitive to its prior at $\\chi_{\\max} = 64$: at $L = 7$ and $p = 0.11$ a prior of $0.03$ failed on 158 of 1000 shots against 189 for the matched prior. Why the matched prior loses to a sharper one here is not yet understood, and it is the next thing to examine.\n",
     "\n",
     "A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them.\n"
    ]

From 4f09de628e1d1f6e2f150811bd4e3bd2233a0230 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Sun, 13 Sep 2026 18:41:58 -0400
Subject: [PATCH 08/15] Run the crossing fit in fast mode, guard it against
 zero errors, and fix the workflow timings

In fast mode only L=3 ran, so the pair loop, the weighted crossing fit and
the crossing plot were never executed by the notebook CI job. Fast mode now
uses L=3 and L=5 with 20 shots per rate, which executes all of them. Doing
so showed two failure modes of the fit with few shots: a point whose paired
differences are all equal has a zero standard error and would get infinite
weight, and an all-flat gap has zero slope. The error is now floored at 1/n,
far below the full-scale errors, and a flat gap is reported instead of
dividing by zero. The notebooks workflow comment quoted the old suite
timings; it now matches docs/source/notebook_pipeline.rst. Only cell
sources changed; the committed full-scale outputs are untouched.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 .github/workflows/notebooks.yml         |  4 ++--
 examples/decoding/quantum_surface.ipynb | 14 ++++++++++++--
 2 files changed, 14 insertions(+), 4 deletions(-)

diff --git a/.github/workflows/notebooks.yml b/.github/workflows/notebooks.yml
index 75c5af80..cc037238 100644
--- a/.github/workflows/notebooks.yml
+++ b/.github/workflows/notebooks.yml
@@ -5,8 +5,8 @@ name: notebooks
 # nothing ran these.
 #
 # MDOPT_NB_FAST=1 shrinks the workloads: at the committed full-scale settings
-# the suite totals roughly 10 hours (quantum_surface ~4.9h, classical_ldpc
-# ~2.5h, quantum_three_qubit ~1.6h, maxbonddim ~1.2h -- see
+# the suite totals roughly 20 hours (quantum_surface ~13h, classical_ldpc
+# ~4h, quantum_three_qubit ~1.6h, maxbonddim ~1.2h -- see
 # docs/source/notebook_pipeline.rst), past the 6h GitHub caps a job at and far
 # too dear to spend per pull request. The notebooks read that variable
 # themselves. What is being tested is that they execute, not the numbers they
diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 7be7ee0a..b9d6c158 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -2941,8 +2941,10 @@
     "failure_rates = {}\n",
     "error_bars = {}\n",
     "undecoded = {}\n",
-    "lattice_sizes = [3] if FAST else [3, 5, 7]\n",
-    "NUM_EXPERIMENTS = 5 if FAST else 3000\n",
+    "# Fast mode keeps two sizes and enough shots that the crossing fit and its\n",
+    "# plot still run.\n",
+    "lattice_sizes = [3, 5] if FAST else [3, 5, 7]\n",
+    "NUM_EXPERIMENTS = 20 if FAST else 3000\n",
     "# Worker processes for the shots; MDOPT_NB_PROCESSES overrides the default of\n",
     "# all but two cores (a shared or memory-tight machine wants fewer).\n",
     "NUM_PROCESSES = int(\n",
@@ -3093,6 +3095,11 @@
     "            for p in error_rates\n",
     "        ]\n",
     "    )\n",
+    "    # A point where every paired difference is equal (common with few shots)\n",
+    "    # has a zero standard error and would get infinite weight; floor it at the\n",
+    "    # error a single discordant shot out of n would carry.\n",
+    "    n_paired = min(len(failures_statistics[key_of(large, p)]) for p in error_rates)\n",
+    "    sigma = np.maximum(np.nan_to_num(sigma, nan=0.0), 1.0 / n_paired)\n",
     "    sign_changes = [\n",
     "        p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",
     "        for (p0, g0), (p1, g1) in zip(zip(error_rates, gap), zip(error_rates[1:], gap[1:]))\n",
@@ -3104,6 +3111,9 @@
     "    coef, *_ = np.linalg.lstsq(design * weights[:, None], gap * weights, rcond=None)\n",
     "    cov = np.linalg.inv((design * weights[:, None]).T @ (design * weights[:, None]))\n",
     "    a, b = coef\n",
+    "    if not np.isfinite(b) or abs(b) < 1e-12:\n",
+    "        print(f\"L={small} and L={large}: the gap is flat on this grid; no crossing can be fitted\")\n",
+    "        continue\n",
     "    p_c = -a / b\n",
     "    grad = np.array([-1.0 / b, a / b**2])\n",
     "    p_c_err = float(np.sqrt(grad @ cov @ grad))\n",

From 2242207440d04fa7d14d6d737aa2f4d253cea9dc Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Mon, 14 Sep 2026 10:57:43 -0400
Subject: [PATCH 09/15] Count only strict sign changes of the gap, and list
 exact ties separately

The crossing diagnostics treated a zero gap at a grid point as a sign
change, so the committed L=3/L=5 data (gap positive at 0.10, exactly zero
at 0.105, positive at 0.11) reported a second crossing at 0.105 and "no
unique crossing". Sign changes are now counted only between gaps of
strictly opposite sign; exact ties are printed separately, and a tie that
sits between gaps of opposite sign is taken as the location of that
crossing. On the committed table L=3/L=5 now has one sign change (0.0938)
and a tie at 0.105, and L=5/L=7 keeps its three sign changes. Only the cell
source changed; the printed outputs refresh at the next regeneration.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 22 ++++++++++++++++------
 1 file changed, 16 insertions(+), 6 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index b9d6c158..520505bf 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -3100,11 +3100,19 @@
     "    # error a single discordant shot out of n would carry.\n",
     "    n_paired = min(len(failures_statistics[key_of(large, p)]) for p in error_rates)\n",
     "    sigma = np.maximum(np.nan_to_num(sigma, nan=0.0), 1.0 / n_paired)\n",
-    "    sign_changes = [\n",
-    "        p0 + (p1 - p0) * (-g0) / (g1 - g0)\n",
-    "        for (p0, g0), (p1, g1) in zip(zip(error_rates, gap), zip(error_rates[1:], gap[1:]))\n",
-    "        if (g0 < 0 <= g1) or (g0 > 0 >= g1)\n",
-    "    ]\n",
+    "    # Sign changes are counted only between gaps of strictly opposite sign.\n",
+    "    # An exact tie (a zero gap at a grid point) is listed separately; when it\n",
+    "    # sits between gaps of opposite sign it is where that crossing lies.\n",
+    "    ties = [p for p, g in zip(error_rates, gap) if g == 0]\n",
+    "    nonzero = [(p, g) for p, g in zip(error_rates, gap) if g != 0]\n",
+    "    sign_changes = []\n",
+    "    for (p0, g0), (p1, g1) in zip(nonzero, nonzero[1:]):\n",
+    "        if g0 * g1 < 0:\n",
+    "            tied_between = [p for p in ties if p0 < p < p1]\n",
+    "            if tied_between:\n",
+    "                sign_changes.append(float(np.mean(tied_between)))\n",
+    "            else:\n",
+    "                sign_changes.append(p0 + (p1 - p0) * (-g0) / (g1 - g0))\n",
     "    # Weighted linear fit gap = a + b p; crossing p_c = -a / b.\n",
     "    design = np.vstack([np.ones(len(error_rates)), np.asarray(error_rates)]).T\n",
     "    weights = 1.0 / sigma\n",
@@ -3119,9 +3127,11 @@
     "    p_c_err = float(np.sqrt(grad @ cov @ grad))\n",
     "    crossings[small, large] = (p_c, p_c_err, sign_changes)\n",
     "    changes = \", \".join(f\"{x:.4f}\" for x in sign_changes) or \"none\"\n",
+    "    tied = \", \".join(f\"{x:.3f}\" for x in ties) or \"none\"\n",
     "    print(\n",
     "        f\"L={small} and L={large}: fitted crossing p = {p_c:.4f} +/- {p_c_err:.4f} \"\n",
-    "        f\"(slope {b:.3f}); sign changes of the gap on the grid: {changes}\"\n",
+    "        f\"(slope {b:.3f}); sign changes of the gap on the grid: {changes}; \"\n",
+    "        f\"exact ties at: {tied}\"\n",
     "    )\n",
     "    if len(sign_changes) != 1:\n",
     "        print(f\"  -> no unique crossing on the grid; only the fit is reported\")\n",

From cb7015ecdd292eb747ea86a7274025c97441853b Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Tue, 15 Sep 2026 06:27:42 -0400
Subject: [PATCH 10/15] Regenerate the example notebooks on the optimised
 decoder

Full-scale re-execution of every eligible notebook after PR #543 merged,
so the committed outputs come from the merged code; the surface-code
threshold sweep now uses the paired-error weighting of the crossing fit.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/classical_ldpc.ipynb        |  642 +--
 .../decoding/dephasing_dmrg_debug_bb.ipynb    |  248 +-
 examples/decoding/maxbonddim.ipynb            | 1108 ++--
 examples/decoding/quantum_five_qubit.ipynb    | 1050 +---
 examples/decoding/quantum_surface.ipynb       |  873 +---
 examples/decoding/quantum_three_qubit.ipynb   |  366 +-
 examples/decoding/shor.ipynb                  | 4502 +----------------
 examples/ising/ground_state.ipynb             |   90 +-
 examples/main_component/main_component.ipynb  |   80 +-
 examples/random_circuit/mps-rand-circ.ipynb   |  340 +-
 10 files changed, 1557 insertions(+), 7742 deletions(-)

diff --git a/examples/decoding/classical_ldpc.ipynb b/examples/decoding/classical_ldpc.ipynb
index 61bff1bb..687fe66d 100644
--- a/examples/decoding/classical_ldpc.ipynb
+++ b/examples/decoding/classical_ldpc.ipynb
@@ -24,10 +24,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T02:45:02.200981Z",
-     "iopub.status.busy": "2026-09-10T02:45:02.200635Z",
-     "iopub.status.idle": "2026-09-10T02:45:02.787941Z",
-     "shell.execute_reply": "2026-09-10T02:45:02.787466Z"
+     "iopub.execute_input": "2026-09-14T22:46:14.600941Z",
+     "iopub.status.busy": "2026-09-14T22:46:14.600751Z",
+     "iopub.status.idle": "2026-09-14T22:46:15.076204Z",
+     "shell.execute_reply": "2026-09-14T22:46:15.075836Z"
     }
    },
    "outputs": [],
@@ -90,10 +90,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:30.307098Z",
-     "iopub.status.busy": "2026-08-29T05:05:30.306976Z",
-     "iopub.status.idle": "2026-08-29T05:05:30.308448Z",
-     "shell.execute_reply": "2026-08-29T05:05:30.308148Z"
+     "iopub.execute_input": "2026-09-14T22:46:15.077461Z",
+     "iopub.status.busy": "2026-09-14T22:46:15.077367Z",
+     "iopub.status.idle": "2026-09-14T22:46:15.078801Z",
+     "shell.execute_reply": "2026-09-14T22:46:15.078471Z"
     }
    },
    "outputs": [],
@@ -114,10 +114,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:30.309197Z",
-     "iopub.status.busy": "2026-08-29T05:05:30.309140Z",
-     "iopub.status.idle": "2026-08-29T05:05:30.310641Z",
-     "shell.execute_reply": "2026-08-29T05:05:30.310293Z"
+     "iopub.execute_input": "2026-09-14T22:46:15.079560Z",
+     "iopub.status.busy": "2026-09-14T22:46:15.079503Z",
+     "iopub.status.idle": "2026-09-14T22:46:15.081023Z",
+     "shell.execute_reply": "2026-09-14T22:46:15.080660Z"
     }
    },
    "outputs": [],
@@ -141,10 +141,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:30.311423Z",
-     "iopub.status.busy": "2026-08-29T05:05:30.311364Z",
-     "iopub.status.idle": "2026-08-29T05:05:30.313067Z",
-     "shell.execute_reply": "2026-08-29T05:05:30.312776Z"
+     "iopub.execute_input": "2026-09-14T22:46:15.081802Z",
+     "iopub.status.busy": "2026-09-14T22:46:15.081745Z",
+     "iopub.status.idle": "2026-09-14T22:46:15.083454Z",
+     "shell.execute_reply": "2026-09-14T22:46:15.083176Z"
     }
    },
    "outputs": [],
@@ -170,10 +170,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:30.313709Z",
-     "iopub.status.busy": "2026-08-29T05:05:30.313655Z",
-     "iopub.status.idle": "2026-08-29T05:05:30.316216Z",
-     "shell.execute_reply": "2026-08-29T05:05:30.315883Z"
+     "iopub.execute_input": "2026-09-14T22:46:15.084163Z",
+     "iopub.status.busy": "2026-09-14T22:46:15.084117Z",
+     "iopub.status.idle": "2026-09-14T22:46:15.086547Z",
+     "shell.execute_reply": "2026-09-14T22:46:15.086291Z"
     }
    },
    "outputs": [
@@ -215,10 +215,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2026-08-29T05:05:30.369950Z"
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+     "shell.execute_reply": "2026-09-14T22:46:15.121690Z"
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    "outputs": [
@@ -235,7 +235,7 @@
      "output_type": "stream",
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+      "100%|██████████| 9/9 [00:00<00:00, 894.46it/s]"
      ]
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     {
@@ -270,10 +270,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:30.371355Z",
-     "iopub.status.busy": "2026-08-29T05:05:30.371294Z",
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-     "shell.execute_reply": "2026-08-29T05:05:31.354479Z"
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+     "shell.execute_reply": "2026-09-14T22:46:15.618307Z"
     }
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    "outputs": [
@@ -290,7 +290,7 @@
      "output_type": "stream",
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+      " 22%|██▏       | 2/9 [00:00<00:00, 12.42it/s]"
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@@ -298,7 +298,7 @@
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+      " 56%|█████▌    | 5/9 [00:00<00:00, 17.80it/s]"
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@@ -306,7 +306,7 @@
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+      " 89%|████████▉ | 8/9 [00:00<00:00, 19.25it/s]"
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@@ -314,31 +314,7 @@
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-     ]
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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-     ]
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-    {
-     "name": "stderr",
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-     ]
-    },
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
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+      "100%|██████████| 9/9 [00:00<00:00, 18.26it/s]"
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@@ -384,10 +360,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
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-     "iopub.status.busy": "2026-08-29T05:05:31.356234Z",
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-     "shell.execute_reply": "2026-08-29T05:05:31.359107Z"
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+     "shell.execute_reply": "2026-09-14T22:46:15.622007Z"
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    "outputs": [
@@ -448,10 +424,10 @@
    "execution_count": 9,
    "metadata": {
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-     "iopub.execute_input": "2026-08-29T05:05:31.360293Z",
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-     "iopub.status.idle": "2026-08-29T05:05:34.026786Z",
-     "shell.execute_reply": "2026-08-29T05:05:34.026198Z"
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+     "shell.execute_reply": "2026-09-14T22:46:19.720911Z"
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    "outputs": [
@@ -482,7 +458,7 @@
      "output_type": "stream",
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-      " 53%|█████▎    | 8/15 [00:00<00:00, 77.70it/s]"
+      " 53%|█████▎    | 8/15 [00:00<00:00, 60.02it/s]"
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@@ -490,31 +466,31 @@
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+      "100%|██████████| 15/15 [00:04<00:00,  3.15it/s]"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\n"
+      "\r",
+      "100%|██████████| 15/15 [00:04<00:00,  3.72it/s]"
      ]
     },
     {
-     "name": "stdout",
+     "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\n",
-      "Decoding:\n",
       "\n"
      ]
     },
     {
-     "name": "stderr",
+     "name": "stdout",
      "output_type": "stream",
      "text": [
-      "\r",
-      "  0%|          | 0/1 [00:00<?, ?it/s]"
+      "\n",
+      "Decoding:\n",
+      "\n"
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+      "  0%|          | 0/1 [00:00<?, ?it/s]"
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@@ -646,10 +622,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2026-08-29T05:05:56.903843Z"
+     "iopub.execute_input": "2026-09-14T22:46:19.722372Z",
+     "iopub.status.busy": "2026-09-14T22:46:19.722299Z",
+     "iopub.status.idle": "2026-09-14T22:46:33.872756Z",
+     "shell.execute_reply": "2026-09-14T22:46:33.872412Z"
     }
    },
    "outputs": [
@@ -666,7 +642,7 @@
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+      "  1%|          | 1/100 [00:00<00:11,  8.27it/s]"
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+      "  2%|▏         | 2/100 [00:00<00:13,  7.45it/s]"
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+      "  3%|▎         | 3/100 [00:00<00:17,  5.67it/s]"
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     {
@@ -1514,16 +1306,16 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:56.905677Z",
-     "iopub.status.busy": "2026-08-29T05:05:56.905561Z",
-     "iopub.status.idle": "2026-08-29T05:05:57.384498Z",
-     "shell.execute_reply": "2026-08-29T05:05:57.384058Z"
+     "iopub.execute_input": "2026-09-14T22:46:33.873840Z",
+     "iopub.status.busy": "2026-09-14T22:46:33.873781Z",
+     "iopub.status.idle": "2026-09-14T22:46:34.241732Z",
+     "shell.execute_reply": "2026-09-14T22:46:34.241429Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x280 with 4 Axes>"
       ]
@@ -1593,10 +1385,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T05:05:57.385549Z",
-     "iopub.status.busy": "2026-08-29T05:05:57.385487Z",
-     "iopub.status.idle": "2026-08-29T07:46:20.998461Z",
-     "shell.execute_reply": "2026-08-29T07:46:20.998035Z"
+     "iopub.execute_input": "2026-09-14T22:46:34.242835Z",
+     "iopub.status.busy": "2026-09-14T22:46:34.242777Z",
+     "iopub.status.idle": "2026-09-15T01:00:59.915147Z",
+     "shell.execute_reply": "2026-09-15T01:00:59.912019Z"
     }
    },
    "outputs": [
@@ -1613,7 +1405,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "  9%|▉         | 1/11 [06:59<1:09:56, 419.66s/it]"
+      "  9%|▉         | 1/11 [07:23<1:13:50, 443.02s/it]"
      ]
     },
     {
@@ -1621,7 +1413,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 18%|█▊        | 2/11 [14:33<1:06:00, 440.04s/it]"
+      " 18%|█▊        | 2/11 [15:10<1:08:37, 457.48s/it]"
      ]
     },
     {
@@ -1629,7 +1421,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 27%|██▋       | 3/11 [21:54<58:41, 440.18s/it]  "
+      " 27%|██▋       | 3/11 [22:52<1:01:14, 459.32s/it]"
      ]
     },
     {
@@ -1637,7 +1429,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 36%|███▋      | 4/11 [28:53<50:22, 431.72s/it]"
+      " 36%|███▋      | 4/11 [32:45<59:45, 512.28s/it]  "
      ]
     },
     {
@@ -1645,7 +1437,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 45%|████▌     | 5/11 [35:55<42:49, 428.28s/it]"
+      " 45%|████▌     | 5/11 [43:37<56:16, 562.76s/it]"
      ]
     },
     {
@@ -1653,7 +1445,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 55%|█████▍    | 6/11 [43:02<35:40, 428.01s/it]"
+      " 55%|█████▍    | 6/11 [51:30<44:20, 532.15s/it]"
      ]
     },
     {
@@ -1661,7 +1453,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 64%|██████▎   | 7/11 [51:09<29:49, 447.28s/it]"
+      " 64%|██████▎   | 7/11 [59:57<34:55, 523.78s/it]"
      ]
     },
     {
@@ -1669,7 +1461,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 73%|███████▎  | 8/11 [58:40<22:25, 448.51s/it]"
+      " 73%|███████▎  | 8/11 [1:07:58<25:31, 510.36s/it]"
      ]
     },
     {
@@ -1677,7 +1469,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 82%|████████▏ | 9/11 [1:06:09<14:56, 448.41s/it]"
+      " 82%|████████▏ | 9/11 [1:16:09<16:48, 504.22s/it]"
      ]
     },
     {
@@ -1685,7 +1477,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 91%|█████████ | 10/11 [1:13:41<07:29, 449.64s/it]"
+      " 91%|█████████ | 10/11 [1:24:12<08:17, 497.70s/it]"
      ]
     },
     {
@@ -1693,7 +1485,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 11/11 [1:21:11<00:00, 449.78s/it]"
+      "100%|██████████| 11/11 [1:32:21<00:00, 494.99s/it]"
      ]
     },
     {
@@ -1701,7 +1493,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 11/11 [1:21:11<00:00, 442.87s/it]"
+      "100%|██████████| 11/11 [1:32:21<00:00, 503.77s/it]"
      ]
     },
     {
@@ -1724,7 +1516,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "  9%|▉         | 1/11 [02:58<29:40, 178.10s/it]"
+      "  9%|▉         | 1/11 [01:43<17:16, 103.62s/it]"
      ]
     },
     {
@@ -1732,7 +1524,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 18%|█▊        | 2/11 [05:58<26:53, 179.28s/it]"
+      " 18%|█▊        | 2/11 [03:30<15:49, 105.49s/it]"
      ]
     },
     {
@@ -1740,7 +1532,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 27%|██▋       | 3/11 [08:47<23:17, 174.67s/it]"
+      " 27%|██▋       | 3/11 [05:18<14:15, 106.88s/it]"
      ]
     },
     {
@@ -1748,7 +1540,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 36%|███▋      | 4/11 [11:40<20:17, 173.99s/it]"
+      " 36%|███▋      | 4/11 [07:09<12:37, 108.19s/it]"
      ]
     },
     {
@@ -1756,7 +1548,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 45%|████▌     | 5/11 [14:31<17:18, 173.08s/it]"
+      " 45%|████▌     | 5/11 [09:00<10:55, 109.24s/it]"
      ]
     },
     {
@@ -1764,7 +1556,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 55%|█████▍    | 6/11 [17:24<14:24, 172.85s/it]"
+      " 55%|█████▍    | 6/11 [11:02<09:29, 113.82s/it]"
      ]
     },
     {
@@ -1772,7 +1564,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 64%|██████▎   | 7/11 [20:19<11:34, 173.65s/it]"
+      " 64%|██████▎   | 7/11 [12:56<07:34, 113.67s/it]"
      ]
     },
     {
@@ -1780,7 +1572,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 73%|███████▎  | 8/11 [14:50<05:41, 113.81s/it]"
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     {
@@ -1788,7 +1580,7 @@
      "output_type": "stream",
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       "\r",
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+      " 82%|████████▏ | 9/11 [16:47<03:49, 114.82s/it]"
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     {
@@ -1796,7 +1588,7 @@
      "output_type": "stream",
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       "\r",
-      " 91%|█████████ | 10/11 [29:16<02:57, 177.36s/it]"
+      " 91%|█████████ | 10/11 [18:39<01:54, 114.08s/it]"
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     {
@@ -1804,7 +1596,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [32:13<00:00, 177.37s/it]"
+      "100%|██████████| 11/11 [20:34<00:00, 114.23s/it]"
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     {
@@ -1812,7 +1604,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [32:13<00:00, 175.81s/it]"
+      "100%|██████████| 11/11 [20:34<00:00, 112.23s/it]"
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     {
@@ -1835,7 +1627,7 @@
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       "\r",
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+      "  9%|▉         | 1/11 [00:48<08:00, 48.01s/it]"
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     {
@@ -1843,7 +1635,7 @@
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       "\r",
-      " 18%|█▊        | 2/11 [03:15<14:40, 97.79s/it]"
+      " 18%|█▊        | 2/11 [01:36<07:12, 48.07s/it]"
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@@ -1851,7 +1643,7 @@
      "output_type": "stream",
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       "\r",
-      " 27%|██▋       | 3/11 [04:53<13:01, 97.72s/it]"
+      " 27%|██▋       | 3/11 [02:24<06:25, 48.21s/it]"
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     {
@@ -1859,7 +1651,7 @@
      "output_type": "stream",
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       "\r",
-      " 36%|███▋      | 4/11 [06:31<11:25, 97.87s/it]"
+      " 36%|███▋      | 4/11 [03:13<05:38, 48.42s/it]"
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     {
@@ -1867,7 +1659,7 @@
      "output_type": "stream",
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       "\r",
-      " 45%|████▌     | 5/11 [08:11<09:51, 98.53s/it]"
+      " 45%|████▌     | 5/11 [04:02<04:51, 48.65s/it]"
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     {
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      "output_type": "stream",
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       "\r",
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+      " 55%|█████▍    | 6/11 [04:54<04:08, 49.71s/it]"
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@@ -1883,7 +1675,7 @@
      "output_type": "stream",
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       "\r",
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+      " 64%|██████▎   | 7/11 [05:43<03:18, 49.73s/it]"
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@@ -1891,7 +1683,7 @@
      "output_type": "stream",
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       "\r",
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+      " 73%|███████▎  | 8/11 [06:33<02:28, 49.63s/it]"
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     {
@@ -1899,7 +1691,7 @@
      "output_type": "stream",
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       "\r",
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+      " 82%|████████▏ | 9/11 [07:22<01:39, 49.61s/it]"
      ]
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     {
@@ -1907,7 +1699,7 @@
      "output_type": "stream",
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       "\r",
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+      " 91%|█████████ | 10/11 [08:10<00:49, 49.07s/it]"
      ]
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     {
@@ -1915,7 +1707,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 11/11 [08:58<00:00, 48.57s/it]"
      ]
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     {
@@ -1923,7 +1715,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 11/11 [08:58<00:00, 48.92s/it]"
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@@ -1946,7 +1738,7 @@
      "output_type": "stream",
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+      "  9%|▉         | 1/11 [00:34<05:43, 34.35s/it]"
      ]
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     {
@@ -1954,7 +1746,7 @@
      "output_type": "stream",
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+      " 18%|█▊        | 2/11 [01:08<05:09, 34.38s/it]"
      ]
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     {
@@ -1962,7 +1754,7 @@
      "output_type": "stream",
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       "\r",
-      " 27%|██▋       | 3/11 [04:07<10:55, 81.97s/it]"
+      " 27%|██▋       | 3/11 [01:43<04:34, 34.34s/it]"
      ]
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     {
@@ -1970,7 +1762,7 @@
      "output_type": "stream",
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       "\r",
-      " 36%|███▋      | 4/11 [05:28<09:30, 81.50s/it]"
+      " 36%|███▋      | 4/11 [02:17<04:00, 34.33s/it]"
      ]
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     {
@@ -1978,7 +1770,7 @@
      "output_type": "stream",
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       "\r",
-      " 45%|████▌     | 5/11 [06:50<08:09, 81.52s/it]"
+      " 45%|████▌     | 5/11 [02:51<03:25, 34.32s/it]"
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     {
@@ -1986,7 +1778,7 @@
      "output_type": "stream",
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       "\r",
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+      " 55%|█████▍    | 6/11 [03:25<02:51, 34.32s/it]"
      ]
     },
     {
@@ -1994,7 +1786,7 @@
      "output_type": "stream",
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       "\r",
-      " 64%|██████▎   | 7/11 [09:30<05:23, 80.82s/it]"
+      " 64%|██████▎   | 7/11 [04:00<02:17, 34.38s/it]"
      ]
     },
     {
@@ -2002,7 +1794,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 73%|███████▎  | 8/11 [04:34<01:43, 34.37s/it]"
      ]
     },
     {
@@ -2010,7 +1802,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 82%|████████▏ | 9/11 [05:09<01:09, 34.50s/it]"
      ]
     },
     {
@@ -2018,7 +1810,7 @@
      "output_type": "stream",
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       "\r",
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+      " 91%|█████████ | 10/11 [05:45<00:34, 34.99s/it]"
      ]
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     {
@@ -2026,7 +1818,7 @@
      "output_type": "stream",
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+      "100%|██████████| 11/11 [06:22<00:00, 35.43s/it]"
      ]
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     {
@@ -2034,7 +1826,7 @@
      "output_type": "stream",
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+      "100%|██████████| 11/11 [06:22<00:00, 34.74s/it]"
      ]
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+      "  9%|▉         | 1/11 [00:33<05:37, 33.74s/it]"
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+      " 18%|█▊        | 2/11 [01:07<05:03, 33.70s/it]"
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@@ -2073,7 +1865,7 @@
      "output_type": "stream",
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+      " 27%|██▋       | 3/11 [01:40<04:29, 33.64s/it]"
      ]
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@@ -2081,7 +1873,7 @@
      "output_type": "stream",
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       "\r",
-      " 36%|███▋      | 4/11 [05:05<08:53, 76.26s/it]"
+      " 36%|███▋      | 4/11 [02:14<03:54, 33.55s/it]"
      ]
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     {
@@ -2089,7 +1881,7 @@
      "output_type": "stream",
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       "\r",
-      " 45%|████▌     | 5/11 [06:21<07:37, 76.18s/it]"
+      " 45%|████▌     | 5/11 [02:47<03:21, 33.53s/it]"
      ]
     },
     {
@@ -2097,7 +1889,7 @@
      "output_type": "stream",
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       "\r",
-      " 55%|█████▍    | 6/11 [07:36<06:20, 76.02s/it]"
+      " 55%|█████▍    | 6/11 [03:21<02:47, 33.59s/it]"
      ]
     },
     {
@@ -2105,7 +1897,7 @@
      "output_type": "stream",
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       "\r",
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+      " 64%|██████▎   | 7/11 [03:55<02:14, 33.56s/it]"
      ]
     },
     {
@@ -2113,7 +1905,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 73%|███████▎  | 8/11 [04:28<01:40, 33.53s/it]"
      ]
     },
     {
@@ -2121,7 +1913,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 82%|████████▏ | 9/11 [11:26<02:32, 76.18s/it]"
+      " 82%|████████▏ | 9/11 [05:02<01:07, 33.55s/it]"
      ]
     },
     {
@@ -2129,7 +1921,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 91%|█████████ | 10/11 [12:42<01:16, 76.18s/it]"
+      " 91%|█████████ | 10/11 [05:35<00:33, 33.55s/it]"
      ]
     },
     {
@@ -2137,7 +1929,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [13:58<00:00, 76.10s/it]"
+      "100%|██████████| 11/11 [06:09<00:00, 33.48s/it]"
      ]
     },
     {
@@ -2145,7 +1937,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [13:58<00:00, 76.23s/it]"
+      "100%|██████████| 11/11 [06:09<00:00, 33.55s/it]"
      ]
     },
     {
@@ -2249,10 +2041,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T07:46:21.006946Z",
-     "iopub.status.busy": "2026-08-29T07:46:21.006819Z",
-     "iopub.status.idle": "2026-08-29T07:46:21.015728Z",
-     "shell.execute_reply": "2026-08-29T07:46:21.015424Z"
+     "iopub.execute_input": "2026-09-15T01:00:59.921667Z",
+     "iopub.status.busy": "2026-09-15T01:00:59.921315Z",
+     "iopub.status.idle": "2026-09-15T01:00:59.947144Z",
+     "shell.execute_reply": "2026-09-15T01:00:59.946749Z"
     }
    },
    "outputs": [],
@@ -2275,16 +2067,16 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-29T07:46:21.016697Z",
-     "iopub.status.busy": "2026-08-29T07:46:21.016627Z",
-     "iopub.status.idle": "2026-08-29T07:46:21.170928Z",
-     "shell.execute_reply": "2026-08-29T07:46:21.170589Z"
+     "iopub.execute_input": "2026-09-15T01:00:59.948609Z",
+     "iopub.status.busy": "2026-09-15T01:00:59.948564Z",
+     "iopub.status.idle": "2026-09-15T01:01:00.125251Z",
+     "shell.execute_reply": "2026-09-15T01:01:00.124928Z"
     }
    },
    "outputs": [
     {
      "data": {
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ihXLi79n9M28xi6RjrAtmcEhZHDTaHDg0J16Hv07WQKcFHMxj+yoKHFFAiXHiWrVqaYWWJPAJgsY2MegadIIXKwuEuC6CDQR+/vlnDBkyROiDsMkAY2HJgbFtOWh0PHr0KMkBzqzIJavxmPXZYhxao3nK9iicEwN+6YXGPetpuwfp89BNi9OFqdPiiOev/BLMo8v7/GXC+WmB+W/JZsDy6ovivY/hAOb7u7GFygKTbk5N4EmroEI++7z4qdwP2nkWehWCsytrskGMAT1aFvL8/vvv4j89Yt3wh+RJJ5bdQtSrVw/ly5ePN4/hId6ZacC5PmZqSF1fOIjIAVkO2mzbti3R0IccPDWCYRu5QC5csgIP3Se51oM+xvndV9BnfBe0G94CNnrpbfo8WOlnymq/pFAwbw6DnnTBfDlMuh15/BozGHaWcVkmRGSMCjaWNtr3nfK3EzFoXQNNg90lf4cE301qvcmhdevWotcgdTsIZm7oe9IMgSQWkTL0Q/nqq69E/nnx4sVx+vRpkenBG4AUFuGI87Fjx5KMTevzMBc4Gi+HFk1y4pLZeKREle7FAy+sGL8OBUvnw6eTe4p5FRqUwf+eLYG9o50sjkd0dAx8A0KQ290FA3vUETFoXQPNn+qA7nVNus0saaT1oW8Ea+SohmHFBmsHD+lB00BXz2FcqypjwHg088al9B9DPIi8eVOW38nB2N27dwtRf3YF/+ijOA0ShjpopBkGYUyaNwBDkIvmFsck5AK5cMlsPIxRpfP3DsTayZuw+49DIgZNLY3uYzuI/0RiBjqjj0dwSAR+nLkDL98E4I/pfdCodklMHN1aO3hYpIC7yI9uVLuESberGGkDj/csC3eziXtk+bRwX1HMwvmmKAunEfzrr79EvjIHEDmoxzi1qcIMbdq0MTjf2DJ7uYQ7WJUqF8iFS2bjkVSzVmZsbJm9CxtnbkdYcLj4vGbrKhg0rY/WQMvleHh5B2Ls1K0ig8PezhrPXvgiJiYWHjnjBvy++fxj2NpY461fMNxzmK5pRoam4MkVupWLUlm4VG1IcHrCzSlivimwcuVKkY7IQdJPP/1UlMAz24UvOR4Pc4EZJXKBXLhkNh4MabzRiduyWevrpz7wvPtSpNOt+mmDMNAlqxfDrCOTMHXXDyhSoZDJeaQFtx944fPv/icMNI3v4qm9ULlcAVFxOHz8eu1ynP5s7Box35RQ9KQNID0FlmgAOXjHmDHBij/2MSxRokSSmRzmhNKZRUFqkZgw/pdLBmPxlyvhnt8NA6f2QsNudbQZG3LC8fe50BGR0ShRJBd++74TcrlrsrDoMfvqaFFLcMvuaJQnLdsUPDlCv6cfDXF6qd0xb1ky0ATL4jnYZ4iHuSAXHnLpoycnLpmNR2LNWncuPYAZhyaiVM3iaRI9OpeOx+PwqbuYNGeXGAysW60oJn3dFg72cQkGNMSSMU5PHoonrSBZKMdQQWrR2r636KytD2s7a+wJXQc5IzAoDJ9/tw61KhfGyIFNYGVpWk/fWE9afs8XZoB+GbR3SDBuer9J8OL8jORhLsiFh27mi7khFy6ZicfLh16wsEzYbciUqnRXTHw8IqPiahWyOdtj+Yw++GrwR8ka6PQ8L0q4w4A057ob/2H+eY2ClS5G1aqN0bXrZhgPc0EuPPQLdcwJuXDJDDz4cM50umXfrEJEaHx9G1M3ay1vwuPx2ucdvv11Kzq1rIyOLSqLec5JpP+lFw99KJ60gbZVvStUxMZuceXrnN7Rq4+Yn5E8UgPKIbLMfM+ePaIkXJJDvHPnjtBEoVbIb78lXRkplzZexpSwZzUumYHHb/0XiCyO8JAIVGpcDsPmxrW/K1yuAH7a8o3RzVoz6njcffQan3/7Pzx69hart5xHuIEQTUbwMATFSBtoF5XL0QkvdZoI/HjkEF68eyfmZySP1GD69OlicJLVjNStXbVqlVbYii3Lxo8fjwMHDiQp3CSX9llyqKyTG5fMwKNW62qwtrXG0N/7i8HBVp811X427+xUkxloUx2PkxceYsSP60UlYbFC7ljyay/YpbC7SnqelyxppEOjohJ9RURHY9/DB/hqv0bUnHjg64vhu3di+9078ZYNj45/t+U8c4Nect26mpAMU/2qVq0q0vyWLVum1QZhJaKh1mVyA3nLBXLhIkcewQEhuHfpkfZ9k5718Pf9+ejyVVv4vwnEo2tx0sOcfnDlscmkQ2PScDwYdtm48zJ++O1fhEdEo1aVwiIHmiXfGckjOWTJmHT5xQsS/axx4SJ4HRzEhg5aeSXpv67hJmrly49/usbJHzZc+ScuDRmW7PYpbnT48GH07dtXm7bDDhU80RUqVEBaQD0PdpygmFLLli1Rp04dMZ9a1VIlIR/NmjRpInvtDrkMYMqJi9x4XDl8A7MGLEJUZDSW3/gdrjk1LeZyFXDPkI7aIak8HjTQc/88gi17r4r3HVtUwuhByQ8QmpqHMciSRjo5PPb3T0ehUqBjx47CmH777bdCS5saHsyzZPWhvgoeC10Sy5KkSBI9ZX1QBpVa3RMnThTGn33gWN0otUZiizFDkrESpGXNDWN0xLMaF7nwyOHqJjpzb5uv0a3IW9xDeM2Skc4o6dA8qTweHMB0d3MSokhf9G+MHu2qxdNQNwbM9vJ+b5wjrK1EBhiRy9HRpKHRLJknrR+WYI9ANhkgLFUqdNqwDvfevo1nqHn6Srq5Y0uPXtp5FirAzirOoHG9DikwcOxyzAG+HTt2YNSoUULRS+KRWgQFBWl1qRn64E2A2yDY223KlClivtQQ2BB0j4c586R5Q6HmthwgFy5y4HH/8iP83H0WvJ+8Fe/bft4MQ2Z9kqQQUkYdj7cpqAKk6bv3+A1KF/NI1bbnnjuTpiwwpeIwCegbUods8e/+o2rVETFoCVLoY3TtOkka4ZQYaKJz585C8GjdunXiLq5voJPzpPl93W7gXI4NedlsM0eOHMJblzI1mOXBEMjcuXNF2IMDivS2De5HGm8UpoK5jZEcuZiTB6+vdVO3ivAF1epyeLhizF/DUbNVwo705joe2xN08Ia2g3f9GsXx5z+n8POYdqJykL+51Bpogtle9QsWQvdNG7RZYHZWVsKTNiWypJFOrgy6ZfESmNOilTYGTQ+aBrpFcdNKENKQUmpR8mr1eVBPmp1bjAUvOqrrXbt2TRj4/fv3Y86cOVqDzoFEijtRP2Ts2LGJrkcpC5cvF3Py4PX16vFrYaDLNS2JyRu+g4tb/G5C5j4eHZpXQo1KhbTCR4un9hTKdBTnHzFhPcLCo/DHulMYrZNxklowpOFkE6chXzZnrhQ7asYgS4Y7jAFDF9IA483hI01+8I8cOSLCEowN85FNv3VWWsH9lvaXp9jPL35LH27PxsbG6HUpZeFZE7x2wkPCYe+kKXAKeReKS/uuCUGklMZwMwph4ZFo1nu+mD64bhR2Hb6JBSuPIjZWLQz4lG/aw8kxZQ06EgMzvuKcOTcR5qCTl6nLwpnZsGnTJmzcuNHgYzwb0tJoZSQYg9UfELjt4619z2lTloVzMI+Gr0aNGkL7+Z9//jHIIy3QNab8MVF3V/eVlIE2JY+0IKOvg8zAxRQ8mP7GNDj9l35a3NtXfvih9VRM6TFH+1t1dHFAo+518d9//0Gux+PkhYfa6S5D/sC8v44IA92uWUXMHN/ZZAY6sVRdzs+04Q4aZxonNkRlQcW8efMSiNBTAJ/drNkJWwoDUCVOyv1ND+h7h/pl4VLMyRRl4Qw1XL58WRwDsc5Ro4S2ND1buUiVysVbZr9GuUAuXEzBw5huKcc2nMb84csR5B8CGztrPL3liSLlC5qUhylQUo+HJC0q4d37ZgItGpXFuKHNTOr9zz9/NkGqLt8vOH/OaG9adkaag1UcuCLY0fqbb75JYKTp+rMajmlgvHsz80Hqfp1eYFyYVXq6AwIfFy2WYDlTDAhwO5KBJqgjzbgac5PlUqigfzzMBS8vLxQtWhRygFy4mIJHUt1SgvyDsWDEnzj6z2nxWYlqRfHt6pEoVCa/yXmYAl56PFZsOKvtNSiBhpMxaVOHZwyl6vL9Y/9M3C2coQxpQIoxGLZj1wdjtFKDVWY9/PjjjwbLlOmR6nYQYXwntdAXG+eAQHqXgOtvny+5DA/IRXw9qTTBrMrFFDzYLcXBJU5Eq1jlwiJ97vLB65g1cDHevvSDhaUFev/QGX1+7AIra6tMcTy8vAPh+covnoEm+Pb5S9MaTiKfszOeBATEm8fbQNHspu0WnqG/RhpV6VGadzWWKet7j5KBvnnzplg+sR5m06ZNE0F36cXUM4KFGsxsYNUd089u3boVryKI8VZuk+vm5+RAz5EGUlrm2Ys3uPfoDf67/Rx3HrzCzXsvxMv7baDIZSYk4SJ+RwyuhIeLdXGdXDe3IcV2dZelx8xluU2+uCzn6S/L95zPz6Vl+T3Ok3jqLqu/T1xWd5+kZcmfy3I5vjitv0/Sd3X3if+5Lt5oCXr/kkQjP+fx5nFnLjZTALlOKV4oLcv3nM/PuZzueZKkHqVluR3OZ3UkNUjYWoziUeRx8eLFeMsyxs+b9IsXL8SL05ynuwy/w+9yHVwX18l1c5+N2SdeV6bYJ24vLftEh8UU+7R3zSHtb2lI5a9xfNNZzBy8SBjonIVy4LfDE9Cgfw34+vka3Cdu01T7lJbzFBsbi6vXbmHG4j3oNeIvONpbC09aF3yfM4e9yc/T2HoN4m/n/Q2hU778Ru+T7LI7SpUqJTQjaIglA5wY0Z49e2LJkiWJCpcY8qRpqFOT3aGbCUH8tf50ormW7AacXtDnYS7o8zBXdgd/RAwHyQFy4WIKHom1tBr4a2/4vvTDoN/6ws7BVvbHIyIiCktWH8S+448QHKqxBRXL5MN/d15ql5FCH1PHdTBJF29q+zwPDESJ986jbnZHqRSm6sqymKVRo0Z4/fq1MNK8k3Fw0BDoNR46dChJZSnGTE0VN9XPdEgs15JVS+kJY1PijMHp06dRr178Gwo9blYg5s+fP0mNEFPySAvY3VwukAsXU/BIrKUVBwuXXZ2VYTxSi5iYWOw/fht//nMa3r5BYl6xQjkx/JOGqFm5MA6evKMdPCxSwF04VqYy0EN37cAVLy+s7tQFlTw80KxYXCs8ViOnR550hoY7OEjI1DuWLv/555/4/vvvxXwODlJCUwIfhTKy6k163JfA8lE2nZTA6VLFcpu0TbsxPFIDZo5QrpTFK7rgzXHYsGFC64PFLjTi6cnDFGDISy6QCxdT8Hhx71WC8Q++97z3KkN5pBZz/jyMXxfuEwY6u4stxo9shRWz+qFWlSLiZtOgZpzhXDa9t8kM9LDdO3H82VNExcYgLDoq3VN1zeJJU+iHhpqxmiFDhmjFUehRU8dC9y69e/fuDONlaBBEN9dyyHf/wyBxN07ftCNTDMZUq1ZNvChNqguKOTG1MXfu3OK4s9oxPXmYAobEo7I6l7TyuH7sFmJjYtPc0iqjj0dsrBoWFMsB0O7jijhy+h76dq6JLq2rwtYmzoxRu+PVm7jBvAdPvLVPwal1smigmf987OkTUfb9V/uOqJ2/QALtDlOm6iKrVxyyIkkXHBCTDBMzG85deYzxM3YkiGtNHN063l3aQqWCrY44ONdrb5d8qIDxvPv376NZs2ba0AIHQDiYQJ6mANfD/SY4OMgQx+bNm+Hj4yPCSd26dTO6LNxcMWm5lGLLiUtqefD6+ufXbVg9aYMweLqQQh8p6ZiSUcfj5esAUcbt5uqIUQPj5HXZOYXC/Po8TD2eRAM9Ys8uHH7yGLaWlvirQyfULVAwgQoeBxulEKKxKniyjEnLBVLJqCHUqVoE3r7B8XItpf+6SfJE5XL5sXBKT+37bkOXY9ffXyS7fRo9Zp2cOHFC28qKmhtdu3aNtxzj9hRFSgzUhK5YMfmWXi9fvkRAQIAQVqJMKvPTeTPq0qWLweXloNtByMEoyo1Lag30hPbTcWGPRju5+aeNUaFBGfz+2RJtS6tPfu6eoo4p6X08At6F4u9N5/Dv/muIjo6FjbUlPulaC64umjCo1DlFnwfHkyikpI/UjCdFxsTEM9B/to8z0EROu1DktNEoAZZryKjA2zh5TJjuN5QljXRyMJRraUrwjluwYEHRvJI9BxnaadiwYYKBUAossTFAYuBd2BgwtEGjXL16de32Wf2ZmJHWlyo1F3S9E3NDLlxSw4Pnvlzd0rh+9BZGLhqEFp82QVhIuNZIs6VVSmVGjeWREulQyUNmt5T//XsBIe+b2NasXBjD+jXUGuikeHCdpho7ilXHIjw6Whjo5e07ol7BOANNqEPXAyELE37RcQRUzqNgKmRJI03RFf3RYsv3HRl4QQ/59n94/NwnftWSSjNSzIEI3XCHLjYtHWw0BxrYmjVrikG+Bg0aiPRE/ZxxU3nS9IxpqJmySOPL3NCkvGU5VBsSpgr9fEhcjOVB7/mdb5BWhL/ndx3RuEdd5C3mITQ6vB5rBOqlllZSxSELXUzJIynpUP3ww427LzFh1k5h2KUB++H9GqJG5cJp5pEaUCt+efsOuPv2LSp7JGwuEGjVGv62JYF3P2hmuPwKlYUNXK0KwpQdD7OkkdaPG9N42drGzRvYo47BmDQvqqRizsbEo3XRqlUrHD16VFRVEkx4162upCfNEvLEhg1cXV0NzufyzNCQUquIr7/+WqTfcZtnzpzB4MGJ31D0eZgL7Fgjl9CLXLgYw4PGecanC/HmmQ8WnJsmcp7pfNBAm6qllbHHIyXprPk8XBESGgGPnC4Y3Ls+mjUoox0sTCsPYxEVE4M9D+6jfanS4rdDQ23IQBNHfW9h20vqzr8fRH29WfzrlK8dOudPGHJJLbKkkdaHfk0/szg4SJgeuZYSmIZI+dBLly4lyoNIKgvDEB4+fChi3WzFRe1ohlGKFy8uRKqoQLh27VqMHDkyydF5uUhQyqWNl5y4JMfj9tl7+KXnHPh4+oqO3fcuPkSlRuVM3tLK2OPB0IOjQ5zzQu9YcmbuPPDCyYuPMKS3pl4ih6sj5vzUTSyjm7GRUeeFBvrLfXuEih31N76qk/RAY9NcjVDTwRvRwYvhYR0KtUVBvLPtD1uHRjAlFCNtQKuCj1u8m0v45vOPxd2f800R7+Kj6IoVK4R3u2/fPmGoGS82hWYGDTJfifVEzEzaHfb2cfoS5oZcuCTGg09Nm2fvwl/f/0+I8ucrkQcTNn6NYpUShgrcUhDWSCkPQ9BPZ+3UojKu336Bw6c1peXVKhQUL6J8CtIATXleaKBHvzfQNpaWqJIneR7ZYs/DJXImYq01Y4Vq9XPkDJ8MlV1O6u7BVFCM9PvHe6mTtqE4mvSoZqqycGZysHUVt0mPd8GCBfj999+FcUyp55wRx8NcoF5GUlWnWZGLIR5Urps5YBHO7tA8lTH2PHrZ50L7OSN5GIK+dOiT576YvfywmOYDW8vG5ZA/j2u680jOQLO0e+97A72kTTs0Lpx8rFsdvBAXQ92xPaAgXkc5CG+6o+tzVLdaBJWdYqRNCv2BMlOm8eiD8e+PP/5YG09m9gbzkinC0rJlS8gBchk4LFYsoVxsVudiiAelRWmgrW2sMHT2p2g3rHm6h6yMPR6GpEMJBztrLP61N4oXzpkhPBJDdGysMNCMQ1tbWGBxm3ZoUsQ4CdZL7wKw0KcsVFBDDRVeRDligU9ZjMQ91HSHySCP51ozQ78TCUMaLAPXf5ki1EEDqDsiTe95+PDhYkBPLh1R5MKDDSDkArlwMcRj8G/9ULpWCcw9/QvaD2+RIWMKxh6PxNJZo2Ni02yg03peGCL6Op6Bbo+mRhpodcQ5bAvIJ3TvaKDFPKiEwf430LQ624qRllEZtMIjPtheTC6QCxfyCAkMwcE1x7XzcuZ3w/wzU1GyWjHZHY8CeXMYlA4tmC+H2c+LSqVCvQIFRYiDHvRHRjYxUIftwFufYXgZxd9J/J2joX4dZdonUcVI6+gop7QHXHrzMBfkwkPS45UD5MJl66rtGFbtW8zovxCn/71gtoyc5I5HZFQ07j58LdJZ9esN+H5A97qyOC89ylfA0f4D8ZGBTkyGPO/YoCU4+XIGxr+qpPWgdcE5eexTNviZHJSYtIEyaGN6wGUED3NBLjzkUoqdEVzoAPgZcAKkAhMaiJ1LDuDPr9cjKjIaHoVzwt1E3qipjwdznX/4bTtu3X+FeT/3SNd01topPC8xsbGYe+4s+leuAvf3VbV5nJ2T/Z5aHY2YwMlY5Hkdl0JLi3m5bXPjTURcUZAm2KFGp3ztYUooRvq9NKduKk9SPeAykkdqwK4TLDPniDflSZlFktISb1PwMAXYtYPKiXJAenNJyjHo8nVbzP18GY5tOCPm1e1QA9+sGA7n7E6yOx4sAf/mly1Cfc7ezlqIjulLh6a06CslPHRFj3RB0SM3ewd8c2Aftt+7i6NPH2N7zz6wNDbdNHwPLMLXI5tlcVhChc75O6J17qo473MMS59rslXy2WVH57z1UC1b/H6QaYVipA2I3NNzuXY0Ti933rA/8MmkHihRNX0bb5pCbH/+/Pn4+eefRQod2wKx+S91pDOahylA5T65IL25JOYYBPkF44sa3+HlAy9YWlmi76Qu6PN9V7MXHBk6Hp6v/PH1lM3wehOI7NkcMOvHLiIjigbblNKhSfFYd+O/ePKhEkbUrIWX794JA21lYYERNWsbZaDDY8IRHhOBbHbtgMjL6Fm4Fpqoy6OQY0HEBs1HVfViii2LZSfm3AHbmH+hDjWtdkeWjElTXEb3FfIuRDsdGR4p2gtN7xunlPfs1gvRbujwupPxvhcRFpFgvWmBKbqFU5dj9uzZomCGjX5To/srl67laWkunNm40DFgQ1gJnKZTEBwQIgx0zgJumH38ZzT+pI7ZDbSh48HqwWE/rBMGmuXdS6f1FhlRrDmQ6gwITn82do2Ynx48eleoiI3demjfc3pbj16ignDb3TuwVKkwr2VrtDSixdW9gFMYf2MSFj/8Q4QxLLL9DDuH1sJAS9odz+3i7ASnn9kvFfNNiSzpSbd37pfoZzVbV4HPC98E7YUIXcNNVGxUFr8f/Vn7vl+R4djsvSLZ7bM8++DBgyJHum7dutpOF9xOWpXW2FShdevWQpipd+/eSepGK5AXzmzXNDklRtX5QTy9NexaB1/9MRT1O9WEi5uz6FokNzx86oNRP21EWHiUMMyzxndGdlfHdK85MATqODvZxGVXsO/g5OPHsOfBA42BbtUGrUok3bwjOjYaW5//gV1vLovBwRh1LPwi/eFu65aIdocGvzzYKP4r2h0ZgBf3vRIVNTIFWJ7NDinslsLGvBTiZzHLJ598kkAFj+GLxLhwPfqeMrtXf/bZZyLXmR3VafRptFMCOYgrEUkJoX9oXBJ7epu4+Ru0HvRRhvEwFro8ChdwE2XdEZHRouGrg71NukiHGkJyx4Ohjy13bmkNdOtkDLRn6EssfTAbz8MDxVBgfedI9C0+Bo428Q20pN1RNXtlMR0cHAInJ82Nx9XaOAlhY5EljfSOoDXx3oeHhcPOXqOnS8nSEbW/x9MbnvGMIz3rwuULYN6Zqdp5+gpda54wPmUc6EFTwYshCQ70UfSIzQB0B+yogjd58uQU7duaNWvwzz//iOnmzZtj7NixKTbSDJnIYeCQXqNcBg7Tmwubw4r8LW2jCY2C4dopm9Cgcy3ZHRNPT0+UKVNW/AasLC3w89dtRWGWtXXG3uBfGDgeBx/FaYUcefIYOR0cMKFRkyQNNLWj974+iM2emxGtVsPJIgoDctuiRv6lUFkYHnh3tXEVL+L2s9sonDt9mvOaxUhrpEFtzaYhoS9wrv++38TuBlveM/0uKXH0lAqns1ksRZZoVLkNfcOYnCfN71epUkX7nsvptreil52a8IkcDDQhB2OUUVw8777SGuikmsPK4Ziw/daRC97YccwT372vcNRtI5eRKKt3PCiQxDJvCU8D/MVh5WBhUoiOjcKpN9uFga5k74uB+coje45JUKmMu+mk53lJlQXkoBS1ifmoQdH5O3fuGCU+zyA/Re6Z28iu1tQ0NjRKfOHCBW23Ekp6suVTekK/px89l+/WjtI+fqamvZAxoH4HvVYpRU6fR0o9af5YeKyY3cEmAkzBY4w6pdDnkdX7CqY3Fwrwq2ONaw5r7mMSFRWDqQv34tDJu+J966blUamM+bJwzukdj+mnTsT7nAaaDygLzp9LMFjIm6AYEFRZwCp4GobkOIsnEc5o7NEHKqchKRqgTc/zkuJGtHwkpxB9vnz5xIuP0zTYLCWW2jMlhu+//x7t27dHnTp18PjxY2FMmCKmC8ZnOaC2Z88eoXA1btw48Qhvyka0xoCZGtIAI8MjKfWSk8OhQ4dELjMH9q5du2byWCONv6lS6czViDYrwO+1P0bXnxCvU0pqm8OmN0LDIkWRyqX/nomw4PgRLdG8kfk9e8I3NBS/nT6JzbdvwRBY+n13xJfa94FR77DiyWoUdSyMDvnaQh15HWr/z6By+Qkq+3bICBjbiDbFKXinT58Wj+Bz587VuviNGjUSsdXkwIyGvHk1ngH/79+/P8EyS5YsQYcOHXD27Fl4eXkZZaDTCnYL16/+YkshCZw2ZVk4MzkYyqlWrRratm2LdevWGeSRFqTFQJuSR1rAwVS5IL24zBu2XBjoPEVzY8TCz7Tz+fRmyECb65j4BYRgxIQNwkCzSGVQ13KyMNDnL1wQudEfr16pY6D1/U413J3iwhZX/K/hh/9+Ev93vtqLoKhgqGwqQZXzSKoNdHqelxSHO5ydncWgQZ48cS1l6PGyG3VyePXqlVa8hx4Z7yQMneiKzNOr5N2FOst79+7FgQMH8N133xmMa/NlijxW/Yo8U7QXSgzkzAyMPn36iPejRo0S07yT8ilDDpBDE1pCN97+oXIZufAzhAWHY/TSIcju4YqFI/5KsjmsOY7JCy9/fD15M169CYSri70oUile2IRanKnEHR8f/ProAW54a55CyubMiSZFCmLRhcvaZTRjsSp8Xbs+wmLCsfbZepzwOSU+y28dic+L9YaztSa0p7JI/dNsep6XFHvSbJ76xx9/iNgnu4t8/vnnIhWsR48eyW/MwkKb3sVHuaioKINxHw520VDQy5wyZYpYTh9ML6Mxl14FChTQ3jA44PbgwQPxyH/r1q143iFT01isQWPJz+nR8jPykZZp3LcuFl/6DXNOTcaC89Mw7+wv4tVyUFNRMq0rQiR9lyEBrovr5Lq5DUnyU3dZtvthl27uE1/kzZ6D7dq1E4Ok0rL8Lm9gXJe0LLfBeRJP3WX194nL6u6TtCz5c1kuxxen9feJ4wD6+yQdJ3Zn1hW2YVUjP+fx5nFnWTpDWVwnb0a6y/I95/NzLqd7nrge3WW5HY51PHv2TNzc/f39ce/ePcFD8lqkZVkazJs0R/r54jTn6S7D7/C7XAfXxXVy3dxnY/aJ3XNMsU/cnu4++Qa/xa97f8Cd+3fiPb0d2nYU107cwM3Lt+LtE59YTbVPxp6nO/ef443PO+TJ5YKRfSuhdHEPHDt2LNF9yqjzdOP2Ldz0fgMHKyuMqVYDy5p8jE65C2Bq47j2Vfns7YWIv23YK+E900DT4rRy8cKkPOeRP3qNUecpuX3iOlKzT+kSk5ZAD5ckmO9LT9CYgSbGojdt2iQGC2kIypUrh+fPn8dbhgNdHIQcOHCgeE8PkxcLB9GS86Rp8BKLSRcuXDjRrAW5dCKRKw/+YJ8+fZrhMWle0HLohmJKLvy5zRv6Byo2LoemvTTlxMTqSRuNEvUy1zE5deEhypTIoy1CMQcPtVqNO299UDZnLu28VRcvoFXZsqKIRSwT4w3/UE9UX6GRcr00sBGsrNT46uZfiIyNgru1HQbnuIjSdv6ATT2oXBdAZZH2QfLUHA9jY9Iptgi0/gxZMAeXr40bN4q7Ow1rcqOh9L7p2dJI379/X8SeJbJsykpDyoG0LVu2iPm8i3OevoEmmMJnTBqf5LknlftL71QOkCsP6Ykgo5ux8uYgFyNtKi5/frsWu5cfwv6/j6Jc3VLIXShniprDmoIHe3VSCEkfunoah0/dRcmiuVEgr2Zb9XVEkkzFIyW49/Ytfjp2GFe9vLC37ycoml2jANgsX36tgSbevP0HB1/tR+UKRWBvH4mf71xFA1tvtMxWAwHqcPR23g17ixjArhNU2X6BSmWaazo9j0eKjfT27dvRtWtXrYGkUaUbzy7UzPpICswJZj8/Gnp+h6EMKdOBA4UzZ85EvXr1xOMGsz74SLB5s6ZNempBj5ChE2aN0MgYarJKAy4HAyk3HvRcaKAZQmK6YEZXIhoKc5kLpuCyceZ2bJy1Q0yz1Fsy0ClpDmsKHvo9PCVIPTzX77iEhX8fQ57c2fDnjL7I5mxvtnMTEhmJ+efPYuW1q6LVlb2VlYhFS0Zan8eSRy54bJkXDg4RQrvaN9YW28MLoKOlJz5zf7/Pjl9A5TTKpBoo6Xk8jDbSjMnRY6Yx5Q9Yyh7gD1l3QDAp0EjSUBsqyuBLwtChQ2Eq8ERwkJMhDxp9Q9AfvDQX5MqDBtrDwyPDebi5JSzFNRfSymXfyqNY/u1aMT1kRj8079/YLDwkPY0alQpphY8WT+0plOmoXEfjTCNNNKhRHM6JpJ6m97mhXWFj2KknjsHrfey2ebFimNCwCfLphAYkHqwYvBf0AF7WV4BYTXMBQvNfhUtRVuhEkVGXyVA5mF7PJj2Ph9FGmsUR9EYPHz4sBpt0Y5ZFixYVusVyBW8oJUqUEB6iITD0IodGo3LkwRurubQ8eGNNq+CUHLhQOGnO4CViuvvYDuj2TXuzHhOGNBwd4lI0SxTJBStLS0xbtA8HTtwR84Z/0hC9OtRI1NtMz3NDAz18907sf1/eXcAlG35q3MRg/8Frj67Dx80PJ9+ehk/E28TWiDdR1lDlWAWVTc104Zyex8MqJal3bJbKuC5DElJ8Uhp3lIN8YlKgZ5jYoJcx1ZIZAYVHfMjFQKeFy7M7L/BLzzmilLrlgCYYNL2PWXgkV6QydcE+XLj2VBSpfP9FC7RsXM4kPJIS4deNJeuCtqRibg8cffoEn1ergWE1asDOynDs+ILdFVx9qclOsbOwg6UqBiExdMbi7BH7peSxdUw3A53e12qKY9KNG8d/THv58qUIgdDb0g1ZZCaYu9RW4SFvHmnhUrB0PnQa2QovH3ph9LLP0+zMmOqYnLwQJ0LUd9RKBIVEiCKVKd+0R+2qRUzGIzER/lG1amN07bg+h0efPIaLrR2qvS92+6xqNbQqUQKFXbNrncEHwY9w0uc02udrg5y2mmQCD/+cKJutNBq410P1HFXxn2dvLHiT/X0jK6mhlQodshkOdZoKsioLl/SQly5dqh31Z8rWgAEDMGTIEJgLxqazKFBgDsREx4jOKnLA8XP3MX6GZgBTtznssH4N0MfEJegP/F/hrp8XvtylSYmb17YRbK0sUcQlF0pkzyu6pUw5cQwHHj1ESTc37OzVF9Y64TW/CD+centOhDNeh2uKVjrn64BO+eNXBqrVUUDYFqjfTcSlUDf8G1AIr6Mc4GEdio6uz1DdIQgWHnHdluSAdEvB4+AhKwF/+eUX3L17F7Vq1RIJ8syhzaxgInpqOpgoPLIGj5RyefvKD//8uhWfz/oENu/7+ZnKQJvimKx43ytRAg00DfXBk3eNNtLG8rgRchGb3+wCUEa8/+fNUlhaqtFO1RaHH+UVwkdh0dFC77lRocJCYF8Vq8ZF/yvCa74ZeFv4woSNhQ1q5qiOCq5xoZgrVy6hSplXUAfPA2I8xbxqDr6o7uCrw0IFWJVCZr1WU2ykmTo3b948EZtmnLdkyZLixQokOcgopgbly5eHHKDwkCePlHAJ8g/G9y1/wdObnogIjRQNY83BI6kc6cfPdQ1YnKF+/tLP5DwojO/t44JzuCreez2oicZF82PZMS888X8s5tXImw+Tm3yEUu/rIdhTcMXjVQiP1RSrlXIuiYY566JGjuqwt4w/rlS+XAWog6dpDLSFOyKs6sI2cgdi1QDl3qWQR6jdADhl0ms1xflejLuMHz8ey5cvF4aauc4UCKI3nVmRWGpeRkPhIU8exnIJD43AhPbThYHO4eGKPhO6mIWHITCqeeD4bfQb/bdBfXJ60gXz5TA5j3PPfTDjhMZAE88DgrDqyh088Q8Q3bsnN22AfnVdsM9vo5aXnaUtmnt8jI752mJWpV/xY9lxaJizvtZAqyPOQB2rSct79vw5VE7joHL6Gir3Q9gb2gDzvcviRZQjItUqeEY6iPcHAiwy7bWaYk86R44cQvyIxSxMy6MgEgtc6F1nVsilqk3hIU8exnCJjorGLz1m49bpe3DM5oBp+35EniK5M5xHYgp2M5ce1A4W5s2dTYgl6cekB3Sva3IeLETRaTij/e9kY4UOdcNxIOQPqEM1c5+EPEVRJ03YtFuBTgnWpY68BnXwbCDyHFROIwGnkYKHyrYEYFtL67n7ZyuNWL9eeBXpCFWOf9DRzc7kLa0y8lq1Sk2hAwcMpTQtNjvlKzNDLt2xFR7y5JEcF/4mfh+0BOd3X4GNnTV+2fkdilYsJItjcubSI5FeFxgUBisrC3zarQ76dqqJI2fuYfLcPWKZIgXcRaVho9olTM7jkZ9vAuFQIiQqEvdCNI0DSjgVQ4Oc9ZDHznDBlDrqHtTBc4GIw+/nWIuBQpUBHtksI+FiEwzYvhcvsgmGyiIasLDPtNdqio00Bf5Z2r1hw4Z4Wg403HKRuMys+skKD3nySI7Lih/W4dCaE7CwtMDETWNQvn4Zs/AwBCdHO7wLDhMFK+NHtkLxwppS9AY6WhzLpveG/fsBTlPyeODrKwYCdXOWNVDDwT4S7fK2RgP3ushjn4hxjn4GdfB8IJwDjzT1FoB9Z6icvoDKMp9BHurQ9UDIwrgZ/r00NwnHEVA5j0JmvFZTbKRr1KghtDsoKKJrpCnOT9nSzAhdbWxzQuEhTx7JcanTvgb2/HkYw+Z8ilptqpmNh67+c/73OiAVy+TD7xO6omr5ArB6n2HCwcNXb+L03x888RZl4boCS2nlse3Obfx45BBi1Sq9Rlaa/4Xz+6F7gaTrKtTBi4DwnZo3dq00ehtWxZLkoXLoCdjFdVfXwiJOJyWzXaspjqZT8Gjq1Kmis0rBggVF6h11HeTURSM1ZdBygMJDnjyS40I1u1UPFqBZv0Zm5eEfGIoJs3bgk69WxcvUqFm5sNZASwJLkm4HwenPxq4R89PKIzw6Ct8dOoAxB/aJ1Dq3bCEoVuTFe8GjWPG/dMnnqJAnPMF31bF+UMe81r5XOY0AbJtA5bYNFq7zEhhoQzxUlrmgsi6X8GUZJ2+a2a7VFBezrF69WpSF62pMMB7z559/mtWTVopZFJgabJfmZ6BlGuVD7118iFwF3FG8ijzqA46dvY9Zyw4i4F0YLC1UGDesOdp8VCHVUqWpwfPAAHy+cwfu+b4VPnPDUo6Icr2oHZjkf8mXHlWsD2q4NxHfY6aGOmQFELoSsG0MC9c5yAp4l17FLJ988kmCeSwJz6yhDjmVHys85MVDv42ahI/7NcLxDadhbWeN+WemolBZTVcgcxwTDgjOXn5Y6D8TRQu644eRLVG6WOKqhTTEaTHGhngQ9lbW8AsLE6l1rSrb4In6DCygQn232tj7/IqIQ+d3yI1uBTqLEm61OhwI/R/UwcsA9fvwC+PQanrdtqnmYQ7IrixcjlA8aQXp4UmzSazU43LOySl489Qbc4f+gfCQCNTvXAs/bvjKbCqB7JYyY+kB+AWECu+5T+da+LRbbdhYZ1x3H2o8W+nI2l5/7YVTAYdwLvC4KCPpka8XiqqfIjbkDxR1DkS0qgD8LAYgu20EnKL+BGK9NV+0LAKV81eAbXOoVOaX683U3cI/REg93swNhYe8eFCEv1jlwtr3do62WPr1KmGgKzcph+/XjspwA617TB4+9REGunABNyyd1htDetfPMANNHk8D/NFx/f+w857Gi6e/dz38qNZADyraH+Fvr6KU9XSUyuYHW8sY2KueogB+glPErxoDbZEXKpfpULnvhsquZYoN9PUscK0qnvT71jeJtdbKSCg85McjLCQc7Z01HYdyFnCDj6cvSlQripmHf4Kji+lSTo2NE/v5ByJHdk1hRnR0DLbuvYYOLSrB1iZje2P+e+smJp44huDISKH3fOiTT7HLaw+2vtwuPh9U5FM0ylUfb182hKvFa1GiLYEl27GwgrXL94BDD6hUKUv/k9s1kloe6RaTllMHEVPBy8tLNC4wNxQe8uNBwX4JNNBueVzx654fTGqgjWlpFRQSjvkrjuLmXU+smjtQeMzM2OjeLn1T/vQRER2NaadOYPX1a+J99bz5MK9la6FcV9e9Jo77nETHfO2EgSayW/olyJKmwVYxWu2YdLu9zHKNpDePFBvpy5cva/saZnRj0vSCMa2/MgIKD3nxOLn1PKb3nR9vnq9XAG6cvIsGnU0r6ZlYSyt60mcvP8ZvSw4Ib5sZEldueBql+WxqMHtj5J7duOGtkQwdWr0Gvq5TTxuTzm2XG9MrThHaGwQHBlUqO9Zz661JBZVV0Q/iGskIHil2h3PlyoU//vgjgYGmxrQxuHnzJjZt2iSk/QyB2tS8EUjNHakNkt4w18CPPhQe8uKxetLGBCL9fL92SsKMj7SCIQ1WBUrgdD4PV/yx7hTGTt0qDDQLVKaNa20WA+0bGor2//xPGGhXOzvMadwUY+vWx5YX23DN/z/tcloDHfMKat/egPqd3po0SXgiB/oDuEYygkeKjTTV7hYtWoQ6deoIzQ52CO/RoweOHDliVJrKzp07hSdOQ2zIsLO8sm7duhg4cKBIacmI0mB//4S5sOaAwkMePPxe++OXnrPx7LZnAsU4vve89ypdtqvbLaXfl3+j+7Dl2HPkpvCee7Srhr9nf4LcOczz9Orm4IDu5cqjap48Qpi/jL0D1ntuxi6vvZj/YDF8I+KKZ9QR56B+2wmIvgmoXAEHnfRcqxJQuS6Eyq65SXj5Z4Fr1So1lTXt2rUTCngSIiIicPr06WS/S6W8n376SUx36dIFHTt2RKdOCdWuPvvsM7H+cePGoXTp0khvFCqUPmI4KYXCw7w8ONayZ/lh/PndWoQEaroOxZNwe+9JFyilafFk6m4pkuAR8dpH44G6uTpg8tj2qFQmv8mOibF9B9k1hfub19lZvKfnTDC8sc53D/Z5HRLv+xTqCTdbjcypOmwr1IHjWeIGWJUVBhkWOaAOXSY+V+XYCJWF6eL5hbLAtZpiI00vmLJ8HDjUHUCsVKlSst9l6bg0islRzatX43RmdcF1URL14cOHwlind5NbhmDk0AFE4WE+Hk9veWLu0GVCapQoWb0YGveoiz/GrtEuw+uQnnS/id1Mvv0VG85qK/N0kc3FQWugTXVMjOk7ePjxI3xzYB+K5ciBf7p0FwODfHH/N3puwT5vjYHuX7gPPsqt0/fUqjzAQhTbj6HK9ouISatj39/w0gE3s8C1muJwh5ubG27duoWGDRuK7tsFChTAX3/9JeYnh+DgYG2aCmM4jD/rS/xRSS9//vziZsBlhw0bZnBd9N6ZwqL7Si3kcJIJhUfG84gMj8TKH//BsKpjhYG2d7ITQknzz05FtzHt8d3aOOW0wuUK4Kct36C+ifsAEtTaMJQMS7EkUx+T3hUqYmO3Htr3nN7Rq4+YHxUTg+mnTmDwzu0IjIhATKxa/Cc0BnordnntE+8/KdQbH+duoqkcfA+VdUmo3P6FKttMjYGO8YY66o72c06ro26J+aZA1SxwrabYSNMYrl27VhhmxmHOnz8PHx8fHD16NNnv0gDT+yYkA60fcOeAotQevUGDBkIrxFAq97Rp04Q3Lr14syC8vb3x9u1bETuPjIzUDlAyHk7cuHFD3CzYSeHVq1diHw4dOiT4SCJR0rK3b98W+/vixQvx4jTn6S7D7/C7zHbhurhOrpvb4LZ0lyUXciI3cnzz5g0eP34sciyZDM/lpGX5nvP5OZdL6T6RT2r3ad++fSbbJ91lU7pPp06dMtk+JXaegt4FYf/qo4iOikHp+sXw5605KNwgj7g2ya1UvbgshN+OTIBzUU13EFOep3fB9DQNd0vJk8s53j7pXiOpvfYswsLhrrO5mNdvUD5Xbly8dBm9t2zCH5cvifmdixTFgoaNqUMsvnfW+7yIQRPVQiqhmUdTPL67FrHeTeH1fLd2n+4/ihDHj/yEdKh/r/jSob6d8O7NHyb5PZ05cyZdrr2U/p5o/1JjI9KlmGX//v1i0FA/+ZqGu2/fvkl+l94xFfTYE5EHibHts2fj54aOHTsWvXr1EncmGn8OHrL5rSFPmi8JPDg01EpZuILk8M43CI6uDloH4drRmwjyD0H9TjXjhdYMlYXb2tsIgSVWI5oCUVEx+HbaNly49jTefCn0MXVchxSJ8RuL0KgolF+8QEzfHD4SF16+wJj9e+EfHg4nGxv89nFztCpRMt53YtWxWP74bxRxLIRmuZsCIX9CHfw7PwFsm8Ii+9IE2xEec6xPQgIWOdNdmS7LloW7u7snkOULCgoSd6nkMHToUOzZoxkcYZYH3xM01PTMpQFF3pEIKuuxh6IhsH0Xd0z3lVpId2hzQ+GRvjzoj+z/+ygGlP4SO5cc0M6v3KS8yHvWH/ugwJJkoAlOD6/+rZhvCsTGqjF98X5hoO1srfBZz7j2VeyWYshAm+qYHHwUl0nSaf06TDx6WBjo8rlyiewNyUDzmNE4ExYqCwwpOgDNctVBwLMBUAfP1Bho+y5QuRpun5fe0qE3PtBrNc1l4SNHjhQXNGPHAQEBuHDhAtavXy8MeHJgeIRGmIOPTZs2FfP4GPD06VO0aNFC+3hw9+5dlChRwmhlqbSUhfOxw8kpPXsJKzzMzePF/VeYN+wPXDt6S7wvX780Zh+fnOSgtK5UqW7nIVN50otWHcM/2y8JcaTpP3RC5bL50ay3pnjm4LpRBrulmOKY7Hv4AMN3vxfT10lgaVqkCBa1bgdbq7h8gi0vtsMn3AdDig0URlp0Swn4Aoimo2YNlct4wL5Xug/uf4jXarqWhc+fPx9btmwR8SCK/7M4xdhGjLVq1RIvXTCDQzelj91f+Moo+Pr6yuJEKzxMzyMqMgobftuOdb9uRVRElAhX9PupO7p81SZZw+KmY4wZQzRlmtX6HZeEgSa++6IF6lQtirBw/cq89DkmhprD8r1XUHA8A731xQ78+1JjzGu710QlJ1eofbuIApUYdQ5YuS2CyiZjy9I/5GvVZEaaZDhoN336dNFG60OAXMrbFR5J80hKhN+QZ3vv0iPM6L8Az++8FO+rt6iEUYsGI0/R3GY/JoxFE0P7NkCrJuWNbmmVVh58cH7o55dgmJLvH/vHFaRse7ET217uENO9CnZDZdeKmgF823ocaYRvxHh42GiaUZsT1jK9Vs1qpO/cuSOERKx07rjS/DJl0q8BZ3pCDipahMIjaR6JifAzb/mTSd0TzLe0ssCL+15wzZVNpNU16Vkv1Y/lpj4m/brUQpXyBVCuZB6DAkuShocksGQKHmxtNeHIYaEBrQ8elUKuGnW9f1/u0qrZ9cjfHq1ya4pYxLFzmQaorGAbII8mwfYyvVbNaqRZAcgwx6pVq0R/Q46QM42F88aPZ6VR5gPT9owN1yg8zMejzefNULVZRYPZFgQ9vSc3nqNoRU1YonjlIvhx/Veo1KQcXHI4m5RLavDE8y1yu7vAwV4Tay6vU7lIgaX6NeI6eEugJ20KHqweHLZ7J26+F0eKDzXVNFCnhDW2v9yFLS/+FXN75GuK1rZLoQ48BLDHoEqlrRb09n4iy2vkQ+SR4oHDuXPn4t9//9XmJRNMhWMzWsaqzYW0DBwyh1H/ycAcUHgkz0NX33lH0BrYO2rylr2evMH84ctx9fBNLLn8G4pUKCSrY/LydQCGfr8Oud2dMfPHLsiezSHDeJz1fI6Re3eL1lbZ7ezw60dV8CTAEzNOa7KoCrvaYkCVPKhdsCB+vf8notXR6OZRGW3tVrBlN2CRCyq3zVBZemSKaySz8Ei3FDwO6O3atQtr1qzRvjZu3Jip49OJladnNBQeKecRHRWNDTO2Y3D5r3Fp/3VYWKjw8OpTs3BJDH4BIfh68mbRzZsVfDbWlhnK45G/vzDQ5XLmwo5efdEs90V0yzVZ+/mmJkvQJ9d3KGZ5Bl+WGIYeufOgre18jYG2ria6desa6NTySA9czQI8UuxJ6w4cyuEOJkHpcZg1cHjdSa3GMwcAY2Ni8eaZpliiUuNy+HLJYBQolQ9yQWhYJEZO3IB7j94gT+5sWPpr7wQhjPQGf+Kbbt9C+1KlYGdljTfvnuLAyyPY5nUZ9vaRcLN2RiPXGmiQsyLcYxcCEYc1X3ToA5Xz92nqnKLADJ50UgOHmRVS+aa5ofBImoe+CD+rAWmg7Zzs8M2K4aKlVXoZ6NQcE2Zw/DhzhzDQri72+H1ClzQbaGN4eAYGYuiuHQgM12hqMJZMmVEaaGLx7TM48O4MHBwiYGGhhl/0O/zrexiXX016b6BtRN9BC5efEjXQcr1GPkQeKfakWc69YsUK5M6dW1YDh4on/eFjSOUxeHojocZzoXL58eeNOZATWE34y/w9OHDijqgmXDC5B8qU0GRypCdOPnuGL/ftRkB4ODqWLoPZLVolWGbctYnwikioiZ3XNjum5bsKlescqKw1+jkKMqEnTY0OlnZTlGj58uVYunQplixZIkRLMiskQRRzQ+GRNA+m0xnyKV49eiO7Y+LjF4RL/z2DpaUFfhnbwWQGOjEePC7LLl3EgO1bhYGumDs3vnmv/5yAW+TrROYHQuW+1ygDLddr5EPkYZWagcNBgwYlqK45ceIEMitY3i4HKDyS5uHq7oK3QtJTne4i/MlxSQ5MtVvya29RlGLKdleGeIRERuK7Qwew+4FGU6db2XKY3OSjeNWDEnwi3kKlZiGNXlswqOFhHQGVyjpTXyPmQnrySLEnXa9ePaHXQeGjf/75R/QhZFk49aUzK9KiRW1KKDwS50FhJJ8XvgkMdHqJ8CfFJSmwq7cE9ihsXKdkuvJ48S4QXTb+Iwy0tYUFpjT5CNM/bm7QQHuGvsDEm78gSmug1VoDzTzpjtkep5qHufAuC/BIsZFmdscPP/wgqgvDw8NFOWT9+vWFhKkCBemBm6fuYO7nmvZLdTvWyBAR/tTg4rWn6Pb5cpy+lFBaN73gYG2DkMgo5HRwxP+6dEOfipUSrapkN++ctm4oYhOKT3PcRwHrEFgjFvmtQzAy521UdzF/UYgCE4Q7qGLHWDSlQnfv3i3m5cmTxyjRf7lCLgONCo+EPJjBManzTCHK36BrbYz5axg6ZusvPp93dqq2mCUjuCSFu49e44cZ2xEWHoUjp++hXvVi6caDTw+SIc5hb48/23cUHbxzGxD4iYiJgLWFtVCws1ZZ4at8lrAPvwwblRqNnF7DgrrVUAlvWuU0KUU85ACXLMAjxZ405UNXrlwZbx47aOi3wcpMkPSrzQ2FR3w8vPsQE9pPR+DbIJSoVhSDpvfBk/+eaz9/dO0pHlx5LISXzHlM2OLqmylbhIGuVrEgvh1umk7YhnD/6VNR3r3x1k3tvFLu7gYN9Jtwb/x861etUBJCliFbxN/CQMfYdsaLKEdEqlVQWxZPcQdvuVwjL7IAj1TpSS9evFgUs1Bflyl4DH1s2LAhQSusjISSgvdhgTf9Ce1/w8W9V+GWNzsWnp8mOnmnRGApI8BqQpZ7v3oTiJJFcmHBlB5wdLBNlw7eVKlj/jNV7Ng95eSAQchmZ/hJ4r+Am1j08A+ExoQim3U2TK8wCQ5BXwKRpxBu/yU80RC/3NUI9f9Y+kvYWrnA1TobXG1cU8xdQfrarFQZaSk2zb5hzJcuV64czI20GGkmohvbXCA9ofCIw+un3hhe81tEhkTi9+OTUap6sRRLlab3MWE14YgJG3D/cdqrCeeeO5NkB2927/5q/14ER0bCw8kJi9u0Q2WPhGl9/DnvfLUXm19sE8OBxZ2KYmSJYchhkx1qdSQQfgBbfd7hX68jCb7bMU9TdCnYO9NcI5mdR7obablB8aQ/PLx96YsnNz1Ro0VlyBGrNp/D8nWnRDUh0+0K5E39jYKe9PPAQHTftEHbwdvOygruDg5Yf/OG1oBXz5sPi1q3RU7HhDeDsJhwLH+0Ehf9L4v3jXM2RL/8tWFtXSLeYKKf3+8ICPpfgu+7OvdBjhxjUr0PCiCfziwfGtiuKyM7wSg8EkdkeCRs3reNevLqMWq0MN/xoBC/r78mBHHr9i2UK6t5YpSE+Pt2qol3QWH4uH7pNBlogiENJ5u4MEnZnLmEkR62awcOPtZki3xSqTJa2DsaNNDsQzjtzkw8CXkGS5UlPincG02y2UHt1xlqh16A0ODQDEFlz9YP2Z1bJiRhkdNovsq1mnE8FCMNoEqVKpADsjqPFw+8MLbpJAz9vT8ada9r9uOhL8QPXBF/P+1WG4N61RfVhCMHNEm37VuoVCiXKxeOP3uKqU0/Rpey5YQkpuFlLdA898fY6LlFhDeK24VA7ccsmEgghoNaFPrXGGnRBDaNjWDNfW6yEo8UZ3ekdTCIetQsfuH/EAMDJbqYNWsW/P3Tf+T+0aOMy2tNClmZR5B/MCa0myYqCrfM3SWuFXMfDwrxL57aU/ue093aVMWzF36IjjZ9NpNuB+/OG9aJhrEjatbGnj79hIEmdI8JvWffiLiWV/Vz1sFvlX5BcbtYqP0GAeoQwKY2VK5zoVKZ1h8z97nJSjxMZqR37ozrPpwYFixYIDJBunXrhsaNG2PSpElJ1sIvWrRIdGlOb+TKZZr28mlFVuVBTehfeswW2hw5C7hh0taxIlPI3MeDIY0SReI4PHvph027r+Do2fs4cSHOoJoCNMgcGJTwwNdXdPQ+8OghimbPoZ0vHZPQ6FDMu78YP9+ahsCoQO3ndmofqP0HAOoAwLoiVK6LoVKlPNskOZj73GQlHkYZ6cOHD2s7eBt6Va5c2SgjvW3bNpQsWVKbb82O44YQGxuLy5cvi1ZdGYGwsDDIAVmVx+LRf+PKoRuwc7TF5O3fIodHdtkcj5M6xvi3xQfE/x7tqqGJicu9fz9zOt57qYP3Ar2MDx6Tl2GvMOnWr7gScA3B0UEiDi2+E+MNtf+nQKw3YFUCqux/QmWRPh2s5XBusgoPo56BODI8atQoNG9uONmd+h3r12saZyb3SCAJMzk6OsLLy8vgclu3bkXHjh2xbt26RNfFll18maJ2nvzlgKzIY/uifdi5ZL+4xr5bM0r0JTQHD0M4fu4+Js/dk2B++VL5Ut3Q1hCYXvdIp1N3Yh28ietBN7D15Q6Ex0aItLovS3yBok6FNR9GXQFiXgKWBaDKvgIqi/TLeTb3uclKPIzypBma6NOnj8iJ1n/RUDJHcMCAAcmuhx6ybutzxh31KxWfPHkCNzc3ODsn3TiU3WGYviK9pJ6LbAhJzesHDx4InesrV67EE+W+ceMGgoOD8ezZM7x69UrEvGngOSDDEVrdZRly4WesJuKL05IkobQMv8Pv3rt3T6yL6+S6uQ1uS3dZciEnciNHyrs+fvxY3IWZc879lpble87n51wupftEPqndJ67DVPuku6z+Pp0/dBmLR2uqV1t+0Qj1OtaMt0/swGyqfUrNeVqy+liC646medXmsyY5T2/evsVX/27F4J2aztyGtpXX0UHsU0BgAJZcXY51AZuEgS7tXBKdo9qhoF1+7T55+VXE26gJCLNdjJu3vU12ngztk1RhZ+prL6XnycXFxWT7lJbfE410avbJGKQ6T9rT01MbL+YAIDWmf/zxxyS/U6lSJezbt09offC7BQsWFAdLFxMnTkSLFi3E9JgxY/Dtt9+Km4R+J15DnjQNdWrypHlSKlQwv8h5VuPBG/SK79fB3ycQY1d8kcA7NffxaNpjDiKjEg4QskfhkQ1fpXn9Px45hHU3/hPTZT0ccPt1aIKAR//aufFTrT7Y8XI3Nr3YJj5p4fExehboCisLK6jVEWKAUGURF7fOCJj73HwIPNItT5o2vVOnTsLjpWdM4+nj4yMyNpIDje/Tp0+FkeZd5+OPP07QbXfIkCFa75qGnMvaGSh9pcATX6aAHE5yVuTBwcHBM/qJ68hQ+MAcxyOMedrWViK9rkDeHHj0vn+iBNIsmM80BnF4jVo46+mJ8Q0boWq+HFh/6ypmnNA0NC2c3QUDqpVDuxJlxfuPczfBBb9LaJWnOeq51xHz1OpoqANGA9GPgRx/Q2WZ/p1fsuq1ak4eKc7uOHbsGEaMGCEeH/766y8h9n/p0iVhqJPD2LFjsWPHDqGYRyW9X375RcxfvXq1MM6SeHahQoWEp87S81u3bqV73Ckr9EmTC4+oyCjR3TsyIu6cWlhYmP14sN3VniM30fOLv7D32C0xb2APjTHUNdB87hzQvW6qtsGS7u1343qB5nV2xoF+/dG0SFGhmdG9TFwxxObuvVCnkIfQ3SAcrBwwufwEWD7U3MzU6lioA7/X9CRkHFrkQmccssK1mml7HLKXYdmyZYXXy1gOszsYO9y1axfatm1r1Dr8/PyQI0ecN0IKDF3oesyM2/DHSy+LsdrkvGalLFz+4HmeM2QZ9v51GDVaVcHUXd+bdAAutbh2yxPzVx4TGhxEhVJ5sfjXXoLbgRO3tYOHRQu647Oe9dCodokUb+Om9xuM2rsbTwMCsLxdB3xUtFiCsvADL09h64udooO3g5U9wmND0TFPJ3Qp2CbBcVQHTQFC1/J5BCrXRVDZNU3TMVDwAfU4rFWrFgYOHIiZM2eK1DuGPpo2bYqgoCCj16FroAn+GPRDGnnz5oWHh4f4b6qwRmKQBg7MjQ+dx9a5u4WBtrBQocMXLZM10Ol9PF6+DsD4Gdu1IkmODjYY/klDzJvcXcutQc3i2uWXTe+dYgNNg7ry6hV03bheGOg8Tk4GlesW3diB/f6btR28aaCJY6+uJDgm6uD57w20Cqpsv5nFQH/o16qceFilJo7IFDkJa9aswbVr1+LFlzMbypcvDzngQ+Zxfvdl/DF2tZj+fFZ/1Gpd1Sw8JPy7/zrm/XUEUdEx4qbRvllFfNajLrK7pk7FzhD8wsLw7cH9OPxE05aqWdFi+K1Zc7ja2SdYNszuLhChCanowsE+fqivQrHLQMgiMa1ymQiVfXuYAx/ytSo3HqmqOPz7779FlgZBN/3ly5fIzGA6jBzwofJ4cvM5fu09T8R9Ww/6CJ2+bG0WHrooXjinMNA1KxfG379/gm8+b5bAQFNgiY1kJXD63qM3Yn5yuPDyBdquWyMMtI2lJSY1boqlbdsbNNCEd6Thjuc+EXHbV6vDEBOiUa9TOX0FlUMfmAsf6rUqRx4p9qSZncGBPMakCYYi2rdvj3///VeEPjIj9NP7zIUPkYe/dyAmtp+O0KAwVGpcDiMWfmZ0HNqUPM5deYJXbwLQuZVGCKd8qbxYMaufKPtOjI++wNLw8ZqCrQHd64jYdFJ4GxqK18HBKJo9O+a3aiNU7RIDy7pjRAfv+GBTqzz2HnHvVfYIsV4KW4dzgIOmhZi58CFeq3LlkWIjzWyL7t27i4C3bow5IzQ20gtyaf31IfJgj8LggFDkLe6BiZvGwNrGOkN5PPF8i4V/H8P5q09FfnOdakWRJ5fm2i1ZNHeyAkv1a2hi0n5+vsiRw01MJybsH6tWC+U6onWJkpjVvCVaFCsORxuN9GpiYAZHI/fqOP72knYe10LR/o55GkEdG6CtHoyOzQ6V46cwNz7Ea1WuPFJspGvWrClS6SiOxEE9VuwwnY7Vh5kVyanxZRQyI4/kuqWUrV0SC879KgbQXNyc08RDV99ZF5K+sy78A0OxYsMZ7DhwHTGxalhZWaBTy8pwcjR+EJrrlNb7WBWCokkYdZZ2zzh9Cms7d9XqPXcuo8lxNgQq2AVFByObtWZUf2CuSJRW38Ey3zLifT7rYHRyfYZqVvuh9hkDiPhzx0x5jaQnQrIAjxQb6Zw5c6J3795o0KCBqBakkf7666/xxRdfILOCBTNyQGbksXvZQYN9B3uM6ygaxxL5S+Y1CY+E+s5IEH6IjIrG5t1XsXrzOQSHaipSG9YqIbI28qehxVZixyQiOhq/nT6Jv69pilCWXLqAiY2S1piOjI3EkofL8SrsNSaW+w6OVo5QOfREtbw1Ad8/xTITS4+Greot8G4ioA6GOnwPYNchU14j6Yk8WYBHqkRmWaZNsSTmMhuTwyx33L9/X5SsmxuZkUebz5uharOK+KrBBPF+zskpuHPuPtZN3YoqH5VHtWaVTMaD4YcalQppY8PUd7a1sY4XfqAH/df604iIjBaNYUcMaIyq5Qumavu6zWHJRVJwlJrDPvb3x5d7d+OWj2Zwb2CVqhhbt36S6wyKCsLs+wvxMPgRrFRWeBzyFBWylUNgjA3eRMXth1dEIApEToalOhiwrg6V6zwRO8+M14jCI4OKWSgMwuA4RUEoUKILlnRv374d48aNg7mgFLOYD2Eh4Wjv3E9Mzzk1Bd83/wXhoRHoOKIVvpg/0LTbCo9Es97zxfTBdaNgb2cjBgTz5o5TfNu487LIeW7ZuJwo704tkmoOWyibKyYcPYzQqChkt7PDzOYtReVgUngT7o1Z9+bhdfgbOFg64KuSI1DaRWP4t77Yjud+K9HR9RnyWIeKmLSVSo0AdT5kz70DKouUhYoUyB8m1e5gKXj//v1Fmgm1pUePHo3ChQvHPb5FRqJixYrIrMjMHYflwOPMdo0yGPFN40mIiY5BteaVMHR2f5Pz0NV3/mzsGrhldxIVgwt/6YlKZfKL+d3bVYMp0LtCRdQvWChBc9hzLzwx5oAmBbV2/vyY3aIVPJySNqKPgh/j93sLEBQdBHcbN3xT+kvks48LAzV3jYWD1W1Rdq6bbGLrODCegc6s14jCIwM96Tt37oj0O4r264J50y1bGmhumUFQPGnz4OTW85jcdVaC+eNWjUCzfo1Mru88fsYOg58N6lkPn3aPr7VhCtBTLr94gZi+OXwkHKytERIZic4b/kG7UqUwrHpNWCaiPSLhVuAdzL6/QMSiCzkUxDelRgmtDl3Evm0HRN9/r34nQQVYlYKFu+F9VpC5YfKycCkPkKl2hvp5UcNj6dKlQtsjs0HSnjU3MiOPNZM3Jsgz5vvNs3eanMeKDWcTVOQR+fO4pouBTqzvIFPqdvTqI/oPJmegCXrMLlbOqJitPMaXHRfPQKtjA6GOOAlEP9Ez0OJTjcJdJr9G0hPXswCPFAfsXr9+LQSWKKhEuVIJXbp0EV1Xdu/eLcStMxOkASFzIzPyYF9C/Ycxvve898rkPJ6/9BPhAH14vzVeNyYtfQfvv+87yPm274u5EoPuMXG1yYYfy34rYtD2lhrdDnXUbcQG/gC1dwOo/YcDlhzc1L8D0ZMumumvkfREySzAI8VG+qOPPkKHDh2wceNGDB48WHjOlBSlge7bty+mTJkiG9ETY5FYG6+MRmbiIRmh/CXzGPSkC5TKa3IertkSllSbUt9ZH9NPnUi4PQN9B/URFRuFpY/+xOm3cemCbrY5YKmKhTpsJ2J9e0Lt2xEI2wwgHLAqDNh3TRjqgBoqpxGZ9hrJCHhlAR4pNtKnT5/G3r17hQb0oUOH8PDhQxFbcXXVPMJRXpTZHpkJ7LcoB2QGHjTOVLIbVecHRIRFoN/E7vG8Rhpovu83sZvJeYz+rKlJ9Z0TA/n/eeUSngcGGtV3UBch0aGYeXcuzviex4ona/AuSuPlqyPOQ+3TGOrAMZpehByzt2sDVY51ULntgIXTQMDl97gVsZGs60Ko7JpnumskI+GYBXhYpSZpe9asWejatSueP38uJEZFD7aAAPE5DTYHGTMTqOwnB8idx/O7LzF36DLcOKERrt+97BA6j26D79aOwvS+mrS4wuUK4JOfu6N+p1om4XH34Wvky+MKZ0c7NKpdEhNHt9bqOxcpkHp958QQGB6OsQf349DjhOMukn9bNLthz/1thK9IsWM3bzsLO4wq/glcrN9nZjBsERsIWOQWhSuw7w6VZc7467b7COr3/ZRVOTZCZeGQ6a6RjIZlFuCRYiPNeHSVKlXw008/if/VqlXD8ePHRRUiu6tQ0H/JkiXITOBNxd3d3dw0ZMsjMjwS/0zbhvXTtyE6KgZ2DrboP7kHOozQZPPU7RDXUWTe2amwd0yol5wanLpwD4vWXkKxQjkxe2JXONjbJNB3Zp60KfE0wB/Hnj4RynWdSxXB+tsP9QIQwMgamtJtXTwLeY7f782Hf1QAslvZ4Ovcz1BQvZB9hzTfpUHOsQ6wLguVKqF+iTrGG+poz7j3UXcACzvAIidUlrlkf40oPPzTjUeqKg7ZOZwvdlPRrTZs3bo1HBwcYJOMoIzcwHZdcoAceVw/dkt4zxwgJGq2roKRCwfBo3Diqm6mAPOh5/19HlHRscI4M7RB7Q4WruhKh0oVh/raHalFJY88+PWjZijt7o6y9htQ0+UQvj6n0Uovkc0Xo8tfRPM8/NlU137nRuAtzL+/COGxkchnHYYxuc7DzSoCiHKEOtZP2yRWZZN4RZo6dD0QQqP+Hv69NBFqxxFQOY+S9TViThTKAjxSVY7FgUEKLdEgU8tj0SKNCDnj0pnNQBM3b96EHCBHHkylo4HO4eGKH9d/hV92fh/PQFNg6dG1p9r3nH5w5bGYn1ocOH4bP87YLgw0QxnTv+8oPGZqd0gl4QSnWdDC+anFu4gIjN63B3d0enR2LVsO5XNpwhIfl5uknb+5awe0qDRHE654D3XEOdzzniUMdGnbAIz3uAI323xQOU+AKudJo7t4c50qt20JXzrbkus1Yk7czAI8UtzjkLHnGTNmYNiwYUIFj4nYq1atEt1yjenOwjZb3KFy5colmsDNvobs9sKCGWdn48phlWIW04CXQ1REFGzehxHePPPBplk78OmUnnAy0LVk9aSNBgWWOHD4yaTuKd7+v/uv4fc/DokBwZaNy+K7L1rC6n1pd0pU8IztOzhizy4xQFjSzQ17+nyilRolHvi/wp23zzB6jyZLY27rOrCzsUcRl1wokV2TvaIO24bYgG9xLDgP6ucoBxunvoBNHVn0blQgbxhrs1JspFlZWK9evQTGc+3atSIFLykwr5rx6i+//FLIm7Zp00YUweiC2SLbtm3DoEGDxM2A3cONUdhLi5HOCqWlxuDVo9eYN3w51NYxmLErzoNMi1RpSrB171XMXn5YTHdpVQW1yjugbh3TF6nwkl/733VMPXkckTExyO/iggWt2qKSR5zAPvH5gZVQvbuMkeUvoahzILxCHeET5oAHkRXgmrctmnt8BGuVGgj5A7DvApVl2tMO5X6NKDxMx8Ok2h26oG40PeE6Oj8eetfh4eHJfnfatGkYMWIE8uXLh6FDh4o86507dybo/BIWFiYqHOvWrYtly5aluwyqHE6yOXlERUZh8++7sHbKJkSG04u2hs8LX+TMrxG5TwpuqTDGiaFahYJwdbFHu2YVMaR3/XTxRoMiIjD+yCHsun9P23dwRrMWBpvD/lTVHh7RB7R6GoWd38HDMRjHfN5iv+cWPAl5hpElhgJOI5FRyOrXalbkkWJPmqB+NNXw6OXSQLMkcvPmzcm2kGFmyIEDB8T32IIrV65cSabrsbkAPW12gklPT/rGjRsiXGNumIPHrTP3xMDg05uazIIqH1VAy9GN0LSNaXU3jIV/QIi216Cpj8fr4CD03rJJdO22srDAt/UaCHnRxG4GsT6toY55qK0DDIixxmzv8ngW6QwbCxt8UXwIqmavjIxEVr5WPzQe6eZJE7NnzxZl4aw2LFq0qOjSYoxhZHoeBxsJa2tr4X2z7Yx+jiHj1gsWLBA3gm7dDBdFMLOEL90dTi2KFCkCOcBUPIwJQYS8C8Wf367FbhH/VSObuzM+/70/Pu7bMMO6XUTHxIr4c9M6JVGjskZVUbcZrKnPS04HR+R1dkFEdAwWtm6DKnkSD0+wbBsxD3E51A3/BhSCV5SDyLaIgQWcLaIwpswPKOaUtDRpeuBDu1bTiiJZgEeqxXbbtm2Lpk2bCtF/ZnuwoCU56KbrcXCQlYmGksAZ7/7hhx9E95fEjDRDJ7wLSa8CBQqI+d7e3qJjzIMHD4SEqlSizpiRdMej8afsKpsW0JNn30ZyuXjxYrxlb9++LYw/940vTnOe7jL8Dr9LvRKui+vkurkNbkt3WXIhJ3IjR+pyP378WIR3+DTC8nppWb7nfH7O5VKyT5vn7cDw6t8meLGLinafnr/Aia3nhIGu2bEy/ro9F84lbIVXefnyZZPtk+6yuvv04sUrfPfrFuw8+B9+nLkDp06fT7BP0nal80Q+KT1Px06fFt1T+B11bCxGFi+Jta3bIrcaSe5TVOQ7XAxxwwKfcvCMckQ0LISBJjrmCIfPTe80n6fU7JPuNWLKay+x85TYPkl8TbFPafk9vXnzxmT7lJbzxLG01OxTuoU7dMEdHj9+vPBq16xZk+SyLVq0EEp5vOswTMIBSBpIXRw8eBDFihUTHjrX7eHhIQwvU/2S86RpqFMT7uBBY6aKuWEqHvSk2QBWt1uKLXONLVQoVqmw9vH+/O7LsHWwReUm5dOFR1LC/ZQcvXDtKaytLDH5m3bxilRMxePe27cie6NW/vz4pWnymUf6+OHaF3gREU4FDe08FdTIb+eKXyvplHBnID60azUr83hnaqnSpAYSmalBjzo5MPuD2h/E+fPnRUEMQenTo0ePiuktW7ZovXKKlrC5ALuRG/LKuWO6r9TC3j6hcI85YCoeDGkUex8+IAqXLyCKUr6qPwFH/zmlnV+rTbUEBtqUPAwhOCQCX0/eIgy0na0VZozvbNBAp5XHpls30WnDOjzy98ORJ4/hHxaW5PLq2GDEBoyBOuqeEEiKjI3C68iYeAZaLAcVXkeYr/nph3atphX2WYCHUUaa2RxJiSbRMytfPuGPXR/9+vUTWh80xLzzSO22OM1mAsTMmTPFY8nWrVuxZ88eUXKe3vX59NTlAFPy0O2W0iPPYCz7ZrVoaXVq2/kM5aEL9h8cNXEDbtx9Kbp2z53UXfQsNCUPivSPPbAP3x46gPDoaDQsVAg7e/VF9iR+ROro51D79UBM2E4cf/4Dvrn+Aw6+PgwPOw8D4qEq5LGPn6qXkfgQr9W0wDsL8DAq3EGjytAEQw+Jgalyn3/+OcyFtGR38AbEbjPmhql4JNYtpe3Q5hi58DOhVJgRPPSx7H8nsWbLeZFmN+enbihRJFeKeOg2htWF1Bj2ga+vCG888PMVRSlf1a6LYTVqxitQ0Yc64gxi/EfjYogVtgYWw+sozbhJAYf86OjREAser0ug3TGqWB/UcE+6I3h64UO7VrMyj3emzO7gj5pxZGpGGwIHAanbYU4jnRZcvXo1QVFNZubxx1iNqI/+087ts/eSNdCm5KEPKtYFBYeje9tqRmlA6/NYd+O/RBvDDq9RC5/+uxVewUEii2Neq9aonV8zmGwI9E3UIatx3WcZNvsXxfMozbXtZOWE9nlb46PcjWEVshRD3e5gqa9GUCmfdTA6uT5DNVsOYJnHSH9o16rCw0SeNAX+qckhZVDogznPzH+eOHEizAWlLDwOrex6IToyYXjK2s4ae0LjPMOMwGvvQOR0c05T125dT5ol3PqNYSVP+vDjx1h1/Sp+b94SOZPUxI6E+t0kbPG6iB2BmnALpUVb52mBlh4fw97KXqtMFxH1CoOva4SPllcaAVtL6wTKdAoUpAYm9aQZby5VqlSSsWG5iG9ntdJSguL79y4+QsWGZcX7AqXz4smN5/EafaSkW0pKeCSlp8HPxkzZgoa1S2Dc0GYpriDU50FDfNYzTs5z3MH96FiqDEbV1lS/flS0KJoWKZLkdmLVsVBxKCbmJWo7vMX+oCJomutjtMvbGs7W8Z8UA2Ns8CYy7rp+FukIW0sbuFrbwNVMMsaZ/VpVeKQcaU7Bkwuyqid9btdlLPpyBfxfB4hc59yFciaISUvdUn7a8o1JxPh18df601i5Ma5NlIRWTcrh+LkHCA2LRJkSHpg3qbuQHE0L2FuQPQb18UuTj9C7YuIyoASF+Ld4boeDlT0GFf0U6tgAIOo2wi2raD1nfWx9sR3bXibcXqd87dA5f4c07IkCBUjfisMPDUw+Z8l6ZuLx+qk3Fo9eibM7Lon3OQu4Cb0NGukGnWulqVtKSnh0aF5JZGhIEqKLp/bE/cfeWLz6OCKjYlClfAH89n2nVBlofR7zz5/VDt7pgiGOxIy0T8RbbH2xA6ffnhHfs1RZomv+TpqO3bZ1kVTiVNNcjbRl3yyCYO4+4WqdDeZCZrxWFR5pg2Kk2Uw1f35kFh6RERRD2ol1U7cgIiwSllaW6Pp1W/SZ0FXbEYXFLDTWEkYtGSyKWTjfGDGklBwPSoQ6OsQZ4FdvArFw1TFER8eibrWimPJNO9jaJuxEYgx0eYRFRYnsDUOPfc8M9CIMiAzEjle7ccT7OGLUMWJeVfu36Fqgv+jebQxoyIUxZ0l9oexwcTT/E1pmulYzAvmzAA/FSL9/7JBDiCQ5HjHRMRhZ63s8/u+ZeF+xUVmMWjQIhcrGH9Bl+beuxrNUeWisxnNKjwe7qEj4Zf5e8f+j+qUxYVQrWFmlPngr8QiPjkLLtasRYzAyp4a7U/xt3Ai4hbkPFiEyNlK8L2fnjy6uT1EsR0+onNqniYu5ofDIejwUI52JQK+5Trvq8H8TgM9n9UfTROQ823zeDHXax7V30hVYMjWOn7uvbQyri8a1S6TJQOvCzsoajQsXxs779xCgI4mrCX2o8HXt+vGWL+pUGFYqCxSwjUTXbHdR1j4MqmxTobJPnYFWoMCcUAYOZXw3pue8feE+lKtXCqVqFNdmckRFRBvskpJePJJC/69W4fFzH6G5LIH3DTaP/Xt2/1Rt3zMwEDPPnEL/MuVQrXBhrQ60taUFFl7bhxWXbyIiwhouDrEYWK08Suaxwd139zCqxHDNIGnEabz2GYdclj4iVU6VfTFU1hWRFsj1GlF4vMu0PDJMu+NDgDEKfhnNgzrPVK5b8vXfolsKJV0JW3vbdDXQ+jySw7MXvvEMNMH3z1/6pXi7NMS/nTqJZmv+FqL8006d0H7mbGuLG+/+w/WY7aha6RHq1rqL8hXu40LkVqx9th6X/K+KhrAaApHIbfUWKpvKULltTbOBlus1Yk4oPDKOhxLueN+MQC48At++EzrP+1ZqBKecszui7ZCU5xinlYcxOHTqrtCE1gepGlNRKCEmNhYbb93E7LNn4BsWKubVLVAQ4xvEbzyw6fkW7fp1YQELfFqkL8q6lNZ8btcEcF0K2NaDSmXzwV0jcoDCI+N4KJ60ju5reoFZFeygrf/S7ajN0voF3/2BAaW/1BrolgOaYMXdeWg9+GOjyrkz8nicuvAQU+YljEXTgNKTHtC9rnHbeuGJtuvWipZWNNBFXLNjebsOWNOpCwIfPYq37OvwuI7eulCrY9HI+n+wjH0dx8OuickMdEZcI8ZC4ZH1eCgx6QyAMR21T2w+iyndZ4vpohULYdTiwShXtxTkiIvXnmLcr9sQFR2DFo3KomblQpgyT5PVUbSgu9DoaFS7hFHrWnn1CqacOIZstrYYVasO+lSsBJtEKlvHXv0eryMTGuoC1uH4Je8FwKYWLHIkrWmuQIFcoMSkUwCp20J6gdkWFN6XwOnFl35D6yFxQvT1O9dCiVqFMWzOp+IzcxropI7H9dsv8N30f4WBpiFmw9g8ueLyjr/5/GN45HQRJeGGQF3nOz5xhpZGeXTtOjj66UAMqFI1noEmj5DoUG2ec/dCXd9/otYK8BMdXR8BlsWgcok7xpntGjEWCo+sx0PxpDNI7vDwupNxFYDlCwix/Tvn7mPmkUnaIhQKVbH3o7mR2PG49+gNRk7cIEq9a1ctgmnfdsSS9SewcdvlBMt271QNo/rFKcVFxsRg7X/XseD8WaHtvK9v/0Q9ZgmXfa9i1bP/obnHR2ibtxXU4ftx8dUk0XPwdZQDPKxD0dH1Gaq75IEqx2qoLAyrNGZ1SUyFRxaQKv3Qwc4wFJBKL1BLQzLQBDtzS925dyzajx7jOmhLj9OTR1qPR043J+E1uzjbYerY9rC2tkRIHhV8qiYc1OR8gj7A4SeP8evJ46JLN5HH2Vko2uV3MVz5R+953fMNOOGj6eJz5u05tMrTHKrghajm4IfqDr5633BPVwOdEdeIwkPhkRgUI011tVzpKzu5ZvJGrciRLnJ4uKLz6NYZxsNYJMYjh6sjFkzuLopUpFLvz+pUR7OyJQzKhzKs8cuJYzj7QnNDcrN3wJi6ddGtbHlYJjIQ+l/ATfz5eBX8o/xFFxRKh3bJ30ZobsREP9GGOHShjn6C9Ibcz01GQ+GRcTwUI01diLAwZM9u+mo8CS/ueSUw0ERQQAisbawzjIex0OXh5R2IG3dfoXlDjfC9i3N8SSLKhzrZxHWBL5szFxysrXH3rQ/arlsjTCrDGp9VqYah1WuIfGdDCBXe80Yc99H0YMxtmwtds9VEzezXAN+5ULvvwzu1G5zhBQsdxz1WDQTBDel91OR4bhQeyBI8FCP9PhacnnBwsUegT/xtGNJ3Tm8exkLi4eMbhC9/2ihEk3iTYSaHIRx8FKfd0XnDOoyuXRctihVH/YKFkM3ODuPq1U80tCHBPzIAp9+eE95zM/cy6Op6B7ZR4wBN2jQQvg/WzqNhEfytSPETqX5UhlapYe00GukNuZ0bc0PhkXE8MtxIb968WfzgWUHXvXt3g/m/bEDLCp6IiAjRkotdYdITxnQ6TwsGTeuD3wct0b6XQh9MwctIHsaCPNg0dvSkTcJA582dDdUqFExU4/mr/Zr0O4JKddR8XtymHf5o1wG2SQymMGuDYQwir70b+uctjVzqEyhtvRSI0hhhlW0TqBw+Fel1TioVYi2soHo3RnxHZVUCKqdRcLJrjvSGnM6NHKDwyDgeGZqCt2HDBmF4u3XrBnd3d8ydOzfBMvv27RMjnkOGDBEjpsOHD093Xk+emD6mGeQfl4LWcmBTjFs9Uvue+s6GBPjTg0dqcPP2fXz18yY8e+mHXG7OmPdzdyFJagjUeNYFwxuMRiw4fy5JA30r8A7GXf8Rj4Ifa2bE+qOh1R8obX0TUDkADn3x0G8+LLIvhcq2tubGFuMNWOo8fTj/DFjm08xPZ8jl3Cg8sh6PDDXSq1evRq1aGsNUs2ZNrFy50qCR9vfXVOJ17txZGPb0zhKsUKGCSdd389Qd9C8xEgdWHdPOq9+ppnZ63tmpBgX4Tc0jNWB63Yotd/DwqQ9yuDpg7s/d4uVB64Oesz54th77G9buCI8Jx99P/ofpd3+Hd4SPEOQnVJYegEN/qJy/hSrncVi4TESpsi3irzd0PeDfK26Gfy+ofTtp5qcz5HBuCIVH1uORoUb65s2bcHZ2FtP8z7QVfXz11VfaXmEMiRQsWNCgbgU9cuYZ6r7kUNJ5fNNZjGs2BUF+wdi34ogo92b596NrT7XLcFq/LNzUPFKDqKgYfDttG24/8IKLkx3m/NQNBfMmrsGx6MJ5gxrPPFtFsyfM+7wTeAc//PctDntryt6bOL3CF0WaaT+3cPkWKsfPoLLIZvB4qBx6QuW2LeHLoSfSG+Y+NxIUHlmPR4YaaRpW2/ej+zS8NMKSupuEQoUKiVAI8fvvv+PHH380uK5p06aJsIj0kjqZe3t74+3bt3jw4AEiIyNx5cqVeAfxxo0bCA4OxrNnz/Dq1SvhtXNUlqEVqWpIWpYtcWj8GR/ni9Ocp7sMv8Pv3rt3D2t+3YipPecgKiIKNdtUQZ+ZHUXMfdmElVrhfYLTVLjbMHubyI3myPD169fFzUlaL99zPj9/8+ZNiveJfFK6T5cuXUCF0vlga2OJGeM7ITrcT6yL6+S6uQ1ui082Yzdvwu9nNXnMulAhVnjSw8v7i30gTp8/hFUPJuLXu7/DJzIEbpbhGJvrJnq5F4K3p0+i+8QGyLr7dP+hP2JUpXDpWihU1uVw/nKQ+H/n3tsUnSdD+6S7LLmQE483jzuPP1OspPOku2xGnyfdaySt+6R77aV0nySY6tpL7T5VrVrVZPuUlvPEziyp2SfZVRyWLl0aJ06cEBc8DTaD7YkRXbt2rdjhxGLS/D5fErgsDXVqKg6lk51a8EazbMxqbJuvERxqP7wFhs8boO2uTo/ZT89rlkT4ddtZpZWHqXD42Bl81DhxgaR3ERFo/89aPA8MxMiaZeBk8w7TTr0UnxVxtcWnVfKgbYmKyG5fHOrI6zjp+Q2Wvy0kPm/s9BY989WGg3N/qCzzJMlDLsdDTlwUHh8OD2MrDjPUSDNTg0a3UqVK4q4zePBg7N0blxkg4cyZM8Ij7tixIw4ePIhmzeIeidOjLJx309RmkDCc8UuP2Ti55bx4P/i3vuj2TftUSYumhUdqERurxsZdl9GxRSXYvS9QMYbHy3fvcOLZU0TYPYCX3wa0z/YcRZ0D4RVpj51+hZDNpS8+LdEFanU4Yt80wp++RVDHrS4q5GI4w1G2x0PuXBQeHw4PWQosjR49Ghs3bhQu//Lly/HDDz+I+f/++y++++47MX316lWMGTMG+/fvF0Z96dKl6c6Ljx6pBcMZ7DFobWOFH9aNRvexHVKt/ZwWHqkB78+zlh3Ewr+PiVi0dL82xIOf3faJy6LI5+KCXhUqwjnkKb4tdA2lsvnB1jIGheyC0dLNE//5H0dYTDhUKjtYuG/AkLLrUNFjlNEGOjEe5oJcuCg8sh6PDM2TLlOmjDDANMT0qHPnzi3mN27cGBUrarpn0MBJBpuQ4tPpibRWClFutHGPugkawmY0j5SARnfBymPYcfA/WFio0P7jitqbiz4PLjv15HGsunYV81q1QesSJbWftct7BBeD3LA9sBC8ohxgbxGNoFh65KH49+VO9CrYDSorTQuslEIOlWRy46LwyHo8MryYJUeOHGjatGm8ea6uruJFVK5cWbwyEvqDl8nh3qVH+N8vm4XnbOdgK4xbWg10anikBX/+c1qEOYhvhzUX3b0N8aCBnnz8KFZdv6aVGtXFteBALHxbTpshHRSreeQrbRuI9nnbZJrjkVm4KDyyHg9FT5qqayEhRi97btdlfNP4J5zdcQlrJm00G4+0YM3W81i1WTPy/NWgpmjzUQWDPGLVakw8ekRroH/96GOh/0yo1dGIffcrtgXk1ylhkaBGiNoBjlYOmeJ4ZCYuCo+sx0PR7qB0Zp6kswwk7Fp2EAu+WC4G26q3qIQ+E7qahUdasG3fNSxbe1JMD+3bAF1aVzXIgwZ6wpFD+OfmDWF+p33cHN3LlY+/YPQdvIpijFk/Bq/C6yjDQkpyOx6ZjYvCI+vxUDxpAPfv30/ycz7y//XDOswb9ocw0Ow9OGXHd3DQU4RLbx6mQJniHqJQ5dNutdG3c8KqR+LuvXv44fBBrYGe2bxlAgOtUllB5ToPHrYJqxH5nTz28cWj5Ho8MhsXhUfW46F0ZkkGUZFR+P2zJTj8P433+clP3dF3YtcM7d6dUrB1la9/wscvt+yOQoODn3M6sX3gJTHh6GGsv3kDs5q3RMfSGplSdehWBEfcwcXI+miaW9PJ+8LbI1jwaJ32u1wjL6hRxfqghntcZxYFChRkghQ8uSKpkk4/rwBc2n8NFpYWGPPXcPT7qVu6GWhTlZZuP3Adn41dk+DF+QQNdVL7cP78eUxu8hE2d+8pDLRaHYnYdz/jjvc0THh0ByufrsE53wti2eq2NzHU7Y72u/msgzEy5y1Us9VUh30IJb9y4qLwyHo8FE/aCNy98ABB/iGo0SJjs05SC3rKu4/cwPJ1cWXbVlYW+H1C10QlR6NjY7H6+jX0q1gJ1jq9B9UxPojyH4V/fXyx610BIR+ayzYnhhUfjOJOReEf9hDeYY/xywPNIOqPJbrDxtIKrjYFRcWhAgUKDEPxpFMAqc5fwuP/nuHSe6+TKF2zRIYYaH0eqcWt+6/iGWgiOjoWgUHx0+ckRMXEYPS+PaLV1ZgD+7Q81JHX8Pp1d0z1jMHOdwWFgW7gXhe/VPhJGGjiqO8trYEmOD3x7joxXy7HwxSQCxeFR9bjkWU9aV09jYjwCNjaabIRXj7wwpwhy0S595yTU1C8cpF0jxFLoACMvX3aBiMvXnuKyfP2CNF+XTC6UaxQTvw9u3+8+eziPWrvbhx49BDWFhZY1KYd6uXJCzvsxblXc/GXbzFEqC3hYGmHgUX6o5ZbjXjfD4gMQEBUYAIertbZ4GqjyX1PLUxxPEwFuXBReHw4PJRu4clg97KDWDN5U4L5KgsV1LFqVGxUFrkL5TTJthgLXrkxvjg+MaB7HXzWs572vZeXF4oW1XioiSE6OgYvXgfgyfO3eOLpC89X/pjwZWtRNUjsOPRfAgNN8Fb8/GV8jeeI6GiM3Lsbhx4/En0I2U2laZGiQimsSN5ssLeIEAa6tHMxfF5sCNxtE3afoCFOqzFODMYcj4yCXLgoPLIejyxrpNt83gxWNpZY+aNGMN45h5PQgKaBbtyzHsau/AI27wWH0ooOzSuhRqVCGD5es63FU3vC1sZaeNK6cHQ0rGtx+PRdnDj3QBjl56/8ROhCF4N710Pe3BpDWatKEVz67xmCguMUAiVPumC+HPEMNNtcHX36RBjoZW3bo2GhQgiODhY8VHYfoVK+hRiX3QHlspWBhSrjI2OJHQ9zQC5cFB5Zj0eWNdK3z97XGmiCBpqo26EGvl87ymDvxdSCIY0rN59r389cdhCDetZDqWK5ERMTi5dv6Bn74va953jjd1FM/z6hizYU8uCJNw6fvqf9vr2dNQrnd0ORAm4oXMAd9jo3k7YfVYCzoy3Gz9B0PCFE01Y1Pfc4+dGv9+8VBtrW0hJ/tOuI2rnfYMP9H3AsyB1f5xuJ3MgNlU0NVDCjwJgk9SoHyIWLwiPr8ciyRnrN5I3ahrBaqIDXT71NaqCJ4+fuY/JcjdY08dTTVxhRj5wu8AsIQWRUwrp/es2Ska5XvRicHe2EUS5S0B253V204Q1DaFS7JCaObq3dZpEC7iKs0qh2Ce0y/SpVxvmXLzCvZWsUcT6IyXcO4WkktxeGcz4XUTJPnIiSuUC1xIwQ2MpMXBQeWY9HljXSL+57JeydqAY8770y+bb+Wn8m/mbeb/a1j6bll62NFQrld0OhfNnF4B4NcamiubTLs1sKXykZqOQNQMI3n38swiucLxn+2vkL4OgnfXHxzURMeBCASLUTHC2AgUUGoLJL/MFBc4FdeuQCuXBReGQ9HlnWSOcvmQdPb3jGM9T0rAuUSns5s+4g356jt/D4+VuDn1tZWuB/CwYKg2ppaWGyLhPrdl/Exm0ahTuCsfBYC8D5oxyY3609Srm7413EI6x4+DMuhzCeYYmyji4YUmI83GzdZNPtgj0x5cBDTlwUHlmPR5ZNwTu59Twmd52lfS+FPn7a8o3BTt4pAfU9ONj31/rTeOEVYHCZxFLiTIFph47h73NxRponOMYeUFupUCibKw70qovtT8dhe0AuWCIWXfPWROv8Q8wyOKhAQVbFO6WYJWk06FwL360dpX1fuFwBkxjoM5ceYcCY1fh5zm5hoF1d7NHmI31xooQDeaYsLe1arST6NS6HKGeVeKmyWQoD7WBtjdktWsLKpjDaZrdADccI/FRmKNoWGBrPQGeFUtvMykXhkfV4ZOliFq/Hb7RdvFm4Ymtvk6A5bErBdlT/7r8OJwdb9OpYA93aVEVoWGS8Mu18Hq7o2LwSmjUsE6+YxVSYdHYFVl9I6MFXLhaKTW2+h6XKEuqYN4CFC1Qq8xcCKFCQFfFO8aSTL2aRDDTB6eHVvxXzU4I7D7zw7IWv9v2n3eqgX+da2LhkEPp3rQ0HextRzKJbpv3ydQAWrT6uFTySILWsTyvO3mclpf69V437XhbY63VAvFNZ5k7UQJuKR1ohFx5y4qLwyHo8zOJJR0REwNY2aVF4lmUzTmys4lxaysJDQ0Ph4KDpImKsJ83BQLagOnH+gUiR++2HTmkuCw8ODoaTk/GedWhUFO6+9cFtHx/c8fHGwCrVUCxHDpRaMAdRsQlPq4UqFheG9EAOu6RbfaWUR3pBLjzkxEXh8eHwkGVZOElNnz4dtWvXxuXLlzF48GDkz8/2S3GIjo7GhQsXMHXqVIwfPx5168aP25oKbjrGmJ1+jU2hoRe8YsMZHDhxW8SVma+czdlOZHJYWRlOaI+1BaKcDc/Xha+vb5In+nlgAPY8uC+MMjt3P/H3j+cvV/LII4y0vV0EokKtE7S0cnGITtZAG8MjoyAXHnLiovDIejwy1EhPmzYN7du3R506dVC+fHlhhFetWhVvGXq19J6dnZ0T5jGnE6ytky//pjf896az2HnohqgSJBrXKYlBveqJ6r+ksO7Gf5h/PuHAwqhatTG6dt14PNi26llAgDDCNMaNChdGzXyaG9nTgADMOH0q3jpc7CyR3SkGHxesjLI5c0IdG4B8+V/j3f2COr0HNf/z5XttsuOREZALDzlxUXhkPR4ZaqQPHjyIoUOHium8efNi//79CZah208jvnjx4gzjZYx61ZEz98SAIFGzcmEM6VMfpYt5GLX+1iVcEBTpgZVXNUYyr7MN2pZyE/MDwsOw/+FDYZT/8/LCgwB/EcaQwGgPjfTDoEe4HX4GRXJHwdI2ADYOoXB0CIeNjaZasWPpViiXLbe4sZXO5SPM8vMXuRAWZgN7+0gUzO+NCrnfmOx4ZATkwkNOXBQeWY9HhhrpV69eaYVI7OzsRPiDsefUlGEzrs2XBK4rJdCNEz979hSFChWOFydmRgYrAosWdNeKJP135yW6tK6CKuWSDxnoYt2dzVh91UXr0b4KisAfl7wQrr6HAeVH4/vD8QcrrS1VcHe2QHWPQqiWJ68wvM99JuF0gC3yvldOZX5zfpsQFLQOQSE7a3jY5Rbz+RTSNXsQFkfbwz1HkNCAVkEt/rfPHmkUX29vb2TPnvoMF1NBLjzkxEXhkfV4ZGh2B42xJERCwxMVFZXqVlQMnTDoLr0KFCigPVhv377FgwcPEBkZKarndPMYOQrLIP/qTSe0baUmLzypnd6y5wp+W7AF3Yctx7ipm+DvH4AXL17Ax/s1xn3eGLaqoHjru3jxooij37t3T9Tv80bEGDe3cf7qVex7+AAbr8UZaA00IYgD97Pj8PPtKOyuRtE8AShZ/AWqVHyIGtVvoWjpG2hVzhGF1Jp9KmodhubOLzDI/Sm+d/PDH6WL4FPrahhcagbyhU2AbZSN2K7Y/tu6ooVVfusQWNOYW4eI9y8D6+L27dvihsZ94ovTnKe7TxzISGyfpFFsaVkeXx5nHm8e9zdv3gipU+rrSkLo0rJ8z/n8nMsld548PDy0+0Qe5ENePOa6yxqzT0mdJ2P2idetKfaJ20vLPhUrVsxk+5SW8+Tn52eyfUrLeSpQoEC6XHsp3Sc6nanZJ9lldzCMsWnTJjFYGBQUhHLlyuH58zh1OF3069dPhEbq1YvTW07Ok+YJMza7Q7/FVN7c2VCiSC7cvPdK62EXyJsdsyd2RZ5cCTtiJ4WY2FgM3L4N5154Iio2vqyofrZFnVp3481zswxHQZtgFLQJRbX8i1HESdOCSh11G1A5AZYFkr2xrby/Bm8Cd6BbzkfIZxOKl5EO2OhTDB7Z2mNAyX7J8udFVaOG+fU75MJDTlwUHh8OD1lmd3Ts2BG3bt0SRpot0Dt06KAlyztz4cKakAPBe0dS9w+m8CWXxpeSFlOv3gSKF5HL3RkDe9RFy8blhL5GUmBnkwsvX+Chny8+rayp3be0sBBxZRro/C5OeB0agOhoywTZFvb2Eajr+AaFbEJR0M4FBR2LwNmuDmBVBrAuDZVFnP6zyrqs0fvWwd0bAbaPNPsV5SDi2j1yPYKrs7dR35fDRS8nHnLiovDIejwy1Eh//fXXWLBggXDz6fpPmTJFzD906BDOnj2LmTNniuyObdu2iceB7du3IyYmBo0aNTI5lxUbzmrLs3XBePQ/Cz8TynSJwTskGEefPBF6zKefP0NIVBQsVSrRWdvVzh7RsdHoVCkXihZ5ilexF+Dk54y79wskyLaoUugFhpaaCliVhEplJx6PmJ6YVmTP1g/ZnVsm/MDCuE4zpuKRVsiFh5y4KDyyHo8sWxbepMccRBnQcba2tsTRDV8Z/M7Oe3ex/Mol3PSO75HmdHBE48KF8WXtusjj5ISJNyfhaehL8ZkF1Chi8w4XXueH5wt3hIbZwsE+AgXyv8XXRR/i41I7U73PChQoyLyQZbhDTnBwtUWAT6heAEIzn3gXEY6Tz56hWt688HDSVKIER0YKA83vVMztgSZFiqBx4SKwtQ9GCeeiQqRIHfUAFa3Pw88iFxo7e6FJNhtYWpbDg2wn8W/uQngd5QAP61B0dH2G/C6j43HigEPZssaHNdILCg/5clF4ZD0eWdZIf96rPmbMP5Ag56JM3fzovWUjLr16hejYWPzUqAn6V64iPv+4aDFYW1qiUaHCcLazwhnfc1j/Zik8Q1/g65IjUSV7JcCqOFrnsEF79yjYOH0P2DbGVs/18Ay+jyHu94SBpqH+N6AQCljFoIsOJ/3qS3NB4SFfLgqPrMcjyxrpCFcV/Mqq4PxMDatQINoBCCqswtaAh8B7Abli2XPAziruEOV0dET9ou7Y/2YnTvqcRmhMmJhvo4qFdzg7ulQSmRcO7mugsojLCGni5IUA9XPEqlV4FanJE2+f7TlcnbwSPP4YE6pJbyg85MtF4ZH1eGRZI/376VMIdwfCc+pkb6jVsFFZ4PuGjUQoo2A2TQduIiw6DAseLsWNwFvaebmswvCR8ys0cPSFU47PtPN1DbQpBvIUKFCQdZFljXRAbKSm5loXfK9SacMbUbFRsLbQ1OTbqqIRGPFEVO9VtPcTxrmCfRQsHHtB5fCJkP5MDCrLXABfyUAOHgGh8JAvF4VH1uORZfWkC2V3iTdoSPB94ezZ8Dj4CZY9WoEvr44THrT4TO2LT13PYEbei/jawweVcw2BZa4TsHAem6SBTglYsSQHKDzky0XhkfV4ZNkUvG9PrsGmKz4Jc5dL+8LBNU6IaGixQajnrsl/jA2aAZVlccC+LVQqNnBVoECBgtRB6cySDCxVYShd0hMODhFQqWLFf/He9Q2sVBCVgBM8rqNOtjza71g4j4PKoXO6Geis0K8tM/KQExeFR9bjkWU96XFXRsAriqGM+JnS2Swi8UveK3CxjAZsP4bK+RuorN5LzylQoECBiaB40sngbTRlOxNGpUNjreHi1Akq972wyL4oQw20pLBlbig85MtF4ZH1eGRZT/qHq/3xItJK6CxLYOZGfpto/FolfreYjALlDK108rLNBYWHfLkoPD4cHoonnQw6ZHusFcQnJGH8jtkem43To0ca5TpzQ+EhXy4Kj6zHI8sa6ZJ2wBfu8YXxR7jfQnE783HKlSv5XOqMgMJDvlwUHlmPh/mfE8wEK5uKqGlxEDUcfLWSpfwfYtXcbJzYOUIOrYAUHvLlovDIejyyrJF2yv4T1GFVoArbCHX0C6is8gP2PeBk385snNhOTA5QeMiXi8Ij6/HIskaapdoqp0GA0yDRhMDJycnclODm5gY5QOEhXy4Kj6zHI8vGpHXx5MkTyAEKD3nykBMXhUfW45FlU/AUKFCgwJxQUvBSgKxQWpoSKDzky0XhkfV4ZLgnff36ddEpnJ3BE+uw+/jxY1y6dAk5c+ZEkyZNjFqv4kkrUKAgM0GWnvSZM2ewf/9+dOvWDTdu3MCWLVsSLPP06VPMnz8f3bt3h4WFBWbMmJHuvK5cuQI5QOEhTx5y4qLwyHo8MtST7tmzJyZNmoTSpUvDz88P7du3x6lTp+It8+OPP4rW6G3bthXvy5cvLww621KllycdGRkJGxvzS48qPOTJQ05cFB4fDg9ZetIUIZHIkBxDH0ktQ4SGhuLNmzh95/TAs2fPIAcoPOTJQ05cFB5Zj0eG5kmHhITA3t5eTFtaWgpRkpiYGDFtaBnCwcFB3Gk8PDzirSsiIkK8dO9KqYUcKpYIhYc8eciJi8Ij6/HIUCPt6OgojDJBAx0bGxvPQOsvQ7DQhIZaH9OmTcPPP/9sUOjE1dUVAQEBKFCgAG7fvo3KlSsLD50Dlbdu3UKhQoVEuMXa2hp2dnYiDl6hQgXh2VerVk277N27d5E3b14EBQWJdTs7O+PVq1ciXCMtc/nyZVSqVEnkSbq7uyM8PFxUH+XIkUPcXcuVK6dd9tq1ayhbtiw8PT0FR+4nb0q8AT18+BC5c+cWHLgsQzzFixfH69evxTHhcUrJPr19+xZFihRJ1T5x0LZmzZom2SceV2nZlO4TuXFZU+xTWs8Tn+b4P637lNbzRL7SNWLKay+l+3ThwgXUr1/f5NdeSvcpV65c6XLtpXSfXr58CR8fnxTtE9dNJBdxzlAjXb16dbHjJMoDxPeJLSPB1tYW+fPnT7Dc999/j6+//lr7ngeJF2HVqlXTcQ8UKFCgwLTgTYvhX1kY6aFDh2LXrl3CuG7fvh3Dhg0T80+fPi3uXkOGDMEnn3yC5cuXo3Xr1jh+/Dh69eplcNCQxpsvCSzr5h2Vd7LkBhl1wTAJ76b8rjlT9xQe8uQhJy4Kjw+LBz1oGmh64kkhQ400c55pRJl6x0ePRo0aifl8ZOEAIVGqVCkMHjwYmzdvFrFpZoMYA6brGfK4jQUPrrmNgcJDvjzkxEXh8eHwSMqDNpvAEsMZ+mGOEiVKiJcEGmq+FChQoCCrQykLV6BAgQIZI8sbaca1f/rpp3jxbYWHwkOOXBQeWZPHB6OCp0CBAgUfIrK8J61AgQIFcoZipBUoUKBAxvjg2mcxerNixQqRCsOCmf79+ycqfLJkyRJRNcXKJAkrV64UFUnSdxlnYnUk18nST+Y1fvrppyLlLzmsX79eLMfinN69eyeanrNt2zaR592sWTPtPKYg8nusXvrqq69Eqs7z58+xc+dOkV9O/VpWV+l+JzHs3r1b8GZ5PUWt8uTJY3A55quz+rJPnz7aeUyBHDt2LPz9/YWC4WeffSbmb9q0SRxrcqRwFiu+kgPXz4pQitHwuLMqyxDu3LmDgwcPYtSoUeI9K1Nnz56Nb775JsGyifFLCqwwIxemeBYrVgx16tRJsAyr2w4cOAAvLy9RfdmyZUsxnzK7x44dE9dIwYIF0aBBAzH//Pnzgje5cnkKgyWHFy9eiPPJajpeG61atUqwjK+vr0hZ5f5xe6wbSIrfwoUL0a5dO5HWumDBAowbNy5ZHrzW161bJ6SBCapU6oMpsv/73/9Ew1VW6w0fPlzUI/Da4rFgOu1ff/0l6huY98vKvq1bt4rCNVYMS4JpSYEyD/z9sRUVt8ffnz5YVbh27VrxOa9n1lzw971q1Sq0aNEigXxEYvzSakN4nvfu3SuqESmtzPXmy5cvURvCCkOuk+eaVdS0IUbXc6g/MCxfvly9bds2MX3mzBn1pEmTEizj5+ennjVrlrphw4bqY8eOaeevWbNG/c8//4jpK1euqL/77jsxPW3aNPXJkyfF9I4dO9QLFy5MlsfBgwfVc+bMEdMvXrxQDxw4MMEyUVFR6t9//13dsWNH9d9//62d/++//6ovX74spleuXKnu3LmzmL558ybHD9R58uRRN2rUSB0cHJwsj9u3b6u/+eYbMR0aGiq2ZQhLlixRDxgwIMHxcnd3V2fPnl1dsmRJsX3ixIkT6unTp4vpN2/eqPv165csDx8fH3X//v3FdGxsrLpNmzbqmJiYBMutW7dOPWbMGPWnn36qnffs2TOx30WKFFHXrl1bvHjcEuOXFCIjI9WdOnXSvu/Ro4fa398/wXI//fSTdvlSpUqJ64F8O3ToIPgTffv2VXt7e4vv9+nTR7tv7dq1E+c2OZBHRESEmB4xYoT6/v37CZbh+ZCOU/369dV79uxJlB/RtWtXtbW1tbpgwYLq9evXq40BjzXPo3StHz16NMEyv/32mzokJERMc18XL14spvlb4LnJmzev+quvvtIu36VLF3G9EV9//bVR52b8+PHqq1evaq8D3d+EhKVLl6pfvXqlXX7cuHFimteug4ODulq1auL6aNCggfrt27eJ8kurDdm8ebP6559/FtNbtmxRt2/fPkkbMmXKFPXZs2fF9NatW8V+GIsPLtyxYcMGrWdMb4Yegj7oEY8ZMwZFixY16rvGrDMpHrzDHjp0KEFHYSsrK+EJUDdAF/TU6LERvEPTG+Cdm+Ddm16b5M0lB3ozksdKz5FVUfTODVWDSsVF+p4qtTzofVI3gdi4caPWU6THRq+UHlZSoJfLqiyCHgS9C+6HPugp0hPUBTUPWKlKz5FeFD8fOHBgovySAjUndI8bzw2PqS74dMAnBYL6Ck2bNsWePXtw9epV8V7ygOjZktfhw4e1Tyf8jAVbJ0+eTJKHpPUgeWglS5YUT0/6+Pvvv7XXDT3tHTt2JMqPoDdJj56aEj169Ej2eHDd1HnneSR4DP/5558Ey5EbvXrpmiQPgseSXj21Mfi0Q1Dngk99klAarz9eM8b8ZqTrKrHf2b59+7SKc7o8WFfB88N1UIN+0KBBwiM3xM8YHsn93hs3bowuXbpoKw7ZxMTUNkTCB2ekeXHyR6JbKp6a7/Li50XJx6t79+5pu4nzsZ4hgZSsSzLIvHiNwYQJE7SPh3yk4wUohVd4sZ09e1ZccLoaJ8byYNgkJbKKXJZCMYsWLcLNmzcNrpOPfHy8TQkPY48jweIn/iBZpUo+HTt21IZXDPFLKw8+kkpGTzoH1IVJ7Lup2Tdjv8ObsZTaJfFIjB/Ba5YC9DTi//77b7LHg8ZUV+QsMR4MuUgVvbrb4++DNz7eQBk+pDOh+3sx9nhwPbxx8XeS1HcWL14sBI70eXzxxRfiRkdjyd8I5SUS42cKG8IbAH+XR48eFZr41BJKyobQ6ZKE4lJy7X+QMWnGjyXvhF4ND5C+HKox3yVoGKlYpavWx/9SCXtK1mXs9wj+CCX8+uuv+OWXX8Q0L0J6o4yVUdeE3m9yHkpaeBCMaTKuyDgyPSL+AFOzzrTwkDxfeixHjhzRHo/E+EnqYmnhQRU0gl6pt7c32rRpIzxMQ9/ldaKbI2vK4yHxYOyZHi8998T4EYzJ83gQH3/8sYi56465pJaH9BTEeCrHWtasWSPed+rUSTyZ8rdGVcqlS5cKbzy9ro88759Y+JtmByf+PgjppsB5vIlLMMSP8XRT2BAuRweFBptGmPFwQzaET5n8Lz2BpfQ3+MF50jRwks40Dw4fuYwx0PrfpWHmAefdj3c+Tkt3b56UlKxLMjC6xtcY8ILi46v0+E95Vg42EZRN5GN+SnkYy5/goyQ9EEK68GgsUrPOtPCQwIEXyYtKip+pePBJZdasWcIr5foT+256Hw86Cny6onHU1XrQ50fvbObMmdrPGY5hCMBUPPiboMdIb5brJkaOHKn1TqVrMjXHgzc53d9pct/5+eef8d1336FKlSraebxR8wmDPCQY4mcqG0IDzUFnDrR26NBBbN+QDaGTwZuIxCOl1/4HZ6TpPUiPJ9QAZuwoNd+ld9KwYUNx9/voo4+0xtHYdequiyeNF3VKhMEZw+bjPTMnaIw44swLRvpx8M5tKCshKR5SDDIpz0oXzCiQNFSYSUJvgB6V7jp5EdJz0x9VT44HQz9SZoSx4HHQHZlPjF9S4LnTjckndj5pGKnGyDAKb9IMHfB60O0SJH1Xf9947RiK7+uCxkXXm0qMB3/YzNigMWb8XAphGOLHa0T3PFBTmZkfSYEZHXxJGu5JXd/Lli0TmTT0lCUeNEqSAZOuSX4uOTXJrVMXzPiRQoJJfWf9+vUiHsxjrBvSYcaTFC6RYIifKWzIgAEDtOMCHNui4eU1mJgN4biBdN2l1C59cNkdzAQYO3asyGrgf2m0eNOmTerBgweL6ejoaPXdu3dFhsTcuXPVL1++FPP5n5kQ/O7333+vvnDhgpjP9xxJvnPnjnrkyJHqhw8fJsuDI/4cTeao9tSpU9X79u0T88+dO6du2bKldrkHDx6oe/fuLbg+ffpUzGMmSbly5UQmBkeNW7RoIeaTM/meP39ejGZ7enomy4PZA+TB4/DHH3+oV6xYIebzu+XLl9cux21z38mFnIjw8HDBndtjxsXhw4fF/MDAQPXo0aPVN27cUM+YMUNkvBiDH374QX3q1Ckxcv7rr79qsxMKFSqkzQTgOWBWTOPGjcX+8lxJKFasmJZbUvySAzN7du3aJTJ7dEf8K1WqJK4fZmgwi6NVq1biHDRv3lybKTFv3jyRfcP94LUgYcKECWJ9O3fu1I76J4dVq1apV69erb506ZK4NqV9ZebL6dOnxfTQoUPVTZo0ETzIh9tPih+zdA4dOiT+SxkwyeHAgQPq2bNni/P52WefqYOCgrTbljIVmM1Tq1Ytsb22bduK3wfB/eW2uY5BgwZp94Hf++uvv8R1x3XyPCcHLsusFf7ehg0bpr2+p0+frs0m4np5nsiDWTT8HUhgZoWUZSMhMX6psSHcNnlJ6+V1fOvWLbGMlAGSmA2hHeA1QhvyxRdfqJ88eaI2Fh9kWTgfO+hF8A7HRxLJ82CuML0GepP//fefuMNy9/k4wngvwc8ePHggHo1023jx+8yHpFpfUjFPXdA74bo44CLFzDiPd1gptsZBHnqA5MH1cuSX2QxcRgJj0GXKlNHy4GMt+RqTq01w3eTBfdf15vl0IA0GcdCN+867Pr03qXkCp/ldevC6x0PaN3p3ugNgyYH7xhASu9BIoOchecD0duiRSLHAihUrao83j4mUhSAhMX7JgV4NvT3pyUT3ePA46Hd/5gCVtJ8cJOXTkRQXlsBBTIYdEstDNwR6jsyn5VOTBIZsuJ+8PvUzYBhjZsgjKX7kwestJY/U9AS5Xd3rSuo0wt8Qu6DohjB4nKS8YA6O8bclZThI4HyGZLhvxuYE8+lCur4lrzgwMFB8n78DxuB1W+XxmpaytHg+yUP/iTUxfqmxIYzJSzF//q44BkIOusc6MRvCJ2Fe/ymxIcQHaaQVKFCg4EPBBxeTVqBAgYIPCYqRVqBAgQIZQzHSChQoUCBjKEZagQIFCmQMxUgrUKBAgYzxwZWFK8hY3Lp1S+hLEEyZYvoWU6VYaCAVVpw4cUKkL1KuNTHZ2JRsj9tJTaNifpepZCwwSK7oRYECuUAx0grSBFaXMW+V5eusAGRuLzWjKXBD0RuWy9IgsnKSOgppNdJU9WMJsTE6yfpgPuuff/4p8lw/BCNN9T5DGtQKPiwo4Q4FaQZLb3W1F1hwMWLECK2QDZP6dYtX0gJqWKTGQBMsENEtGsnsoGyrgg8fiietIF3ASitWDrIiUKpgY8UaVew4n1KsrATbvn27+Kxu3bpCxY6eLqvLqAfMyjlWINLA8ybACjfqCdMjlrQxWGXGdfI/tR+k7jf8HiUrWbHICi9jweo2qWtLkyZNRIUZBYV4o6G4E58SqP+gP0/qkMOqRYr4kGO9evW0nXcYZqF2OEM/nK8vtsUKQooD8WmDx4U3FB4PVr5RapN6D5RrJS8+uVDoiGEmdhvh/jGEQ/CYXb9+XVRDVqpUyeA+kiP58BxwHayEUzxy+ULxpBWYHCxiZTujiRMnxitdp0ASDSlLnSkMxLADPVtqY7PsncaZZbNsgsCybXqKNH4s86X4PQ01P+e0VH5LBTIacRrUrl27ilJyiu6wUQLlO8ePH6+NmScHbpM3Bxo8botiQiyvpiGmFjHLlb/99luxrP48GnO2/KJSH1uU0ZiOHj1aLEse1GNmqIZ6w2xDZUhwiWXZNP7cL0mfuF+/fuLJhDcb7iM/442Ix5aGntKkkoHmfs6dO1eoJrIRAbdnCJQ7ZZOEzz//XNxoWLo9Z86cFJ9nBRkDxUgrMAnoHbP7BDtOULWNEpH0HHVB48uYND1RSUKTHjF1DOiNEtRsoMg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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -2342,13 +2134,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T02:45:02.789208Z",
-     "iopub.status.busy": "2026-09-10T02:45:02.789097Z",
-     "iopub.status.idle": "2026-09-10T03:58:42.701874Z",
-     "shell.execute_reply": "2026-09-10T03:58:42.701412Z"
+     "iopub.execute_input": "2026-09-15T01:01:00.126724Z",
+     "iopub.status.busy": "2026-09-15T01:01:00.126664Z",
+     "iopub.status.idle": "2026-09-15T01:36:58.814443Z",
+     "shell.execute_reply": "2026-09-15T01:36:58.814010Z"
     }
    },
    "outputs": [
@@ -2356,26 +2148,26 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "p=0.001: MPS-MPO 2.500e-04 +- 1.4e-04 | BP 5.000e-04 +- 2.0e-04  (12000 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
+      "p=0.001: MPS-MPO 1.667e-04 +- 1.2e-04 | BP 5.000e-04 +- 2.0e-04  (12000 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "p=0.01: MPS-MPO 1.667e-03 +- 7.4e-04 | BP 3.667e-03 +- 1.1e-03  (3000 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
+      "p=0.01: MPS-MPO 2.000e-03 +- 8.2e-04 | BP 3.667e-03 +- 1.1e-03  (3000 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "p=0.1: MPS-MPO 6.200e-02 +- 1.1e-02 | BP 1.920e-01 +- 1.8e-02  (500 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
+      "p=0.1: MPS-MPO 7.000e-02 +- 1.1e-02 | BP 1.920e-01 +- 1.8e-02  (500 shots, 0 MPS-MPO shots raised and were counted as failures)\n"
      ]
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
diff --git a/examples/decoding/dephasing_dmrg_debug_bb.ipynb b/examples/decoding/dephasing_dmrg_debug_bb.ipynb
index 5060d2ef..54f04650 100644
--- a/examples/decoding/dephasing_dmrg_debug_bb.ipynb
+++ b/examples/decoding/dephasing_dmrg_debug_bb.ipynb
@@ -26,10 +26,10 @@
    "id": "7801dfd0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:19.746541Z",
-     "iopub.status.busy": "2026-08-30T18:28:19.746450Z",
-     "iopub.status.idle": "2026-08-30T18:28:19.805621Z",
-     "shell.execute_reply": "2026-08-30T18:28:19.804916Z"
+     "iopub.execute_input": "2026-09-15T01:37:02.013888Z",
+     "iopub.status.busy": "2026-09-15T01:37:02.013713Z",
+     "iopub.status.idle": "2026-09-15T01:37:02.081456Z",
+     "shell.execute_reply": "2026-09-15T01:37:02.081129Z"
     }
    },
    "outputs": [
@@ -37,8 +37,8 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "REPO_ROOT: /Users/aberezutskii/mdopt/examples/decoding\n",
-      "EXAMPLES_ROOT: /Users/aberezutskii/mdopt/examples/decoding/examples\n"
+      "REPO_ROOT: /Users/aberezutskii/mdopt-notebooks/examples/decoding\n",
+      "EXAMPLES_ROOT: /Users/aberezutskii/mdopt-notebooks/examples/decoding/examples\n"
      ]
     }
    ],
@@ -77,10 +77,10 @@
    "id": "2c07a284",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:19.806882Z",
-     "iopub.status.busy": "2026-08-30T18:28:19.806779Z",
-     "iopub.status.idle": "2026-08-30T18:28:21.361742Z",
-     "shell.execute_reply": "2026-08-30T18:28:21.361241Z"
+     "iopub.execute_input": "2026-09-15T01:37:02.082808Z",
+     "iopub.status.busy": "2026-09-15T01:37:02.082745Z",
+     "iopub.status.idle": "2026-09-15T01:37:02.377157Z",
+     "shell.execute_reply": "2026-09-15T01:37:02.376691Z"
     }
    },
    "outputs": [],
@@ -115,10 +115,10 @@
    "id": "60b97ca0",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:21.363717Z",
-     "iopub.status.busy": "2026-08-30T18:28:21.363524Z",
-     "iopub.status.idle": "2026-08-30T18:28:21.388327Z",
-     "shell.execute_reply": "2026-08-30T18:28:21.387703Z"
+     "iopub.execute_input": "2026-09-15T01:37:02.378174Z",
+     "iopub.status.busy": "2026-09-15T01:37:02.378081Z",
+     "iopub.status.idle": "2026-09-15T01:37:02.390540Z",
+     "shell.execute_reply": "2026-09-15T01:37:02.390141Z"
     }
    },
    "outputs": [],
@@ -154,10 +154,10 @@
    "id": "142fd16e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:21.389531Z",
-     "iopub.status.busy": "2026-08-30T18:28:21.389431Z",
-     "iopub.status.idle": "2026-08-30T18:28:21.857829Z",
-     "shell.execute_reply": "2026-08-30T18:28:21.857223Z"
+     "iopub.execute_input": "2026-09-15T01:37:02.391321Z",
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@@ -191,10 +191,10 @@
    "id": "fbbd1566",
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-     "iopub.execute_input": "2026-08-30T18:28:21.859205Z",
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-     "shell.execute_reply": "2026-08-30T18:28:21.874376Z"
+     "iopub.execute_input": "2026-09-15T01:37:03.479933Z",
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@@ -239,10 +239,10 @@
    "id": "68a33209",
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-     "iopub.execute_input": "2026-08-30T18:28:21.876171Z",
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-     "shell.execute_reply": "2026-08-30T18:28:21.894499Z"
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@@ -380,10 +380,10 @@
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-     "shell.execute_reply": "2026-08-30T18:29:38.800278Z"
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+     "shell.execute_reply": "2026-09-15T01:38:20.639800Z"
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    "outputs": [
@@ -400,7 +400,7 @@
      "output_type": "stream",
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       "\r",
-      " 25%|██▌       | 3/12 [00:00<00:00, 18.69it/s]"
+      " 50%|█████     | 6/12 [00:00<00:00, 25.63it/s]"
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@@ -408,7 +408,7 @@
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+      " 75%|███████▌  | 9/12 [00:04<00:01,  1.81it/s]"
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@@ -416,7 +416,7 @@
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+      " 92%|█████████▏| 11/12 [00:08<00:01,  1.03s/it]"
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@@ -424,7 +424,7 @@
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+      "100%|██████████| 12/12 [00:10<00:00,  1.27s/it]"
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@@ -432,39 +432,7 @@
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-     "name": "stderr",
-     "output_type": "stream",
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-     ]
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-     "name": "stderr",
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-     "name": "stderr",
-     "output_type": "stream",
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-     ]
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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+      "100%|██████████| 12/12 [00:11<00:00,  1.09it/s]"
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+      "  3%|▎         | 1/36 [00:02<01:24,  2.41s/it]"
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@@ -495,7 +463,7 @@
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+      "  6%|▌         | 2/36 [00:04<01:20,  2.36s/it]"
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@@ -503,7 +471,7 @@
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+      "  8%|▊         | 3/36 [00:07<01:17,  2.34s/it]"
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@@ -511,7 +479,7 @@
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+      " 11%|█         | 4/36 [00:09<01:14,  2.33s/it]"
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@@ -519,7 +487,7 @@
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+      " 14%|█▍        | 5/36 [00:11<01:14,  2.40s/it]"
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@@ -527,7 +495,7 @@
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+      " 17%|█▋        | 6/36 [00:14<01:13,  2.45s/it]"
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@@ -535,7 +503,7 @@
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+      " 19%|█▉        | 7/36 [00:16<01:08,  2.36s/it]"
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@@ -543,7 +511,7 @@
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+      " 22%|██▏       | 8/36 [00:18<01:04,  2.30s/it]"
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@@ -551,7 +519,7 @@
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+      " 25%|██▌       | 9/36 [00:20<01:00,  2.25s/it]"
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@@ -559,7 +527,7 @@
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+      " 28%|██▊       | 10/36 [00:23<00:57,  2.21s/it]"
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@@ -567,7 +535,7 @@
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+      " 31%|███       | 11/36 [00:25<00:56,  2.25s/it]"
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@@ -575,7 +543,7 @@
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+      " 33%|███▎      | 12/36 [00:27<00:55,  2.29s/it]"
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+      " 36%|███▌      | 13/36 [00:29<00:50,  2.20s/it]"
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@@ -591,7 +559,7 @@
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+      " 39%|███▉      | 14/36 [00:31<00:47,  2.16s/it]"
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@@ -599,7 +567,7 @@
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+      " 42%|████▏     | 15/36 [00:33<00:44,  2.13s/it]"
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@@ -607,7 +575,7 @@
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+      " 44%|████▍     | 16/36 [00:35<00:42,  2.11s/it]"
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@@ -615,7 +583,7 @@
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+      " 47%|████▋     | 17/36 [00:38<00:40,  2.15s/it]"
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@@ -623,7 +591,7 @@
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+      " 50%|█████     | 18/36 [00:40<00:39,  2.20s/it]"
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@@ -639,7 +607,7 @@
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@@ -655,7 +623,7 @@
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+      " 61%|██████    | 22/36 [00:49<00:28,  2.05s/it]"
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@@ -711,7 +679,7 @@
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+      " 81%|████████  | 29/36 [00:59<00:09,  1.41s/it]"
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@@ -719,7 +687,7 @@
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@@ -727,7 +695,7 @@
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@@ -735,7 +703,7 @@
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@@ -743,7 +711,7 @@
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+      "100%|██████████| 36/36 [01:06<00:00,  1.84s/it]"
      ]
     },
     {
@@ -822,10 +790,10 @@
    "id": "92e2797f",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:29:38.802118Z",
-     "iopub.status.busy": "2026-08-30T18:29:38.802009Z",
-     "iopub.status.idle": "2026-08-30T18:29:38.827227Z",
-     "shell.execute_reply": "2026-08-30T18:29:38.826654Z"
+     "iopub.execute_input": "2026-09-15T01:38:20.641271Z",
+     "iopub.status.busy": "2026-09-15T01:38:20.641188Z",
+     "iopub.status.idle": "2026-09-15T01:38:20.658869Z",
+     "shell.execute_reply": "2026-09-15T01:38:20.658396Z"
     }
    },
    "outputs": [
@@ -833,7 +801,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "amp_zero = 0.0003116555556050491\n"
+      "amp_zero = 0.0003116555557114791\n"
      ]
     }
    ],
@@ -881,10 +849,10 @@
    "id": "96adfaeb",
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-     "iopub.status.idle": "2026-08-30T18:29:42.641315Z",
-     "shell.execute_reply": "2026-08-30T18:29:42.640799Z"
+     "iopub.execute_input": "2026-09-15T01:38:20.659775Z",
+     "iopub.status.busy": "2026-09-15T01:38:20.659711Z",
+     "iopub.status.idle": "2026-09-15T01:38:25.339696Z",
+     "shell.execute_reply": "2026-09-15T01:38:25.339376Z"
     }
    },
    "outputs": [
@@ -901,7 +869,7 @@
      "output_type": "stream",
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+      " 10%|█         | 1/10 [00:00<00:04,  2.14it/s]"
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@@ -909,7 +877,7 @@
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-      " 20%|██        | 2/10 [00:00<00:02,  2.68it/s]"
+      " 20%|██        | 2/10 [00:00<00:03,  2.15it/s]"
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+      " 30%|███       | 3/10 [00:01<00:03,  2.15it/s]"
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+      " 40%|████      | 4/10 [00:01<00:02,  2.15it/s]"
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+      " 50%|█████     | 5/10 [00:02<00:02,  2.15it/s]"
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@@ -981,16 +949,16 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 10/10 [00:03<00:00,  2.65it/s]"
+      "100%|██████████| 10/10 [00:04<00:00,  2.15it/s]"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "bitstring_star: 111111010010001000101010\n",
-      "amp_star      : 0.015581332495539018\n",
-      "amp_zero      : 0.0003116555556050491\n"
+      "bitstring_star: 110100100100001000101010\n",
+      "amp_star      : 0.015581332500471024\n",
+      "amp_zero      : 0.0003116555557114791\n"
      ]
     },
     {
@@ -1030,10 +998,10 @@
    "id": "edd98c6e",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:29:42.642658Z",
-     "iopub.status.busy": "2026-08-30T18:29:42.642539Z",
-     "iopub.status.idle": "2026-08-30T18:29:42.658868Z",
-     "shell.execute_reply": "2026-08-30T18:29:42.658138Z"
+     "iopub.execute_input": "2026-09-15T01:38:25.340641Z",
+     "iopub.status.busy": "2026-09-15T01:38:25.340584Z",
+     "iopub.status.idle": "2026-09-15T01:38:25.350508Z",
+     "shell.execute_reply": "2026-09-15T01:38:25.350208Z"
     }
    },
    "outputs": [
@@ -1041,7 +1009,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "eps: 1.5581332495539018e-11\n",
+      "eps: 1.5581332500471024e-11\n",
       "MAP(identity) [estimate]: False\n"
      ]
     }
@@ -1066,10 +1034,10 @@
    "id": "dfd99e59",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:29:42.660406Z",
-     "iopub.status.busy": "2026-08-30T18:29:42.660270Z",
-     "iopub.status.idle": "2026-08-30T18:29:43.347715Z",
-     "shell.execute_reply": "2026-08-30T18:29:43.347149Z"
+     "iopub.execute_input": "2026-09-15T01:38:25.351338Z",
+     "iopub.status.busy": "2026-09-15T01:38:25.351291Z",
+     "iopub.status.idle": "2026-09-15T01:38:25.823083Z",
+     "shell.execute_reply": "2026-09-15T01:38:25.822801Z"
     }
    },
    "outputs": [
@@ -1077,10 +1045,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Exact amp_max: 0.015581332495541163\n",
-      "Exact amp_id : 0.0003116555556050921\n",
-      "Exact MAP bitstring: 111111010010001000101010\n",
-      "DMRG amp_star / amp_max = 0.9999999999998623\n"
+      "Exact amp_max: 0.015581332500470689\n",
+      "Exact amp_id : 0.0003116555557114724\n",
+      "Exact MAP bitstring: 110100100100001000101010\n",
+      "DMRG amp_star / amp_max = 1.0000000000000215\n"
      ]
     }
    ],
diff --git a/examples/decoding/maxbonddim.ipynb b/examples/decoding/maxbonddim.ipynb
index 2a2f1181..b2091386 100644
--- a/examples/decoding/maxbonddim.ipynb
+++ b/examples/decoding/maxbonddim.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T17:26:41.777003Z",
-     "iopub.status.busy": "2026-08-28T17:26:41.776936Z",
-     "iopub.status.idle": "2026-08-28T17:26:43.027579Z",
-     "shell.execute_reply": "2026-08-28T17:26:43.027110Z"
+     "iopub.execute_input": "2026-09-15T01:38:29.009488Z",
+     "iopub.status.busy": "2026-09-15T01:38:29.009352Z",
+     "iopub.status.idle": "2026-09-15T01:38:29.416315Z",
+     "shell.execute_reply": "2026-09-15T01:38:29.415849Z"
     }
    },
    "outputs": [],
@@ -72,10 +72,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T17:26:43.028648Z",
-     "iopub.status.busy": "2026-08-28T17:26:43.028536Z",
-     "iopub.status.idle": "2026-08-28T17:26:43.031517Z",
-     "shell.execute_reply": "2026-08-28T17:26:43.031174Z"
+     "iopub.execute_input": "2026-09-15T01:38:29.417326Z",
+     "iopub.status.busy": "2026-09-15T01:38:29.417233Z",
+     "iopub.status.idle": "2026-09-15T01:38:29.419756Z",
+     "shell.execute_reply": "2026-09-15T01:38:29.419485Z"
     }
    },
    "outputs": [],
@@ -137,10 +137,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T17:26:43.032347Z",
-     "iopub.status.busy": "2026-08-28T17:26:43.032283Z",
-     "iopub.status.idle": "2026-08-28T17:26:43.033983Z",
-     "shell.execute_reply": "2026-08-28T17:26:43.033653Z"
+     "iopub.execute_input": "2026-09-15T01:38:29.420705Z",
+     "iopub.status.busy": "2026-09-15T01:38:29.420644Z",
+     "iopub.status.idle": "2026-09-15T01:38:29.422396Z",
+     "shell.execute_reply": "2026-09-15T01:38:29.422014Z"
     }
    },
    "outputs": [],
@@ -163,10 +163,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T17:26:43.034665Z",
-     "iopub.status.busy": "2026-08-28T17:26:43.034607Z",
-     "iopub.status.idle": "2026-08-28T18:40:01.896750Z",
-     "shell.execute_reply": "2026-08-28T18:40:01.894867Z"
+     "iopub.execute_input": "2026-09-15T01:38:29.423214Z",
+     "iopub.status.busy": "2026-09-15T01:38:29.423167Z",
+     "iopub.status.idle": "2026-09-15T04:50:20.319258Z",
+     "shell.execute_reply": "2026-09-15T04:50:20.318716Z"
     }
    },
    "outputs": [
@@ -183,15 +183,7 @@
      "output_type": "stream",
      "text": [
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-     ]
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-    {
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-     "output_type": "stream",
-     "text": [
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+      "100%|██████████| 50/50 [00:00<00:00, 1268.97it/s]"
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     {
@@ -214,7 +206,7 @@
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+      " 66%|██████▌   | 33/50 [00:00<00:00, 329.51it/s]"
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@@ -222,47 +214,7 @@
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+      "100%|██████████| 50/50 [00:00<00:00, 329.05it/s]"
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+      " 18%|█▊        | 9/50 [00:00<00:00, 88.81it/s]"
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      ]
     },
     {
@@ -3076,16 +2556,16 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T18:40:01.906277Z",
-     "iopub.status.busy": "2026-08-28T18:40:01.906162Z",
-     "iopub.status.idle": "2026-08-28T18:40:02.189694Z",
-     "shell.execute_reply": "2026-08-28T18:40:02.189323Z"
+     "iopub.execute_input": "2026-09-15T04:50:20.324396Z",
+     "iopub.status.busy": "2026-09-15T04:50:20.323844Z",
+     "iopub.status.idle": "2026-09-15T04:50:20.503492Z",
+     "shell.execute_reply": "2026-09-15T04:50:20.503100Z"
     }
    },
    "outputs": [
     {
      "data": {
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",
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",
       "text/plain": [
        "<Figure size 700x500 with 2 Axes>"
       ]
@@ -3095,7 +2575,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
diff --git a/examples/decoding/quantum_five_qubit.ipynb b/examples/decoding/quantum_five_qubit.ipynb
index 1d7f8d34..1c1f8be2 100644
--- a/examples/decoding/quantum_five_qubit.ipynb
+++ b/examples/decoding/quantum_five_qubit.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:51.908328Z",
-     "iopub.status.busy": "2026-08-30T17:41:51.908197Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.447212Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.446502Z"
+     "iopub.execute_input": "2026-09-15T04:50:23.798836Z",
+     "iopub.status.busy": "2026-09-15T04:50:23.798682Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.700523Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.700093Z"
     }
    },
    "outputs": [],
@@ -85,10 +85,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.448914Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.448661Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.451360Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.450787Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.701609Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.701500Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.703242Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.702901Z"
     }
    },
    "outputs": [],
@@ -121,10 +121,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.452533Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.452412Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.454559Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.454085Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.703963Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.703916Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.705549Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.705286Z"
     }
    },
    "outputs": [
@@ -160,10 +160,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.483945Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.483759Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.486884Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.486283Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.706290Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.706237Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.707837Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.707513Z"
     }
    },
    "outputs": [
@@ -194,10 +194,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.488289Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.488184Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.490571Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.489921Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.708758Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.708712Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.710328Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.710021Z"
     }
    },
    "outputs": [
@@ -224,10 +224,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.491731Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.491638Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.493960Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.493455Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.711058Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.711009Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.712571Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.712341Z"
     }
    },
    "outputs": [
@@ -261,10 +261,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.495213Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.495103Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.497171Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.496741Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.713279Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.713215Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.714803Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.714489Z"
     }
    },
    "outputs": [],
@@ -288,10 +288,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.498525Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.498423Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.500869Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.500392Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.715587Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.715543Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.717099Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.716858Z"
     }
    },
    "outputs": [],
@@ -316,10 +316,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.502250Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.502158Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.504280Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.503767Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.717791Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.717746Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.719253Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.718938Z"
     }
    },
    "outputs": [],
@@ -340,10 +340,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.505386Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.505299Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.508178Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.507543Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.719907Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.719865Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.721626Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.721342Z"
     }
    },
    "outputs": [],
@@ -362,10 +362,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.509252Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.509168Z",
-     "iopub.status.idle": "2026-08-30T17:41:54.592255Z",
-     "shell.execute_reply": "2026-08-30T17:41:54.591827Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.722364Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.722314Z",
+     "iopub.status.idle": "2026-09-15T04:50:24.747399Z",
+     "shell.execute_reply": "2026-09-15T04:50:24.747124Z"
     }
    },
    "outputs": [
@@ -382,7 +382,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 113.17it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 802.58it/s]"
      ]
     },
     {
@@ -405,7 +405,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 123.55it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 537.39it/s]"
      ]
     },
     {
@@ -428,7 +428,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 4/4 [00:00<00:00, 121.47it/s]"
+      "100%|██████████| 4/4 [00:00<00:00, 626.09it/s]"
      ]
     },
     {
@@ -484,16 +484,16 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:54.594001Z",
-     "iopub.status.busy": "2026-08-30T17:41:54.593856Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.491649Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.490386Z"
+     "iopub.execute_input": "2026-09-15T04:50:24.748329Z",
+     "iopub.status.busy": "2026-09-15T04:50:24.748263Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.143495Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.143051Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x280 with 4 Axes>"
       ]
@@ -549,10 +549,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.494495Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.494225Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.497797Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.496859Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.144884Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.144808Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.146331Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.146097Z"
     }
    },
    "outputs": [],
@@ -572,10 +572,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.499901Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.499760Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.502665Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.502035Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.147228Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.147179Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.148741Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.148453Z"
     }
    },
    "outputs": [
@@ -596,10 +596,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.504264Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.504130Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.581144Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.580261Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.149879Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.149831Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.163466Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.163125Z"
     }
    },
    "outputs": [
@@ -616,7 +616,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 8/8 [00:00<00:00, 111.79it/s]"
+      "100%|██████████| 8/8 [00:00<00:00, 708.09it/s]"
      ]
     },
     {
@@ -646,16 +646,16 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.583043Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.582887Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.906789Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.906059Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.164356Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.164304Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.291964Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.291561Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -694,10 +694,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.908754Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.908578Z",
-     "iopub.status.idle": "2026-08-30T17:41:55.912577Z",
-     "shell.execute_reply": "2026-08-30T17:41:55.911864Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.293064Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.293008Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.295066Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.294706Z"
     }
    },
    "outputs": [
@@ -728,10 +728,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:55.914103Z",
-     "iopub.status.busy": "2026-08-30T17:41:55.913973Z",
-     "iopub.status.idle": "2026-08-30T17:41:56.172800Z",
-     "shell.execute_reply": "2026-08-30T17:41:56.172200Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.295826Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.295776Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.325456Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.325150Z"
     }
    },
    "outputs": [
@@ -748,23 +748,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 38%|███▊      | 3/8 [00:00<00:00, 29.07it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      " 88%|████████▊ | 7/8 [00:00<00:00, 31.61it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "100%|██████████| 8/8 [00:00<00:00, 31.62it/s]"
+      "100%|██████████| 8/8 [00:00<00:00, 297.47it/s]"
      ]
     },
     {
@@ -825,16 +809,16 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:56.175029Z",
-     "iopub.status.busy": "2026-08-30T17:41:56.174848Z",
-     "iopub.status.idle": "2026-08-30T17:41:56.620566Z",
-     "shell.execute_reply": "2026-08-30T17:41:56.619872Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.326404Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.326349Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.506831Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.506428Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x280 with 2 Axes>"
       ]
@@ -876,10 +860,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:56.622332Z",
-     "iopub.status.busy": "2026-08-30T17:41:56.622178Z",
-     "iopub.status.idle": "2026-08-30T17:41:56.624555Z",
-     "shell.execute_reply": "2026-08-30T17:41:56.623986Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.507615Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.507562Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.509038Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.508739Z"
     }
    },
    "outputs": [],
@@ -899,10 +883,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:56.626218Z",
-     "iopub.status.busy": "2026-08-30T17:41:56.626076Z",
-     "iopub.status.idle": "2026-08-30T17:41:56.628846Z",
-     "shell.execute_reply": "2026-08-30T17:41:56.628163Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.509758Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.509709Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.511316Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.511004Z"
     }
    },
    "outputs": [],
@@ -917,10 +901,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:56.630276Z",
-     "iopub.status.busy": "2026-08-30T17:41:56.630127Z",
-     "iopub.status.idle": "2026-08-30T17:41:57.063027Z",
-     "shell.execute_reply": "2026-08-30T17:41:57.062348Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.512124Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.512062Z",
+     "iopub.status.idle": "2026-09-15T04:50:25.558963Z",
+     "shell.execute_reply": "2026-09-15T04:50:25.558653Z"
     }
    },
    "outputs": [
@@ -937,31 +921,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "4it [00:00, 32.21it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "8it [00:00, 33.53it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "12it [00:00, 34.75it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "15it [00:00, 34.97it/s]"
+      "15it [00:00, 335.85it/s]"
      ]
     },
     {
@@ -995,10 +955,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:41:57.064297Z",
-     "iopub.status.busy": "2026-08-30T17:41:57.064158Z",
-     "iopub.status.idle": "2026-08-30T17:42:00.590930Z",
-     "shell.execute_reply": "2026-08-30T17:42:00.590266Z"
+     "iopub.execute_input": "2026-09-15T04:50:25.559704Z",
+     "iopub.status.busy": "2026-09-15T04:50:25.559652Z",
+     "iopub.status.idle": "2026-09-15T04:50:26.040234Z",
+     "shell.execute_reply": "2026-09-15T04:50:26.039895Z"
     }
    },
    "outputs": [
@@ -1015,207 +975,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "4it [00:00, 31.50it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "8it [00:00, 29.26it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "11it [00:00, 28.68it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "14it [00:00, 27.97it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "17it [00:00, 27.70it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "21it [00:00, 28.32it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "24it [00:00, 28.03it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "27it [00:00, 27.56it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "30it [00:01, 26.92it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "33it [00:01, 25.84it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "36it [00:01, 24.26it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "39it [00:01, 23.95it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "42it [00:01, 24.09it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "45it [00:01, 23.45it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "48it [00:01, 23.54it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "51it [00:01, 23.42it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "54it [00:02, 24.22it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "57it [00:02, 24.50it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "60it [00:02, 25.01it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "63it [00:02, 25.78it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "66it [00:02, 26.39it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "69it [00:02, 26.85it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
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-      "\r",
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@@ -1223,7 +983,7 @@
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@@ -1830,7 +1070,7 @@
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@@ -1878,7 +1118,7 @@
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@@ -1902,7 +1142,7 @@
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@@ -1910,7 +1150,7 @@
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-      "263it [00:09, 26.80it/s]"
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@@ -1918,7 +1158,7 @@
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@@ -1926,7 +1166,7 @@
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@@ -1934,7 +1174,7 @@
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@@ -1969,10 +1209,10 @@
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    "metadata": {
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-     "shell.execute_reply": "2026-08-30T17:42:10.469214Z"
+     "iopub.execute_input": "2026-09-15T04:50:27.485735Z",
+     "iopub.status.busy": "2026-09-15T04:50:27.485679Z",
+     "iopub.status.idle": "2026-09-15T04:50:27.634352Z",
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@@ -2024,10 +1264,10 @@
    "execution_count": 26,
    "metadata": {
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-     "iopub.status.idle": "2026-08-30T17:42:10.475123Z",
-     "shell.execute_reply": "2026-08-30T17:42:10.474415Z"
+     "iopub.execute_input": "2026-09-15T04:50:27.635227Z",
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@@ -2040,10 +1280,10 @@
    "execution_count": 27,
    "metadata": {
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-     "shell.execute_reply": "2026-08-30T17:42:10.479019Z"
+     "iopub.execute_input": "2026-09-15T04:50:27.637345Z",
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@@ -2063,10 +1303,10 @@
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-     "iopub.status.idle": "2026-08-30T17:42:10.484793Z",
-     "shell.execute_reply": "2026-08-30T17:42:10.483983Z"
+     "iopub.execute_input": "2026-09-15T04:50:27.639548Z",
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@@ -2088,10 +1328,10 @@
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    "outputs": [],
diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 520505bf..a5be5f26 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
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-     "shell.execute_reply": "2026-09-10T15:43:05.759222Z"
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    "outputs": [],
@@ -88,10 +88,10 @@
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    "metadata": {
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-     "iopub.execute_input": "2026-08-30T18:29:48.155419Z",
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-     "shell.execute_reply": "2026-08-30T18:29:48.157499Z"
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@@ -142,10 +142,10 @@
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@@ -169,10 +169,10 @@
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@@ -197,10 +197,10 @@
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-     "shell.execute_reply": "2026-08-30T18:29:48.167612Z"
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@@ -247,10 +247,10 @@
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    "metadata": {
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-     "shell.execute_reply": "2026-08-30T18:29:48.170581Z"
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@@ -264,10 +264,10 @@
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-     "shell.execute_reply": "2026-08-30T18:29:48.174025Z"
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@@ -314,10 +314,10 @@
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-     "shell.execute_reply": "2026-08-30T18:29:48.177097Z"
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    "outputs": [
@@ -349,10 +349,10 @@
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    "metadata": {
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    "outputs": [
@@ -382,10 +382,10 @@
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-     "shell.execute_reply": "2026-08-30T18:29:48.183584Z"
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    "outputs": [
@@ -416,10 +416,10 @@
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@@ -438,10 +438,10 @@
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    "outputs": [
@@ -458,7 +458,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 70.55it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 436.91it/s]"
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@@ -481,7 +481,7 @@
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       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 64.56it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 430.10it/s]"
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     {
@@ -504,15 +504,7 @@
      "output_type": "stream",
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       "\r",
-      " 83%|████████▎ | 5/6 [00:00<00:00, 44.34it/s]"
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "100%|██████████| 6/6 [00:00<00:00, 42.18it/s]"
+      "100%|██████████| 6/6 [00:00<00:00, 168.85it/s]"
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@@ -535,7 +527,7 @@
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       "\r",
-      " 33%|███▎      | 2/6 [00:00<00:00,  4.69it/s]"
+      " 33%|███▎      | 2/6 [00:00<00:00,  8.72it/s]"
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@@ -543,7 +535,7 @@
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-      " 50%|█████     | 3/6 [00:01<00:01,  1.81it/s]"
+      " 50%|█████     | 3/6 [00:01<00:01,  2.01it/s]"
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     {
@@ -551,7 +543,7 @@
      "output_type": "stream",
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-      " 67%|██████▋   | 4/6 [00:03<00:02,  1.09s/it]"
+      " 67%|██████▋   | 4/6 [00:03<00:02,  1.13s/it]"
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@@ -559,7 +551,7 @@
      "output_type": "stream",
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       "\r",
-      " 83%|████████▎ | 5/6 [00:13<00:04,  4.19s/it]"
+      " 83%|████████▎ | 5/6 [00:12<00:04,  4.05s/it]"
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@@ -567,7 +559,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 6/6 [00:58<00:00, 17.63s/it]"
+      "100%|██████████| 6/6 [00:59<00:00, 18.06s/it]"
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@@ -575,7 +567,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 6/6 [00:58<00:00,  9.69s/it]"
+      "100%|██████████| 6/6 [00:59<00:00,  9.87s/it]"
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     {
@@ -632,10 +624,10 @@
    "execution_count": 13,
    "metadata": {
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-     "shell.execute_reply": "2026-08-30T18:30:47.148469Z"
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@@ -688,10 +680,10 @@
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-     "shell.execute_reply": "2026-08-30T18:30:47.151825Z"
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@@ -711,10 +703,10 @@
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@@ -735,10 +727,10 @@
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    "outputs": [
@@ -755,7 +747,7 @@
      "output_type": "stream",
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       "\r",
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+      "  9%|▉         | 1/11 [00:46<07:42, 46.20s/it]"
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@@ -763,7 +755,7 @@
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+      " 18%|█▊        | 2/11 [01:32<06:56, 46.28s/it]"
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@@ -771,7 +763,7 @@
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+      " 27%|██▋       | 3/11 [02:07<05:27, 40.93s/it]"
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@@ -779,7 +771,7 @@
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+      " 36%|███▋      | 4/11 [02:17<03:22, 28.90s/it]"
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@@ -787,7 +779,7 @@
      "output_type": "stream",
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       "\r",
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+      " 45%|████▌     | 5/11 [02:21<01:58, 19.75s/it]"
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@@ -795,7 +787,7 @@
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@@ -803,7 +795,7 @@
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+      " 64%|██████▎   | 7/11 [02:23<00:37,  9.33s/it]"
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@@ -811,7 +803,7 @@
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@@ -819,7 +811,7 @@
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@@ -827,7 +819,7 @@
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+      " 91%|█████████ | 10/11 [02:23<00:03,  3.19s/it]"
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@@ -835,7 +827,7 @@
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+      "100%|██████████| 11/11 [02:24<00:00,  2.27s/it]"
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+      "100%|██████████| 11/11 [02:24<00:00, 13.11s/it]"
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     {
@@ -873,16 +865,16 @@
    "execution_count": 17,
    "metadata": {
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-     "shell.execute_reply": "2026-08-30T18:33:22.237160Z"
+     "iopub.execute_input": "2026-09-15T04:53:55.181173Z",
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+     "shell.execute_reply": "2026-09-15T04:53:55.303648Z"
     }
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    "outputs": [
     {
      "data": {
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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -921,10 +913,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:33:22.239336Z",
-     "iopub.status.busy": "2026-08-30T18:33:22.239197Z",
-     "iopub.status.idle": "2026-08-30T18:33:22.250620Z",
-     "shell.execute_reply": "2026-08-30T18:33:22.250010Z"
+     "iopub.execute_input": "2026-09-15T04:53:55.304840Z",
+     "iopub.status.busy": "2026-09-15T04:53:55.304780Z",
+     "iopub.status.idle": "2026-09-15T04:53:55.313902Z",
+     "shell.execute_reply": "2026-09-15T04:53:55.313572Z"
     }
    },
    "outputs": [
@@ -957,10 +949,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:33:22.251804Z",
-     "iopub.status.busy": "2026-08-30T18:33:22.251702Z",
-     "iopub.status.idle": "2026-08-30T18:35:00.744335Z",
-     "shell.execute_reply": "2026-08-30T18:35:00.743892Z"
+     "iopub.execute_input": "2026-09-15T04:53:55.314676Z",
+     "iopub.status.busy": "2026-09-15T04:53:55.314626Z",
+     "iopub.status.idle": "2026-09-15T04:55:51.365617Z",
+     "shell.execute_reply": "2026-09-15T04:55:51.365326Z"
     }
    },
    "outputs": [
@@ -977,31 +969,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "  9%|▉         | 1/11 [00:31<05:13, 31.40s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      " 18%|█▊        | 2/11 [01:02<04:41, 31.28s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      " 27%|██▋       | 3/11 [01:24<03:36, 27.02s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      " 36%|███▋      | 4/11 [01:33<02:18, 19.81s/it]"
+      "  9%|▉         | 1/11 [00:37<06:13, 37.36s/it]"
      ]
     },
     {
@@ -1009,7 +977,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 45%|████▌     | 5/11 [01:36<01:22, 13.78s/it]"
+      " 18%|█▊        | 2/11 [01:14<05:35, 37.33s/it]"
      ]
     },
     {
@@ -1017,7 +985,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 55%|█████▍    | 6/11 [01:37<00:47,  9.47s/it]"
+      " 27%|██▋       | 3/11 [01:41<04:18, 32.31s/it]"
      ]
     },
     {
@@ -1025,7 +993,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 64%|██████▎   | 7/11 [01:37<00:26,  6.51s/it]"
+      " 36%|███▋      | 4/11 [01:51<02:47, 23.86s/it]"
      ]
     },
     {
@@ -1033,7 +1001,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 73%|███████▎  | 8/11 [01:38<00:13,  4.50s/it]"
+      " 45%|████▌     | 5/11 [01:55<01:38, 16.40s/it]"
      ]
     },
     {
@@ -1041,7 +1009,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 82%|████████▏ | 9/11 [01:38<00:06,  3.14s/it]"
+      " 55%|█████▍    | 6/11 [01:55<00:55, 11.07s/it]"
      ]
     },
     {
@@ -1049,7 +1017,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 91%|█████████ | 10/11 [01:38<00:02,  2.21s/it]"
+      " 64%|██████▎   | 7/11 [01:55<00:30,  7.50s/it]"
      ]
     },
     {
@@ -1057,15 +1025,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 11/11 [01:38<00:00,  1.57s/it]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "100%|██████████| 11/11 [01:38<00:00,  8.95s/it]"
+      "100%|██████████| 11/11 [01:56<00:00, 10.55s/it]"
      ]
     },
     {
@@ -1130,16 +1090,16 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:35:00.746112Z",
-     "iopub.status.busy": "2026-08-30T18:35:00.745924Z",
-     "iopub.status.idle": "2026-08-30T18:35:01.075704Z",
-     "shell.execute_reply": "2026-08-30T18:35:01.075059Z"
+     "iopub.execute_input": "2026-09-15T04:55:51.366621Z",
+     "iopub.status.busy": "2026-09-15T04:55:51.366561Z",
+     "iopub.status.idle": "2026-09-15T04:55:51.542368Z",
+     "shell.execute_reply": "2026-09-15T04:55:51.542108Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x280 with 2 Axes>"
       ]
@@ -1181,10 +1141,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:35:01.077321Z",
-     "iopub.status.busy": "2026-08-30T18:35:01.077193Z",
-     "iopub.status.idle": "2026-08-30T18:35:01.079837Z",
-     "shell.execute_reply": "2026-08-30T18:35:01.079253Z"
+     "iopub.execute_input": "2026-09-15T04:55:51.543295Z",
+     "iopub.status.busy": "2026-09-15T04:55:51.543237Z",
+     "iopub.status.idle": "2026-09-15T04:55:51.544700Z",
+     "shell.execute_reply": "2026-09-15T04:55:51.544427Z"
     }
    },
    "outputs": [],
@@ -1204,10 +1164,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:35:01.081708Z",
-     "iopub.status.busy": "2026-08-30T18:35:01.081554Z",
-     "iopub.status.idle": "2026-08-30T18:35:01.084724Z",
-     "shell.execute_reply": "2026-08-30T18:35:01.083938Z"
+     "iopub.execute_input": "2026-09-15T04:55:51.545398Z",
+     "iopub.status.busy": "2026-09-15T04:55:51.545352Z",
+     "iopub.status.idle": "2026-09-15T04:55:51.546978Z",
+     "shell.execute_reply": "2026-09-15T04:55:51.546753Z"
     }
    },
    "outputs": [],
@@ -1221,10 +1181,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:35:01.085946Z",
-     "iopub.status.busy": "2026-08-30T18:35:01.085851Z",
-     "iopub.status.idle": "2026-08-30T18:35:05.417507Z",
-     "shell.execute_reply": "2026-08-30T18:35:05.416874Z"
+     "iopub.execute_input": "2026-09-15T04:55:51.547766Z",
+     "iopub.status.busy": "2026-09-15T04:55:51.547694Z",
+     "iopub.status.idle": "2026-09-15T04:55:51.885265Z",
+     "shell.execute_reply": "2026-09-15T04:55:51.884928Z"
     }
    },
    "outputs": [
@@ -1241,231 +1201,7 @@
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-     ]
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-     ]
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-     "output_type": "stream",
-     "text": [
-      "\r",
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-     ]
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-     "output_type": "stream",
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-      "\r",
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-     ]
-    },
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-     "text": [
-      "\r",
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-     ]
-    },
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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-     ]
-    },
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-     "output_type": "stream",
-     "text": [
-      "\r",
-      " 77%|███████▋  | 30/39 [00:03<00:01,  8.78it/s]"
+      " 31%|███       | 12/39 [00:00<00:00, 116.97it/s]"
      ]
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     {
@@ -1473,7 +1209,7 @@
      "output_type": "stream",
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+      " 62%|██████▏   | 24/39 [00:00<00:00, 115.32it/s]"
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+      "100%|██████████| 39/39 [00:00<00:00, 116.30it/s]"
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     {
@@ -1575,10 +1255,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:35:05.419063Z",
-     "iopub.status.busy": "2026-08-30T18:35:05.418937Z",
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-     "shell.execute_reply": "2026-08-30T18:41:49.258632Z"
+     "iopub.execute_input": "2026-09-15T04:55:51.886101Z",
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+     "iopub.status.idle": "2026-09-15T05:06:07.427538Z",
+     "shell.execute_reply": "2026-09-15T05:06:07.427179Z"
     }
    },
    "outputs": [
@@ -1595,7 +1275,7 @@
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+      "  5%|▌         | 1/20 [00:19<06:12, 19.60s/it]"
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+      " 10%|█         | 2/20 [00:53<08:22, 27.93s/it]"
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+      " 15%|█▌        | 3/20 [01:29<08:57, 31.63s/it]"
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-      " 20%|██        | 4/20 [01:18<05:27, 20.44s/it]"
+      " 20%|██        | 4/20 [02:00<08:21, 31.37s/it]"
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+      " 30%|███       | 6/20 [02:51<06:38, 28.45s/it]"
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+      " 40%|████      | 8/20 [03:57<06:14, 31.20s/it]"
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+      " 45%|████▌     | 9/20 [04:33<05:58, 32.58s/it]"
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+      " 60%|██████    | 12/20 [06:18<04:37, 34.73s/it]"
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     {
@@ -1785,10 +1465,10 @@
    "execution_count": 25,
    "metadata": {
     "execution": {
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-     "shell.execute_reply": "2026-08-30T18:41:49.488320Z"
+     "iopub.execute_input": "2026-09-15T05:06:07.428500Z",
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    "outputs": [
@@ -1839,10 +1519,10 @@
    "execution_count": 26,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:41:49.490364Z",
-     "iopub.status.busy": "2026-08-30T18:41:49.490239Z",
-     "iopub.status.idle": "2026-08-30T18:41:49.492559Z",
-     "shell.execute_reply": "2026-08-30T18:41:49.491894Z"
+     "iopub.execute_input": "2026-09-15T05:06:07.541763Z",
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@@ -1862,10 +1542,10 @@
    "execution_count": 27,
    "metadata": {
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-     "iopub.execute_input": "2026-08-30T18:41:49.494070Z",
-     "iopub.status.busy": "2026-08-30T18:41:49.493923Z",
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-     "shell.execute_reply": "2026-08-30T18:41:49.495969Z"
+     "iopub.execute_input": "2026-09-15T05:06:07.543962Z",
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    "outputs": [
@@ -1911,10 +1591,10 @@
    "execution_count": 28,
    "metadata": {
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-     "iopub.execute_input": "2026-08-30T18:41:49.497528Z",
-     "iopub.status.busy": "2026-08-30T18:41:49.497434Z",
-     "iopub.status.idle": "2026-08-30T18:41:49.572973Z",
-     "shell.execute_reply": "2026-08-30T18:41:49.572430Z"
+     "iopub.execute_input": "2026-09-15T05:06:07.546855Z",
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    "outputs": [
@@ -1952,10 +1632,10 @@
    "execution_count": 29,
    "metadata": {
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-     "iopub.execute_input": "2026-08-30T18:41:49.574446Z",
-     "iopub.status.busy": "2026-08-30T18:41:49.574335Z",
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-     "shell.execute_reply": "2026-08-30T18:41:49.576569Z"
+     "iopub.execute_input": "2026-09-15T05:06:07.583845Z",
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    "outputs": [
@@ -1994,10 +1674,10 @@
    "execution_count": 30,
    "metadata": {
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-     "iopub.status.busy": "2026-08-30T18:41:49.578076Z",
-     "iopub.status.idle": "2026-08-30T18:41:49.826249Z",
-     "shell.execute_reply": "2026-08-30T18:41:49.825704Z"
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@@ -2069,10 +1749,10 @@
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    "metadata": {
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-     "shell.execute_reply": "2026-08-30T19:20:05.422592Z"
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+     "shell.execute_reply": "2026-09-15T05:38:03.655696Z"
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    "outputs": [
@@ -2096,7 +1776,7 @@
      "output_type": "stream",
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+      " 14%|█▍        | 1/7 [00:48<04:51, 48.62s/it]"
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+      " 29%|██▊       | 2/7 [03:09<08:33, 102.63s/it]"
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+      " 43%|████▎     | 3/7 [06:13<09:19, 139.86s/it]"
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@@ -2136,7 +1816,7 @@
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+      " 29%|██▊       | 2/7 [00:39<01:46, 21.28s/it]"
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+      " 43%|████▎     | 3/7 [01:17<01:55, 28.97s/it]"
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@@ -2222,7 +1902,7 @@
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+      " 43%|████▎     | 3/7 [00:22<00:34,  8.59s/it]"
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+      " 71%|███████▏  | 5/7 [00:53<00:25, 12.74s/it]"
      ]
     },
     {
@@ -2308,7 +1988,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 86%|████████▌ | 6/7 [02:51<00:34, 34.96s/it]"
+      " 86%|████████▌ | 6/7 [01:11<00:14, 14.59s/it]"
      ]
     },
     {
@@ -2316,7 +1996,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [03:38<00:00, 38.93s/it]"
+      "100%|██████████| 7/7 [01:30<00:00, 16.19s/it]"
      ]
     },
     {
@@ -2324,7 +2004,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [03:38<00:00, 31.19s/it]"
+      "100%|██████████| 7/7 [01:30<00:00, 12.98s/it]"
      ]
     },
     {
@@ -2354,7 +2034,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 14%|█▍        | 1/7 [00:04<00:28,  4.75s/it]"
+      " 14%|█▍        | 1/7 [00:01<00:07,  1.25s/it]"
      ]
     },
     {
@@ -2362,7 +2042,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 29%|██▊       | 2/7 [00:18<00:50, 10.14s/it]"
+      " 29%|██▊       | 2/7 [00:04<00:13,  2.60s/it]"
      ]
     },
     {
@@ -2370,7 +2050,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [00:36<00:55, 13.78s/it]"
+      " 43%|████▎     | 3/7 [00:09<00:14,  3.54s/it]"
      ]
     },
     {
@@ -2378,7 +2058,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 57%|█████▋    | 4/7 [00:58<00:51, 17.11s/it]"
+      " 57%|█████▋    | 4/7 [00:15<00:13,  4.41s/it]"
      ]
     },
     {
@@ -2386,7 +2066,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 71%|███████▏  | 5/7 [01:25<00:40, 20.34s/it]"
+      " 71%|███████▏  | 5/7 [00:21<00:10,  5.21s/it]"
      ]
     },
     {
@@ -2394,7 +2074,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 86%|████████▌ | 6/7 [01:53<00:23, 23.26s/it]"
+      " 86%|████████▌ | 6/7 [00:29<00:05,  5.96s/it]"
      ]
     },
     {
@@ -2402,7 +2082,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [02:25<00:00, 25.87s/it]"
+      "100%|██████████| 7/7 [00:37<00:00,  6.60s/it]"
      ]
     },
     {
@@ -2410,7 +2090,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [02:25<00:00, 20.75s/it]"
+      "100%|██████████| 7/7 [00:37<00:00,  5.31s/it]"
      ]
     },
     {
@@ -2440,7 +2120,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 14%|█▍        | 1/7 [00:04<00:25,  4.22s/it]"
+      " 14%|█▍        | 1/7 [00:00<00:04,  1.35it/s]"
      ]
     },
     {
@@ -2448,7 +2128,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 29%|██▊       | 2/7 [00:16<00:44,  8.82s/it]"
+      " 29%|██▊       | 2/7 [00:02<00:07,  1.54s/it]"
      ]
     },
     {
@@ -2456,7 +2136,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [00:32<00:48, 12.01s/it]"
+      " 43%|████▎     | 3/7 [00:05<00:08,  2.10s/it]"
      ]
     },
     {
@@ -2464,7 +2144,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 57%|█████▋    | 4/7 [00:51<00:44, 14.98s/it]"
+      " 57%|█████▋    | 4/7 [00:08<00:07,  2.61s/it]"
      ]
     },
     {
@@ -2472,7 +2152,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 71%|███████▏  | 5/7 [01:14<00:35, 17.77s/it]"
+      " 71%|███████▏  | 5/7 [00:12<00:06,  3.08s/it]"
      ]
     },
     {
@@ -2480,7 +2160,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 86%|████████▌ | 6/7 [01:39<00:20, 20.27s/it]"
+      " 86%|████████▌ | 6/7 [00:17<00:03,  3.53s/it]"
      ]
     },
     {
@@ -2488,7 +2168,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [02:06<00:00, 22.51s/it]"
+      "100%|██████████| 7/7 [00:22<00:00,  3.91s/it]"
      ]
     },
     {
@@ -2496,7 +2176,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [02:06<00:00, 18.08s/it]"
+      "100%|██████████| 7/7 [00:22<00:00,  3.14s/it]"
      ]
     },
     {
@@ -2565,10 +2245,10 @@
    "execution_count": 32,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T19:20:05.423881Z",
-     "iopub.status.busy": "2026-08-30T19:20:05.423826Z",
-     "iopub.status.idle": "2026-08-30T19:20:05.429614Z",
-     "shell.execute_reply": "2026-08-30T19:20:05.429274Z"
+     "iopub.execute_input": "2026-09-15T05:38:03.657011Z",
+     "iopub.status.busy": "2026-09-15T05:38:03.656955Z",
+     "iopub.status.idle": "2026-09-15T05:38:03.662162Z",
+     "shell.execute_reply": "2026-09-15T05:38:03.661822Z"
     }
    },
    "outputs": [],
@@ -2591,16 +2271,16 @@
    "execution_count": 33,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T19:20:05.430443Z",
-     "iopub.status.busy": "2026-08-30T19:20:05.430386Z",
-     "iopub.status.idle": "2026-08-30T19:20:05.590948Z",
-     "shell.execute_reply": "2026-08-30T19:20:05.590609Z"
+     "iopub.execute_input": "2026-09-15T05:38:03.663056Z",
+     "iopub.status.busy": "2026-09-15T05:38:03.663002Z",
+     "iopub.status.idle": "2026-09-15T05:38:03.808819Z",
+     "shell.execute_reply": "2026-09-15T05:38:03.808527Z"
     }
    },
    "outputs": [
     {
      "data": {
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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -2660,13 +2340,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 34,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-10T15:43:05.760698Z",
-     "iopub.status.busy": "2026-09-10T15:43:05.760590Z",
-     "iopub.status.idle": "2026-09-11T02:24:44.708755Z",
-     "shell.execute_reply": "2026-09-11T02:24:44.708216Z"
+     "iopub.execute_input": "2026-09-15T05:38:03.809776Z",
+     "iopub.status.busy": "2026-09-15T05:38:03.809719Z",
+     "iopub.status.idle": "2026-09-15T10:22:26.179236Z",
+     "shell.execute_reply": "2026-09-15T10:22:26.178767Z"
     }
    },
    "outputs": [
@@ -2683,7 +2363,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  12%|█▎        | 1/8 [00:57<06:39, 57.05s/it]"
+      "L=3, chi=64:  12%|█▎        | 1/8 [00:29<03:28, 29.79s/it]"
      ]
     },
     {
@@ -2691,7 +2371,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  25%|██▌       | 2/8 [02:02<06:12, 62.09s/it]"
+      "L=3, chi=64:  25%|██▌       | 2/8 [01:02<03:09, 31.66s/it]"
      ]
     },
     {
@@ -2699,7 +2379,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  38%|███▊      | 3/8 [03:11<05:25, 65.02s/it]"
+      "L=3, chi=64:  38%|███▊      | 3/8 [01:35<02:41, 32.30s/it]"
      ]
     },
     {
@@ -2707,7 +2387,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  50%|█████     | 4/8 [04:24<04:33, 68.36s/it]"
+      "L=3, chi=64:  50%|█████     | 4/8 [02:09<02:10, 32.69s/it]"
      ]
     },
     {
@@ -2715,7 +2395,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  62%|██████▎   | 5/8 [05:50<03:43, 74.56s/it]"
+      "L=3, chi=64:  62%|██████▎   | 5/8 [02:43<01:39, 33.26s/it]"
      ]
     },
     {
@@ -2723,7 +2403,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  75%|███████▌  | 6/8 [07:15<02:36, 78.07s/it]"
+      "L=3, chi=64:  75%|███████▌  | 6/8 [03:17<01:07, 33.59s/it]"
      ]
     },
     {
@@ -2731,7 +2411,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  88%|████████▊ | 7/8 [08:44<01:21, 81.66s/it]"
+      "L=3, chi=64:  88%|████████▊ | 7/8 [03:54<00:34, 34.53s/it]"
      ]
     },
     {
@@ -2739,7 +2419,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [10:15<00:00, 84.66s/it]"
+      "L=3, chi=64: 100%|██████████| 8/8 [04:31<00:00, 35.54s/it]"
      ]
     },
     {
@@ -2747,7 +2427,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [10:15<00:00, 76.90s/it]"
+      "L=3, chi=64: 100%|██████████| 8/8 [04:31<00:00, 33.97s/it]"
      ]
     },
     {
@@ -2770,7 +2450,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  12%|█▎        | 1/8 [16:20<1:54:23, 980.46s/it]"
+      "L=5, chi=64:  12%|█▎        | 1/8 [07:20<51:20, 440.05s/it]"
      ]
     },
     {
@@ -2778,7 +2458,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  25%|██▌       | 2/8 [34:50<1:45:40, 1056.76s/it]"
+      "L=5, chi=64:  25%|██▌       | 2/8 [14:46<44:22, 443.74s/it]"
      ]
     },
     {
@@ -2786,7 +2466,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  38%|███▊      | 3/8 [52:16<1:27:39, 1051.91s/it]"
+      "L=5, chi=64:  38%|███▊      | 3/8 [22:12<37:04, 444.96s/it]"
      ]
     },
     {
@@ -2794,7 +2474,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  50%|█████     | 4/8 [1:10:43<1:11:34, 1073.74s/it]"
+      "L=5, chi=64:  50%|█████     | 4/8 [29:44<29:50, 447.68s/it]"
      ]
     },
     {
@@ -2802,7 +2482,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  62%|██████▎   | 5/8 [1:28:43<53:47, 1075.94s/it]  "
+      "L=5, chi=64:  62%|██████▎   | 5/8 [37:14<22:25, 448.45s/it]"
      ]
     },
     {
@@ -2810,7 +2490,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  75%|███████▌  | 6/8 [1:45:56<35:22, 1061.36s/it]"
+      "L=5, chi=64:  75%|███████▌  | 6/8 [44:45<14:58, 449.35s/it]"
      ]
     },
     {
@@ -2818,7 +2498,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  88%|████████▊ | 7/8 [2:04:12<17:52, 1072.60s/it]"
+      "L=5, chi=64:  88%|████████▊ | 7/8 [52:20<07:31, 451.12s/it]"
      ]
     },
     {
@@ -2826,7 +2506,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [2:23:11<00:00, 1093.71s/it]"
+      "L=5, chi=64: 100%|██████████| 8/8 [59:58<00:00, 453.40s/it]"
      ]
     },
     {
@@ -2834,7 +2514,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [2:23:11<00:00, 1073.94s/it]"
+      "L=5, chi=64: 100%|██████████| 8/8 [59:58<00:00, 449.82s/it]"
      ]
     },
     {
@@ -2857,7 +2537,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  12%|█▎        | 1/8 [1:04:49<7:33:43, 3889.13s/it]"
+      "L=7, chi=64:  12%|█▎        | 1/8 [27:30<3:12:33, 1650.55s/it]"
      ]
     },
     {
@@ -2865,7 +2545,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  25%|██▌       | 2/8 [2:10:10<6:30:49, 3908.29s/it]"
+      "L=7, chi=64:  25%|██▌       | 2/8 [54:59<2:44:58, 1649.81s/it]"
      ]
     },
     {
@@ -2873,7 +2553,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  38%|███▊      | 3/8 [3:15:34<5:26:16, 3915.40s/it]"
+      "L=7, chi=64:  38%|███▊      | 3/8 [1:22:24<2:17:18, 1647.64s/it]"
      ]
     },
     {
@@ -2881,7 +2561,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  50%|█████     | 4/8 [4:13:56<4:10:08, 3752.18s/it]"
+      "L=7, chi=64:  50%|█████     | 4/8 [1:49:51<1:49:48, 1647.12s/it]"
      ]
     },
     {
@@ -2889,7 +2569,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  62%|██████▎   | 5/8 [5:12:39<3:03:28, 3669.62s/it]"
+      "L=7, chi=64:  62%|██████▎   | 5/8 [2:17:18<1:22:21, 1647.01s/it]"
      ]
     },
     {
@@ -2897,7 +2577,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  75%|███████▌  | 6/8 [6:11:21<2:00:38, 3619.46s/it]"
+      "L=7, chi=64:  75%|███████▌  | 6/8 [2:44:43<54:53, 1646.51s/it]  "
      ]
     },
     {
@@ -2905,7 +2585,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  88%|████████▊ | 7/8 [7:09:42<59:40, 3580.60s/it]  "
+      "L=7, chi=64:  88%|████████▊ | 7/8 [3:12:11<27:26, 1646.84s/it]"
      ]
     },
     {
@@ -2913,7 +2593,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [8:08:11<00:00, 3557.70s/it]"
+      "L=7, chi=64: 100%|██████████| 8/8 [3:39:51<00:00, 1651.01s/it]"
      ]
     },
     {
@@ -2921,7 +2601,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [8:08:11<00:00, 3661.41s/it]"
+      "L=7, chi=64: 100%|██████████| 8/8 [3:39:51<00:00, 1648.88s/it]"
      ]
     },
     {
@@ -3022,13 +2702,13 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 35,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-11T02:24:44.711917Z",
-     "iopub.status.busy": "2026-09-11T02:24:44.711795Z",
-     "iopub.status.idle": "2026-09-11T02:24:44.719401Z",
-     "shell.execute_reply": "2026-09-11T02:24:44.719057Z"
+     "iopub.execute_input": "2026-09-15T10:22:26.180407Z",
+     "iopub.status.busy": "2026-09-15T10:22:26.180305Z",
+     "iopub.status.idle": "2026-09-15T10:22:26.189519Z",
+     "shell.execute_reply": "2026-09-15T10:22:26.189171Z"
     }
    },
    "outputs": [
@@ -3039,12 +2719,11 @@
       "logical error rate (standard error) per lattice size and rate\n",
       "p                 0.080           0.090           0.095           0.100           0.105           0.110           0.120           0.130\n",
       "L=3       0.1053(0.0056)   0.1233(0.0060)   0.1203(0.0059)   0.1360(0.0063)   0.1483(0.0065)   0.1457(0.0064)   0.1840(0.0071)   0.2133(0.0075)\n",
-      "L=5       0.0877(0.0052)   0.1083(0.0057)   0.1250(0.0060)   0.1377(0.0063)   0.1483(0.0065)   0.1580(0.0067)   0.2113(0.0075)   0.2377(0.0078)\n",
-      "L=7       0.0717(0.0047)   0.1107(0.0057)   0.1240(0.0060)   0.1400(0.0063)   0.1540(0.0066)   0.1910(0.0072)   0.2270(0.0076)   0.2807(0.0082)\n",
-      "L=3 and L=5: fitted crossing p = 0.0988 +/- 0.0033 (slope 0.956); sign changes of the gap on the grid: 0.0938, 0.1050\n",
-      "  -> no unique crossing on the grid; only the fit is reported\n",
-      "L=5 and L=7: fitted crossing p = 0.0937 +/- 0.0032 (slope 1.059); sign changes of the gap on the grid: 0.0887, 0.0935, 0.0965\n",
+      "L=5       0.0870(0.0051)   0.1083(0.0057)   0.1243(0.0060)   0.1383(0.0063)   0.1473(0.0065)   0.1570(0.0066)   0.2123(0.0075)   0.2367(0.0078)\n",
+      "L=7       0.0707(0.0047)   0.1107(0.0057)   0.1247(0.0060)   0.1383(0.0063)   0.1523(0.0066)   0.1890(0.0071)   0.2283(0.0077)   0.2783(0.0082)\n",
+      "L=3 and L=5: fitted crossing p = 0.0992 +/- 0.0030 (slope 0.961); sign changes of the gap on the grid: 0.0939, 0.1035, 0.1054; exact ties at: none\n",
       "  -> no unique crossing on the grid; only the fit is reported\n",
+      "L=5 and L=7: fitted crossing p = 0.0940 +/- 0.0030 (slope 1.044); sign changes of the gap on the grid: 0.0887; exact ties at: 0.100\n",
       "Every shot decoded; no failure was counted from a raised decode.\n"
      ]
     }
@@ -3147,19 +2826,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 36,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-11T02:24:44.720273Z",
-     "iopub.status.busy": "2026-09-11T02:24:44.720222Z",
-     "iopub.status.idle": "2026-09-11T02:24:45.147221Z",
-     "shell.execute_reply": "2026-09-11T02:24:45.146873Z"
+     "iopub.execute_input": "2026-09-15T10:22:26.190328Z",
+     "iopub.status.busy": "2026-09-15T10:22:26.190273Z",
+     "iopub.status.idle": "2026-09-15T10:22:26.367379Z",
+     "shell.execute_reply": "2026-09-15T10:22:26.367022Z"
     }
    },
    "outputs": [
     {
      "data": {
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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
diff --git a/examples/decoding/quantum_three_qubit.ipynb b/examples/decoding/quantum_three_qubit.ipynb
index 5b811a5d..bc30f29b 100644
--- a/examples/decoding/quantum_three_qubit.ipynb
+++ b/examples/decoding/quantum_three_qubit.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:13.972928Z",
-     "iopub.status.busy": "2026-08-30T17:42:13.972772Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.361779Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.361158Z"
+     "iopub.execute_input": "2026-09-15T10:22:29.643453Z",
+     "iopub.status.busy": "2026-09-15T10:22:29.643307Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.272656Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.272168Z"
     }
    },
    "outputs": [],
@@ -92,10 +92,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.364349Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.364050Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.367126Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.366411Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.273756Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.273647Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.275372Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.275098Z"
     }
    },
    "outputs": [],
@@ -126,10 +126,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.368727Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.368590Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.371795Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.370894Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.276213Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.276153Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.277814Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.277487Z"
     }
    },
    "outputs": [
@@ -163,10 +163,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.373660Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.373531Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.377071Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.376161Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.278612Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.278564Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.279993Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.279736Z"
     }
    },
    "outputs": [
@@ -195,10 +195,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.378675Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.378513Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.381484Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.380798Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.280726Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.280673Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.282256Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.281950Z"
     }
    },
    "outputs": [
@@ -225,10 +225,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.383067Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.382947Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.385391Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.384795Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.282995Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.282950Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.284499Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.284226Z"
     }
    },
    "outputs": [
@@ -262,10 +262,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.387011Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.386742Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.389270Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.388650Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.285271Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.285228Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.286664Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.286433Z"
     }
    },
    "outputs": [],
@@ -289,10 +289,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.390621Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.390485Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.393376Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.392739Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.287516Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.287467Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.289029Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.288796Z"
     }
    },
    "outputs": [],
@@ -317,10 +317,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.394960Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.394831Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.397202Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.396663Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.289814Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.289772Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.291258Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.290918Z"
     }
    },
    "outputs": [],
@@ -341,10 +341,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.399065Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.398932Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.401795Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.401365Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.291923Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.291877Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.293511Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.293269Z"
     }
    },
    "outputs": [],
@@ -363,10 +363,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.403589Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.403453Z",
-     "iopub.status.idle": "2026-08-30T17:42:16.466261Z",
-     "shell.execute_reply": "2026-08-30T17:42:16.465576Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.294259Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.294199Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.315136Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.314819Z"
     }
    },
    "outputs": [
@@ -383,7 +383,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 113.64it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 633.68it/s]"
      ]
     },
     {
@@ -406,7 +406,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 130.23it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 923.45it/s]"
      ]
     },
     {
@@ -429,7 +429,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 2/2 [00:00<00:00, 186.85it/s]"
+      "100%|██████████| 2/2 [00:00<00:00, 1072.44it/s]"
      ]
     },
     {
@@ -485,16 +485,16 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:16.470660Z",
-     "iopub.status.busy": "2026-08-30T17:42:16.470497Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.323567Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.323032Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.316151Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.316084Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.666467Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.666089Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 700x280 with 4 Axes>"
       ]
@@ -550,10 +550,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.325613Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.325474Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.328338Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.327515Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.667518Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.667460Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.669019Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.668757Z"
     }
    },
    "outputs": [],
@@ -573,10 +573,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.330156Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.330009Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.332865Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.332228Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.669805Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.669745Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.671135Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.670804Z"
     }
    },
    "outputs": [
@@ -597,10 +597,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.334392Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.334260Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.355571Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.354969Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.671986Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.671941Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.676804Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.676538Z"
     }
    },
    "outputs": [
@@ -617,7 +617,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 4/4 [00:00<00:00, 233.81it/s]"
+      "100%|██████████| 4/4 [00:00<00:00, 1527.42it/s]"
      ]
     },
     {
@@ -647,16 +647,16 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.357260Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.357115Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.695562Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.694550Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.677658Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.677608Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.798188Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.797847Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]
@@ -695,10 +695,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.697252Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.697134Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.699722Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.699165Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.799483Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.799428Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.801182Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.800874Z"
     }
    },
    "outputs": [],
@@ -714,10 +714,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.701442Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.701304Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.704334Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.703777Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.801959Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.801907Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.803634Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.803295Z"
     }
    },
    "outputs": [
@@ -746,10 +746,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.705907Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.705783Z",
-     "iopub.status.idle": "2026-08-30T17:42:17.760525Z",
-     "shell.execute_reply": "2026-08-30T17:42:17.759450Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.804395Z",
+     "iopub.status.busy": "2026-09-15T10:22:30.804346Z",
+     "iopub.status.idle": "2026-09-15T10:22:30.812659Z",
+     "shell.execute_reply": "2026-09-15T10:22:30.812369Z"
     }
    },
    "outputs": [
@@ -766,7 +766,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      "100%|██████████| 4/4 [00:00<00:00, 722.53it/s]"
      ]
     },
     {
@@ -830,10 +830,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:17.762389Z",
-     "iopub.status.busy": "2026-08-30T17:42:17.762230Z",
-     "iopub.status.idle": "2026-08-30T17:42:18.181631Z",
-     "shell.execute_reply": "2026-08-30T17:42:18.180775Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.813468Z",
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+     "shell.execute_reply": "2026-09-15T10:22:30.983787Z"
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    "outputs": [
@@ -881,10 +881,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:18.183634Z",
-     "iopub.status.busy": "2026-08-30T17:42:18.183495Z",
-     "iopub.status.idle": "2026-08-30T17:42:18.185638Z",
-     "shell.execute_reply": "2026-08-30T17:42:18.185090Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.985115Z",
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    "outputs": [],
@@ -904,10 +904,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T17:42:18.187401Z",
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-     "shell.execute_reply": "2026-08-30T18:27:03.907133Z"
+     "iopub.execute_input": "2026-09-15T10:22:30.987392Z",
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+     "iopub.status.idle": "2026-09-15T10:27:01.658565Z",
+     "shell.execute_reply": "2026-09-15T10:27:01.658139Z"
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    "outputs": [
@@ -931,7 +931,7 @@
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+      "  5%|▌         | 1/19 [00:00<00:04,  4.30it/s]"
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+      " 11%|█         | 2/19 [00:00<00:09,  1.89it/s]"
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+      " 16%|█▌        | 3/19 [00:02<00:13,  1.23it/s]"
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-      " 21%|██        | 4/19 [00:41<03:09, 12.65s/it]"
+      " 21%|██        | 4/19 [00:03<00:16,  1.11s/it]"
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+      " 26%|██▋       | 5/19 [00:05<00:19,  1.42s/it]"
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+      " 37%|███▋      | 7/19 [00:10<00:24,  2.04s/it]"
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+      " 42%|████▏     | 8/19 [00:13<00:25,  2.35s/it]"
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+      " 21%|██        | 4/19 [00:03<00:17,  1.16s/it]"
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-      " 11%|█         | 2/19 [00:08<01:21,  4.78s/it]"
+      " 11%|█         | 2/19 [00:00<00:09,  1.88it/s]"
      ]
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     {
@@ -1493,7 +1493,7 @@
      "output_type": "stream",
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+      " 16%|█▌        | 3/19 [00:02<00:13,  1.21it/s]"
      ]
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@@ -1501,7 +1501,7 @@
      "output_type": "stream",
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-      " 21%|██        | 4/19 [00:34<02:36, 10.42s/it]"
+      " 21%|██        | 4/19 [00:03<00:16,  1.13s/it]"
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@@ -1509,7 +1509,7 @@
      "output_type": "stream",
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+      " 26%|██▋       | 5/19 [00:05<00:20,  1.45s/it]"
      ]
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@@ -1517,7 +1517,7 @@
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+      " 32%|███▏      | 6/19 [00:08<00:22,  1.75s/it]"
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@@ -1525,7 +1525,7 @@
      "output_type": "stream",
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+      " 37%|███▋      | 7/19 [00:10<00:24,  2.08s/it]"
      ]
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@@ -1533,7 +1533,7 @@
      "output_type": "stream",
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+      " 42%|████▏     | 8/19 [00:13<00:26,  2.39s/it]"
      ]
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     {
@@ -1541,7 +1541,7 @@
      "output_type": "stream",
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+      " 47%|████▋     | 9/19 [00:17<00:27,  2.71s/it]"
      ]
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@@ -1549,7 +1549,7 @@
      "output_type": "stream",
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+      " 53%|█████▎    | 10/19 [00:21<00:27,  3.04s/it]"
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@@ -1557,7 +1557,7 @@
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+      " 58%|█████▊    | 11/19 [00:25<00:26,  3.36s/it]"
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@@ -1565,7 +1565,7 @@
      "output_type": "stream",
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+      " 63%|██████▎   | 12/19 [00:29<00:25,  3.65s/it]"
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@@ -1573,7 +1573,7 @@
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+      " 68%|██████▊   | 13/19 [00:34<00:23,  3.96s/it]"
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@@ -1581,7 +1581,7 @@
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+      " 74%|███████▎  | 14/19 [00:38<00:21,  4.22s/it]"
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@@ -1589,7 +1589,7 @@
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+      " 79%|███████▉  | 15/19 [00:44<00:17,  4.50s/it]"
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@@ -1597,7 +1597,7 @@
      "output_type": "stream",
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+      " 84%|████████▍ | 16/19 [00:49<00:14,  4.74s/it]"
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     {
@@ -1605,7 +1605,7 @@
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+      " 89%|████████▉ | 17/19 [00:54<00:09,  4.98s/it]"
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@@ -1613,7 +1613,7 @@
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+      " 95%|█████████▍| 18/19 [01:00<00:05,  5.19s/it]"
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@@ -1621,7 +1621,7 @@
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+      "100%|██████████| 19/19 [01:06<00:00,  5.40s/it]"
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     {
@@ -1629,7 +1629,7 @@
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+      "100%|██████████| 19/19 [01:06<00:00,  3.50s/it]"
      ]
     },
     {
@@ -1697,10 +1697,10 @@
    "execution_count": 23,
    "metadata": {
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@@ -1721,10 +1721,10 @@
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     }
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    "outputs": [
diff --git a/examples/decoding/shor.ipynb b/examples/decoding/shor.ipynb
index 10ad6f90..e8e68ede 100644
--- a/examples/decoding/shor.ipynb
+++ b/examples/decoding/shor.ipynb
@@ -20,10 +20,10 @@
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@@ -74,10 +74,10 @@
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    "outputs": [
@@ -123,10 +123,10 @@
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@@ -151,10 +151,10 @@
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@@ -178,10 +178,10 @@
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@@ -225,10 +225,10 @@
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@@ -242,10 +242,10 @@
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@@ -289,10 +289,10 @@
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@@ -325,10 +325,10 @@
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@@ -359,10 +359,10 @@
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@@ -403,10 +403,10 @@
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@@ -424,10 +424,10 @@
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    "outputs": [
@@ -444,7 +444,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 2/2 [00:00<00:00, 130.52it/s]"
+      "100%|██████████| 2/2 [00:00<00:00, 1188.36it/s]"
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     {
@@ -467,7 +467,7 @@
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       "\r",
-      "100%|██████████| 6/6 [00:00<00:00, 537.69it/s]"
+      "100%|██████████| 6/6 [00:00<00:00, 3014.59it/s]"
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     {
@@ -490,7 +490,7 @@
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+      "100%|██████████| 1/1 [00:00<00:00, 721.04it/s]"
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     {
@@ -513,7 +513,7 @@
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       "\r",
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+      "100%|██████████| 1/1 [00:00<00:00, 870.19it/s]"
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     {
@@ -556,10 +556,10 @@
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@@ -608,10 +608,10 @@
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@@ -626,10 +626,10 @@
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@@ -646,47 +646,7 @@
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@@ -717,10 +677,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
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-     "iopub.status.idle": "2026-08-30T18:27:18.196319Z",
-     "shell.execute_reply": "2026-08-30T18:27:18.195645Z"
+     "iopub.execute_input": "2026-09-15T10:27:05.640166Z",
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+     "shell.execute_reply": "2026-09-15T10:27:06.438767Z"
     }
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    "outputs": [
@@ -737,223 +697,7 @@
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-      "\r",
-      "125it [00:03, 42.95it/s]"
+      "41it [00:00, 400.88it/s]"
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@@ -961,7 +705,7 @@
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      "text": [
       "\r",
-      "130it [00:03, 44.18it/s]"
+      "82it [00:00, 403.00it/s]"
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@@ -969,7 +713,7 @@
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       "\r",
-      "135it [00:03, 44.86it/s]"
+      "123it [00:00, 403.32it/s]"
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@@ -977,7 +721,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "140it [00:03, 45.60it/s]"
+      "164it [00:00, 405.85it/s]"
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@@ -985,7 +729,7 @@
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      "text": [
       "\r",
-      "145it [00:03, 46.12it/s]"
+      "205it [00:00, 403.35it/s]"
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@@ -993,7 +737,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "150it [00:03, 46.43it/s]"
+      "247it [00:00, 405.82it/s]"
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     {
@@ -1001,7 +745,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "155it [00:03, 46.34it/s]"
+      "289it [00:00, 407.85it/s]"
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@@ -1009,308 +753,44 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "160it [00:03, 46.62it/s]"
+      "324it [00:00, 406.73it/s]"
      ]
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     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "\r",
-      "165it [00:04, 46.76it/s]"
+      "\n"
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-     "name": "stderr",
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-     "text": [
-      "\r",
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-     "name": "stderr",
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-     "text": [
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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-     ]
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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-     ]
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "300it [00:07, 41.83it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "305it [00:07, 42.40it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "310it [00:07, 43.18it/s]"
-     ]
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "315it [00:07, 43.38it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "320it [00:07, 43.35it/s]"
-     ]
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-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
-      "324it [00:07, 41.33it/s]"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
-   "source": [
-    "two_qubit_outputs = [\n",
-    "    decode_css(\n",
-    "        code,\n",
-    "        error,\n",
-    "        bias_type=\"Bitflip\",\n",
-    "        renormalise=renormalise,\n",
-    "        silent=True,\n",
-    "        bias_prob=1e-2,\n",
-    "    )\n",
-    "    for error in tqdm(two_qubit_paulis)\n",
-    "]\n",
-    "two_qubit_corrections_distribution = [output[0] for output in two_qubit_outputs]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 17,
-   "metadata": {
-    "execution": {
-     "iopub.execute_input": "2026-08-30T18:27:18.197891Z",
-     "iopub.status.busy": "2026-08-30T18:27:18.197768Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.389867Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.389428Z"
-    }
-   },
-   "outputs": [
+    }
+   ],
+   "source": [
+    "two_qubit_outputs = [\n",
+    "    decode_css(\n",
+    "        code,\n",
+    "        error,\n",
+    "        bias_type=\"Bitflip\",\n",
+    "        renormalise=renormalise,\n",
+    "        silent=True,\n",
+    "        bias_prob=1e-2,\n",
+    "    )\n",
+    "    for error in tqdm(two_qubit_paulis)\n",
+    "]\n",
+    "two_qubit_corrections_distribution = [output[0] for output in two_qubit_outputs]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {
+    "execution": {
+     "iopub.execute_input": "2026-09-15T10:27:06.440038Z",
+     "iopub.status.busy": "2026-09-15T10:27:06.439980Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.057696Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.057427Z"
+    }
+   },
+   "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
@@ -1324,3607 +804,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "4it [00:00, 39.37it/s]"
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-      "9it [00:00, 41.67it/s]"
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-      "\r",
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-      "\r",
-      "19it [00:00, 41.27it/s]"
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-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\r",
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-      "\r",
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-      "\r",
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-      "\r",
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-      "\r",
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@@ -5148,7 +1028,7 @@
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      "text": [
       "\r",
-      "2156it [00:55, 39.17it/s]"
+      "1189it [00:02, 402.04it/s]"
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@@ -5156,7 +1036,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2160it [00:55, 38.88it/s]"
+      "1230it [00:03, 402.75it/s]"
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     {
@@ -5164,7 +1044,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2164it [00:55, 39.01it/s]"
+      "1271it [00:03, 404.33it/s]"
      ]
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     {
@@ -5172,7 +1052,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2169it [00:55, 39.41it/s]"
+      "1312it [00:03, 405.86it/s]"
      ]
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     {
@@ -5180,7 +1060,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2173it [00:55, 39.56it/s]"
+      "1353it [00:03, 405.80it/s]"
      ]
     },
     {
@@ -5188,7 +1068,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2177it [00:55, 39.24it/s]"
+      "1394it [00:03, 404.90it/s]"
      ]
     },
     {
@@ -5196,7 +1076,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2181it [00:55, 38.98it/s]"
+      "1435it [00:03, 405.10it/s]"
      ]
     },
     {
@@ -5204,7 +1084,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2185it [00:56, 39.24it/s]"
+      "1476it [00:03, 405.07it/s]"
      ]
     },
     {
@@ -5212,7 +1092,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2190it [00:56, 39.56it/s]"
+      "1517it [00:03, 403.93it/s]"
      ]
     },
     {
@@ -5220,7 +1100,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2195it [00:56, 39.74it/s]"
+      "1558it [00:03, 404.46it/s]"
      ]
     },
     {
@@ -5228,7 +1108,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2199it [00:56, 39.06it/s]"
+      "1599it [00:03, 399.23it/s]"
      ]
     },
     {
@@ -5236,7 +1116,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2203it [00:56, 38.84it/s]"
+      "1640it [00:04, 402.00it/s]"
      ]
     },
     {
@@ -5244,7 +1124,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2208it [00:56, 39.06it/s]"
+      "1681it [00:04, 403.67it/s]"
      ]
     },
     {
@@ -5252,7 +1132,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2212it [00:56, 39.31it/s]"
+      "1722it [00:04, 405.14it/s]"
      ]
     },
     {
@@ -5260,7 +1140,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2216it [00:56, 38.94it/s]"
+      "1763it [00:04, 405.99it/s]"
      ]
     },
     {
@@ -5268,7 +1148,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2220it [00:56, 38.53it/s]"
+      "1804it [00:04, 406.22it/s]"
      ]
     },
     {
@@ -5276,7 +1156,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2224it [00:57, 38.88it/s]"
+      "1845it [00:04, 406.76it/s]"
      ]
     },
     {
@@ -5284,7 +1164,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2228it [00:57, 39.00it/s]"
+      "1886it [00:04, 406.83it/s]"
      ]
     },
     {
@@ -5292,7 +1172,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2232it [00:57, 38.88it/s]"
+      "1927it [00:04, 406.56it/s]"
      ]
     },
     {
@@ -5300,7 +1180,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2236it [00:57, 38.93it/s]"
+      "1968it [00:04, 406.43it/s]"
      ]
     },
     {
@@ -5308,7 +1188,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2241it [00:57, 39.86it/s]"
+      "2009it [00:04, 406.42it/s]"
      ]
     },
     {
@@ -5316,7 +1196,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2246it [00:57, 40.30it/s]"
+      "2050it [00:05, 401.59it/s]"
      ]
     },
     {
@@ -5324,7 +1204,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2251it [00:57, 40.84it/s]"
+      "2091it [00:05, 402.02it/s]"
      ]
     },
     {
@@ -5332,7 +1212,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2256it [00:57, 38.99it/s]"
+      "2133it [00:05, 404.36it/s]"
      ]
     },
     {
@@ -5340,7 +1220,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2260it [00:57, 38.52it/s]"
+      "2174it [00:05, 405.64it/s]"
      ]
     },
     {
@@ -5348,7 +1228,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2264it [00:58, 38.40it/s]"
+      "2215it [00:05, 400.89it/s]"
      ]
     },
     {
@@ -5356,7 +1236,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2268it [00:58, 38.55it/s]"
+      "2256it [00:05, 401.43it/s]"
      ]
     },
     {
@@ -5364,7 +1244,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "2268it [00:58, 38.98it/s]"
+      "2268it [00:05, 403.89it/s]"
      ]
     },
     {
@@ -5395,10 +1275,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.391384Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.391277Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.393444Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.393082Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.058633Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.058576Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.060348Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.060116Z"
     }
    },
    "outputs": [],
@@ -5419,10 +1299,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.394850Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.394737Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.459688Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.459112Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.061088Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.061043Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.094767Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.094389Z"
     }
    },
    "outputs": [
@@ -5447,10 +1327,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.460931Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.460823Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.496097Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.495570Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.095663Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.095606Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.114104Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.113729Z"
     }
    },
    "outputs": [
@@ -5475,10 +1355,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.497373Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.497242Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.538182Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.537784Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.114906Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.114855Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.137011Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.136583Z"
     }
    },
    "outputs": [
@@ -5511,10 +1391,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.539588Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.539456Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.542707Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.542135Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.137775Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.137722Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.139885Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.139629Z"
     }
    },
    "outputs": [],
@@ -5537,10 +1417,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.544118Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.544023Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.547397Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.546978Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.140596Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.140547Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.142811Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.142463Z"
     }
    },
    "outputs": [
@@ -5599,10 +1479,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-30T18:28:16.548631Z",
-     "iopub.status.busy": "2026-08-30T18:28:16.548521Z",
-     "iopub.status.idle": "2026-08-30T18:28:16.551488Z",
-     "shell.execute_reply": "2026-08-30T18:28:16.551080Z"
+     "iopub.execute_input": "2026-09-15T10:27:12.143531Z",
+     "iopub.status.busy": "2026-09-15T10:27:12.143484Z",
+     "iopub.status.idle": "2026-09-15T10:27:12.145474Z",
+     "shell.execute_reply": "2026-09-15T10:27:12.145231Z"
     }
    },
    "outputs": [
diff --git a/examples/ising/ground_state.ipynb b/examples/ising/ground_state.ipynb
index 758a3a47..7a6675b3 100644
--- a/examples/ising/ground_state.ipynb
+++ b/examples/ising/ground_state.ipynb
@@ -26,10 +26,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:43.597396Z",
-     "iopub.status.busy": "2026-08-28T15:14:43.597222Z",
-     "iopub.status.idle": "2026-08-28T15:14:43.874715Z",
-     "shell.execute_reply": "2026-08-28T15:14:43.874415Z"
+     "iopub.execute_input": "2026-09-15T10:27:15.328412Z",
+     "iopub.status.busy": "2026-09-15T10:27:15.328261Z",
+     "iopub.status.idle": "2026-09-15T10:27:15.592358Z",
+     "shell.execute_reply": "2026-09-15T10:27:15.591973Z"
     }
    },
    "outputs": [],
@@ -61,10 +61,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:43.875982Z",
-     "iopub.status.busy": "2026-08-28T15:14:43.875908Z",
-     "iopub.status.idle": "2026-08-28T15:14:43.881080Z",
-     "shell.execute_reply": "2026-08-28T15:14:43.880746Z"
+     "iopub.execute_input": "2026-09-15T10:27:15.593588Z",
+     "iopub.status.busy": "2026-09-15T10:27:15.593519Z",
+     "iopub.status.idle": "2026-09-15T10:27:15.598670Z",
+     "shell.execute_reply": "2026-09-15T10:27:15.598348Z"
     }
    },
    "outputs": [
@@ -109,10 +109,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:43.881914Z",
-     "iopub.status.busy": "2026-08-28T15:14:43.881865Z",
-     "iopub.status.idle": "2026-08-28T15:14:44.220610Z",
-     "shell.execute_reply": "2026-08-28T15:14:44.220294Z"
+     "iopub.execute_input": "2026-09-15T10:27:15.599450Z",
+     "iopub.status.busy": "2026-09-15T10:27:15.599403Z",
+     "iopub.status.idle": "2026-09-15T10:27:15.869519Z",
+     "shell.execute_reply": "2026-09-15T10:27:15.869102Z"
     }
    },
    "outputs": [
@@ -137,7 +137,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 40%|████      | 4/10 [00:00<00:00, 32.89it/s]"
+      " 50%|█████     | 5/10 [00:00<00:00, 42.35it/s]"
      ]
     },
     {
@@ -145,7 +145,7 @@
      "output_type": "stream",
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       "\r",
-      " 80%|████████  | 8/10 [00:00<00:00, 31.41it/s]"
+      "100%|██████████| 10/10 [00:00<00:00, 39.32it/s]"
      ]
     },
     {
@@ -153,7 +153,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 10/10 [00:00<00:00, 31.36it/s]"
+      "100%|██████████| 10/10 [00:00<00:00, 39.70it/s]"
      ]
     },
     {
@@ -215,10 +215,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:44.221746Z",
-     "iopub.status.busy": "2026-08-28T15:14:44.221672Z",
-     "iopub.status.idle": "2026-08-28T15:14:50.940190Z",
-     "shell.execute_reply": "2026-08-28T15:14:50.939861Z"
+     "iopub.execute_input": "2026-09-15T10:27:15.870517Z",
+     "iopub.status.busy": "2026-09-15T10:27:15.870445Z",
+     "iopub.status.idle": "2026-09-15T10:27:21.121213Z",
+     "shell.execute_reply": "2026-09-15T10:27:21.120926Z"
     }
    },
    "outputs": [
@@ -235,7 +235,7 @@
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+      "  5%|▌         | 1/20 [00:00<00:05,  3.75it/s]"
      ]
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@@ -243,7 +243,7 @@
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+      " 10%|█         | 2/20 [00:00<00:05,  3.44it/s]"
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     {
@@ -251,7 +251,7 @@
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+      " 15%|█▌        | 3/20 [00:00<00:04,  3.71it/s]"
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@@ -259,7 +259,7 @@
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-      " 20%|██        | 4/20 [00:01<00:05,  2.94it/s]"
+      " 20%|██        | 4/20 [00:01<00:04,  3.79it/s]"
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@@ -267,7 +267,7 @@
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+      " 25%|██▌       | 5/20 [00:01<00:03,  3.79it/s]"
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+      " 30%|███       | 6/20 [00:01<00:03,  3.79it/s]"
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+      " 40%|████      | 8/20 [00:02<00:03,  3.77it/s]"
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@@ -299,7 +299,7 @@
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+      " 50%|█████     | 10/20 [00:02<00:02,  3.72it/s]"
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@@ -315,7 +315,7 @@
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@@ -323,7 +323,7 @@
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+      " 60%|██████    | 12/20 [00:03<00:02,  3.72it/s]"
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@@ -331,7 +331,7 @@
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      ]
     },
     {
@@ -371,7 +371,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 90%|█████████ | 18/20 [00:06<00:00,  3.01it/s]"
+      " 90%|█████████ | 18/20 [00:04<00:00,  3.92it/s]"
      ]
     },
     {
@@ -379,7 +379,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 95%|█████████▌| 19/20 [00:06<00:00,  3.01it/s]"
+      " 95%|█████████▌| 19/20 [00:04<00:00,  3.95it/s]"
      ]
     },
     {
@@ -387,7 +387,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 20/20 [00:06<00:00,  3.02it/s]"
+      "100%|██████████| 20/20 [00:05<00:00,  3.96it/s]"
      ]
     },
     {
@@ -395,7 +395,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 20/20 [00:06<00:00,  2.98it/s]"
+      "100%|██████████| 20/20 [00:05<00:00,  3.81it/s]"
      ]
     },
     {
@@ -443,16 +443,16 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:50.941148Z",
-     "iopub.status.busy": "2026-08-28T15:14:50.941092Z",
-     "iopub.status.idle": "2026-08-28T15:14:51.074258Z",
-     "shell.execute_reply": "2026-08-28T15:14:51.073800Z"
+     "iopub.execute_input": "2026-09-15T10:27:21.122284Z",
+     "iopub.status.busy": "2026-09-15T10:27:21.122217Z",
+     "iopub.status.idle": "2026-09-15T10:27:21.264847Z",
+     "shell.execute_reply": "2026-09-15T10:27:21.264572Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 500x400 with 1 Axes>"
       ]
diff --git a/examples/main_component/main_component.ipynb b/examples/main_component/main_component.ipynb
index 6043d09e..9d4e1558 100644
--- a/examples/main_component/main_component.ipynb
+++ b/examples/main_component/main_component.ipynb
@@ -24,10 +24,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.688923Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.688685Z",
-     "iopub.status.idle": "2026-08-28T15:14:13.839131Z",
-     "shell.execute_reply": "2026-08-28T15:14:13.838655Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.457002Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.456863Z",
+     "iopub.status.idle": "2026-09-15T10:27:24.610556Z",
+     "shell.execute_reply": "2026-09-15T10:27:24.610119Z"
     }
    },
    "outputs": [],
@@ -73,10 +73,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.840121Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.840046Z",
-     "iopub.status.idle": "2026-08-28T15:14:13.841714Z",
-     "shell.execute_reply": "2026-08-28T15:14:13.841434Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.611546Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.611475Z",
+     "iopub.status.idle": "2026-09-15T10:27:24.613148Z",
+     "shell.execute_reply": "2026-09-15T10:27:24.612869Z"
     }
    },
    "outputs": [],
@@ -98,10 +98,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.842416Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.842373Z",
-     "iopub.status.idle": "2026-08-28T15:14:13.844002Z",
-     "shell.execute_reply": "2026-08-28T15:14:13.843653Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.613982Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.613931Z",
+     "iopub.status.idle": "2026-09-15T10:27:24.615431Z",
+     "shell.execute_reply": "2026-09-15T10:27:24.615174Z"
     }
    },
    "outputs": [],
@@ -124,10 +124,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.844865Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.844799Z",
-     "iopub.status.idle": "2026-08-28T15:14:13.854129Z",
-     "shell.execute_reply": "2026-08-28T15:14:13.853811Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.616227Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.616175Z",
+     "iopub.status.idle": "2026-09-15T10:27:24.624049Z",
+     "shell.execute_reply": "2026-09-15T10:27:24.623694Z"
     }
    },
    "outputs": [],
@@ -149,10 +149,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.854933Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.854888Z",
-     "iopub.status.idle": "2026-08-28T15:14:13.913978Z",
-     "shell.execute_reply": "2026-08-28T15:14:13.913674Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.624816Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.624770Z",
+     "iopub.status.idle": "2026-09-15T10:27:24.682363Z",
+     "shell.execute_reply": "2026-09-15T10:27:24.681981Z"
     }
    },
    "outputs": [
@@ -169,7 +169,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1024/1024 [00:00<00:00, 20335.73it/s]"
+      "100%|██████████| 1024/1024 [00:00<00:00, 21208.35it/s]"
      ]
     },
     {
@@ -204,10 +204,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:13.915146Z",
-     "iopub.status.busy": "2026-08-28T15:14:13.915077Z",
-     "iopub.status.idle": "2026-08-28T15:14:14.432481Z",
-     "shell.execute_reply": "2026-08-28T15:14:14.432127Z"
+     "iopub.execute_input": "2026-09-15T10:27:24.683508Z",
+     "iopub.status.busy": "2026-09-15T10:27:24.683444Z",
+     "iopub.status.idle": "2026-09-15T10:27:25.379534Z",
+     "shell.execute_reply": "2026-09-15T10:27:25.379173Z"
     }
    },
    "outputs": [
@@ -224,7 +224,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00,  3.16it/s]"
+      "100%|██████████| 1/1 [00:00<00:00,  1.99it/s]"
      ]
     },
     {
@@ -232,7 +232,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00,  3.16it/s]"
+      "100%|██████████| 1/1 [00:00<00:00,  1.99it/s]"
      ]
     },
     {
@@ -277,10 +277,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:14.433362Z",
-     "iopub.status.busy": "2026-08-28T15:14:14.433299Z",
-     "iopub.status.idle": "2026-08-28T15:14:14.698232Z",
-     "shell.execute_reply": "2026-08-28T15:14:14.697819Z"
+     "iopub.execute_input": "2026-09-15T10:27:25.380495Z",
+     "iopub.status.busy": "2026-09-15T10:27:25.380440Z",
+     "iopub.status.idle": "2026-09-15T10:27:25.628956Z",
+     "shell.execute_reply": "2026-09-15T10:27:25.628539Z"
     }
    },
    "outputs": [
@@ -297,7 +297,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 38.87it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 54.37it/s]"
      ]
     },
     {
@@ -346,10 +346,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:14.699076Z",
-     "iopub.status.busy": "2026-08-28T15:14:14.699014Z",
-     "iopub.status.idle": "2026-08-28T15:14:14.700575Z",
-     "shell.execute_reply": "2026-08-28T15:14:14.700313Z"
+     "iopub.execute_input": "2026-09-15T10:27:25.629878Z",
+     "iopub.status.busy": "2026-09-15T10:27:25.629822Z",
+     "iopub.status.idle": "2026-09-15T10:27:25.631428Z",
+     "shell.execute_reply": "2026-09-15T10:27:25.631127Z"
     }
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    "outputs": [],
@@ -373,10 +373,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:14.701253Z",
-     "iopub.status.busy": "2026-08-28T15:14:14.701206Z",
-     "iopub.status.idle": "2026-08-28T15:14:14.702693Z",
-     "shell.execute_reply": "2026-08-28T15:14:14.702378Z"
+     "iopub.execute_input": "2026-09-15T10:27:25.632175Z",
+     "iopub.status.busy": "2026-09-15T10:27:25.632129Z",
+     "iopub.status.idle": "2026-09-15T10:27:25.633682Z",
+     "shell.execute_reply": "2026-09-15T10:27:25.633322Z"
     }
    },
    "outputs": [],
diff --git a/examples/random_circuit/mps-rand-circ.ipynb b/examples/random_circuit/mps-rand-circ.ipynb
index b0734edc..6940c7f8 100644
--- a/examples/random_circuit/mps-rand-circ.ipynb
+++ b/examples/random_circuit/mps-rand-circ.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:17.887732Z",
-     "iopub.status.busy": "2026-08-28T15:14:17.887578Z",
-     "iopub.status.idle": "2026-08-28T15:14:18.377359Z",
-     "shell.execute_reply": "2026-08-28T15:14:18.376939Z"
+     "iopub.execute_input": "2026-09-15T10:27:28.684081Z",
+     "iopub.status.busy": "2026-09-15T10:27:28.683926Z",
+     "iopub.status.idle": "2026-09-15T10:27:29.177284Z",
+     "shell.execute_reply": "2026-09-15T10:27:29.176824Z"
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    "outputs": [],
@@ -47,10 +47,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:18.378467Z",
-     "iopub.status.busy": "2026-08-28T15:14:18.378370Z",
-     "iopub.status.idle": "2026-08-28T15:14:40.274040Z",
-     "shell.execute_reply": "2026-08-28T15:14:40.273565Z"
+     "iopub.execute_input": "2026-09-15T10:27:29.178271Z",
+     "iopub.status.busy": "2026-09-15T10:27:29.178183Z",
+     "iopub.status.idle": "2026-09-15T10:27:39.623061Z",
+     "shell.execute_reply": "2026-09-15T10:27:39.622688Z"
     }
    },
    "outputs": [
@@ -67,7 +67,7 @@
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+      " 44%|████▍     | 4/9 [00:00<00:00, 38.47it/s]"
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@@ -75,7 +75,7 @@
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+      " 89%|████████▉ | 8/9 [00:00<00:00, 21.23it/s]"
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     {
@@ -83,39 +83,7 @@
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-     ]
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+      "100%|██████████| 9/9 [00:00<00:00, 20.64it/s]"
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@@ -138,7 +106,7 @@
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+      " 44%|████▍     | 4/9 [00:00<00:00, 34.31it/s]"
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@@ -146,7 +114,7 @@
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+      " 89%|████████▉ | 8/9 [00:00<00:00, 17.83it/s]"
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@@ -154,39 +122,7 @@
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+      "100%|██████████| 9/9 [00:00<00:00, 17.25it/s]"
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+      " 44%|████▍     | 4/9 [00:00<00:00, 28.77it/s]"
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+      "100%|██████████| 9/9 [00:00<00:00, 13.57it/s]"
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+      " 44%|████▍     | 4/9 [00:00<00:00, 24.33it/s]"
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@@ -312,7 +200,7 @@
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+      " 78%|███████▊  | 7/9 [00:00<00:00, 12.93it/s]"
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@@ -320,7 +208,7 @@
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+      "100%|██████████| 9/9 [00:00<00:00,  9.34it/s]"
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+      "100%|██████████| 9/9 [00:00<00:00, 10.80it/s]"
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@@ -391,7 +247,7 @@
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      "output_type": "stream",
      "text": [
       "\r",
-      " 56%|█████▌    | 5/9 [00:01<00:01,  3.86it/s]"
+      " 56%|█████▌    | 5/9 [00:00<00:00,  7.39it/s]"
      ]
     },
     {
@@ -699,7 +475,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 67%|██████▋   | 6/9 [00:01<00:01,  2.96it/s]"
+      " 67%|██████▋   | 6/9 [00:00<00:00,  5.53it/s]"
      ]
     },
     {
@@ -707,7 +483,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 78%|███████▊  | 7/9 [00:02<00:00,  2.36it/s]"
+      " 78%|███████▊  | 7/9 [00:01<00:00,  4.28it/s]"
      ]
     },
     {
@@ -715,7 +491,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 89%|████████▉ | 8/9 [00:02<00:00,  1.94it/s]"
+      " 89%|████████▉ | 8/9 [00:01<00:00,  3.42it/s]"
      ]
     },
     {
@@ -723,7 +499,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 9/9 [00:03<00:00,  1.64it/s]"
+      "100%|██████████| 9/9 [00:02<00:00,  2.83it/s]"
      ]
     },
     {
@@ -731,7 +507,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 9/9 [00:03<00:00,  2.35it/s]"
+      "100%|██████████| 9/9 [00:02<00:00,  4.00it/s]"
      ]
     },
     {
@@ -803,10 +579,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:40.275004Z",
-     "iopub.status.busy": "2026-08-28T15:14:40.274934Z",
-     "iopub.status.idle": "2026-08-28T15:14:40.277149Z",
-     "shell.execute_reply": "2026-08-28T15:14:40.276724Z"
+     "iopub.execute_input": "2026-09-15T10:27:39.624183Z",
+     "iopub.status.busy": "2026-09-15T10:27:39.624110Z",
+     "iopub.status.idle": "2026-09-15T10:27:39.626107Z",
+     "shell.execute_reply": "2026-09-15T10:27:39.625853Z"
     }
    },
    "outputs": [],
@@ -833,16 +609,16 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-08-28T15:14:40.277994Z",
-     "iopub.status.busy": "2026-08-28T15:14:40.277940Z",
-     "iopub.status.idle": "2026-08-28T15:14:40.424175Z",
-     "shell.execute_reply": "2026-08-28T15:14:40.423814Z"
+     "iopub.execute_input": "2026-09-15T10:27:39.626926Z",
+     "iopub.status.busy": "2026-09-15T10:27:39.626868Z",
+     "iopub.status.idle": "2026-09-15T10:27:39.776429Z",
+     "shell.execute_reply": "2026-09-15T10:27:39.776052Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 400x300 with 1 Axes>"
       ]

From 9e89443ff5d57f402e4ca66fca78c731544126c4 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Tue, 15 Sep 2026 09:11:35 -0400
Subject: [PATCH 11/15] Match the notebook text and runtimes to the regenerated
 outputs

quantum_surface: the rates quoted at p = 0.08, the p = 0.105 exception
(now a small L = 5 below L = 3 reversal, not a tie), the L = 5/L = 7 gap
sizes and the sign-change description follow the regenerated table. The
L = 3 bond-dimension paragraph follows the regenerated plot, whose
chi_max = 8 curve now sits above the converged one at high rates rather
than below it at p = 0.07 to 0.09; that sweep's counts were recomputed
from its seed, since the cell does not print them. The runtime note
gives this run's times on eight workers.

classical_ldpc: the comparison cell's runtime. notebook_pipeline.rst
and the notebooks workflow comment: the per-notebook times of this run,
about 12 hours in total.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 .github/workflows/notebooks.yml         | 13 ++++-----
 docs/source/notebook_pipeline.rst       | 37 +++++++++++++------------
 examples/decoding/classical_ldpc.ipynb  |  2 +-
 examples/decoding/quantum_surface.ipynb |  8 +++---
 4 files changed, 30 insertions(+), 30 deletions(-)

diff --git a/.github/workflows/notebooks.yml b/.github/workflows/notebooks.yml
index cc037238..b193358b 100644
--- a/.github/workflows/notebooks.yml
+++ b/.github/workflows/notebooks.yml
@@ -5,13 +5,12 @@ name: notebooks
 # nothing ran these.
 #
 # MDOPT_NB_FAST=1 shrinks the workloads: at the committed full-scale settings
-# the suite totals roughly 20 hours (quantum_surface ~13h, classical_ldpc
-# ~4h, quantum_three_qubit ~1.6h, maxbonddim ~1.2h -- see
-# docs/source/notebook_pipeline.rst), past the 6h GitHub caps a job at and far
-# too dear to spend per pull request. The notebooks read that variable
-# themselves. What is being tested is that they execute, not the numbers they
-# produce -- the outputs are discarded, and the ones the documentation shows
-# come from a full-scale run committed by hand.
+# the suite totals roughly 12 hours (quantum_surface ~5.5h, maxbonddim ~3.2h,
+# classical_ldpc ~2.8h -- see docs/source/notebook_pipeline.rst), past the 6h
+# GitHub caps a job at and far too dear to spend per pull request. The
+# notebooks read that variable themselves. What is being tested is that they
+# execute, not the numbers they produce -- the outputs are discarded, and the
+# ones the documentation shows come from a full-scale run committed by hand.
 
 on:
   push:
diff --git a/docs/source/notebook_pipeline.rst b/docs/source/notebook_pipeline.rst
index 300bdb1b..0c05c977 100644
--- a/docs/source/notebook_pipeline.rst
+++ b/docs/source/notebook_pipeline.rst
@@ -46,27 +46,28 @@ Regenerating the results
 notebook afterwards; the next push to ``main`` opens the sync PR, and the docs
 follow once it is merged.
 
-Expect this to take hours. Measured on an M-series laptop (10 cores), one
-notebook at a time:
+Expect this to take hours: the last full run took about 12 hours. Measured on
+an M-series laptop (10 cores: 4 performance, 6 efficiency), one notebook at a
+time, with one BLAS thread per process:
 
-===========================  ==================================================
+===========================  ==============================================================
 notebook                     full run
-===========================  ==================================================
+===========================  ==============================================================
 ``main_component``           4 s
-``ground_state``             11 s
-``mps-rand-circ``            26 s
-``dephasing_dmrg_debug_bb``  39 s
-``shor``                     39 s
-``quantum_five_qubit``       43 s
-``maxbonddim``               1.2 h
-``quantum_three_qubit``      1.6 h
-``classical_ldpc``           ~4 h (the BP comparison cell alone 1.25 h)
-``quantum_surface``          ~13 h (the threshold sweep alone ~10 h)
-===========================  ==================================================
-
-The last two notebooks end with a cell that regenerates its data through a
-pool of worker processes (all but two cores by default;
-``MDOPT_NB_PROCESSES`` overrides it). Their times above are with five
+``quantum_five_qubit``       7 s
+``ground_state``             9 s
+``shor``                     10 s
+``mps-rand-circ``            14 s
+``dephasing_dmrg_debug_bb``  1.5 min
+``quantum_three_qubit``      4.6 min
+``classical_ldpc``           2.8 h (the truncation sweep 2.2 h, the BP comparison 36 min)
+``maxbonddim``               3.2 h
+``quantum_surface``          5.5 h (the threshold sweep alone 4.7 h)
+===========================  ==============================================================
+
+``classical_ldpc`` and ``quantum_surface`` end with a cell that regenerates
+its data through a pool of worker processes (all but two cores by default;
+``MDOPT_NB_PROCESSES`` overrides it). Their times above are with eight
 workers; note that concurrent workers on this laptop run about three times
 slower per shot than a single process, because they share the efficiency
 cores, so a lone-process estimate understates them badly. The shot counts in
diff --git a/examples/decoding/classical_ldpc.ipynb b/examples/decoding/classical_ldpc.ipynb
index 687fe66d..3e64f827 100644
--- a/examples/decoding/classical_ldpc.ipynb
+++ b/examples/decoding/classical_ldpc.ipynb
@@ -2129,7 +2129,7 @@
    "source": [
     "We see what we expect: the decoder is able to correct more errors with less truncation. This is a good sign that the decoder is working as expected.\n",
     "\n",
-    "Finally, let us compare the MPS-MPO decoder with belief propagation, the standard decoder for LDPC codes, on identical codes and identical received words: for every shot a fresh random (3,4)-regular code is drawn, a codeword is sent through the binary symmetric channel, and both decoders see the same corrupted word. Belief propagation (`ldpc`, product-sum, 80 iterations) is run inline, the MPS-MPO decodes go through the campaign worker in parallel. Nothing is loaded from disk; the cell takes about an hour and a quarter at full scale on five worker processes."
+    "Finally, let us compare the MPS-MPO decoder with belief propagation, the standard decoder for LDPC codes, on identical codes and identical received words: for every shot a fresh random (3,4)-regular code is drawn, a codeword is sent through the binary symmetric channel, and both decoders see the same corrupted word. Belief propagation (`ldpc`, product-sum, 80 iterations) is run inline, the MPS-MPO decodes go through the campaign worker in parallel. Nothing is loaded from disk; the cell takes about 36 minutes at full scale on eight worker processes."
    ]
   },
   {
diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index a5be5f26..ec202d86 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -2328,14 +2328,14 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The $\\chi_{\\max} = 64$ and $\\chi_{\\max} = 128$ curves lie on top of each other at every rate: for bit-flip noise the decoder is exact once the bond dimension reaches $2^6$, where $6$ is the largest number of leg crossings met while applying the MPOs on this lattice, so nothing changes beyond it. The $\\chi_{\\max} = 32$ and $16$ curves are within one standard error of the converged one everywhere; only $\\chi_{\\max} = 8$ departs from it, by about one standard error around $p = 0.07$ to $0.09$, where truncation happens to make the decoder look slightly better rather than worse. With 500 shots per point the error bars are about $\\pm 0.015$, so this is the resolution at which \"converged\" is meant here.\n"
+    "The $\\chi_{\\max} = 64$ and $\\chi_{\\max} = 128$ curves lie on top of each other at every rate: for bit-flip noise the decoder is exact once the bond dimension reaches $2^6$, where $6$ is the largest number of leg crossings met while applying the MPOs on this lattice, so nothing changes beyond it. The $\\chi_{\\max} = 32$ and $16$ curves stay within one standard error of the converged one everywhere. $\\chi_{\\max} = 8$ departs furthest at the highest rates, where truncation makes the decoder worse, as it should: at $p = 0.13$ it fails on 22.4% of the shots against 20.6%, about one standard error. With 500 shots per point the error bars are about $\\pm 0.015$, so this is the resolution at which \"converged\" is meant here.\n"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, the bond dimension at which the $L = 3$ sweep above is converged ($\\chi_{\\max} = 64$), a grid that is dense around the crossing, and enough shots to resolve it. Whether $L = 7$ is converged at this bond dimension is not established by the sweep above (its MPOs have more leg crossings than those of $L = 3$), and the discussion after the plot comes back to this. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about eleven hours at full scale on five worker processes (ten minutes for $L = 3$, two and a half hours for $L = 5$, eight for $L = 7$).\n"
+    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, the bond dimension at which the $L = 3$ sweep above is converged ($\\chi_{\\max} = 64$), a grid that is dense around the crossing, and enough shots to resolve it. Whether $L = 7$ is converged at this bond dimension is not established by the sweep above (its MPOs have more leg crossings than those of $L = 3$), and the discussion after the plot comes back to this. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about four and three-quarter hours at full scale on eight worker processes (four and a half minutes for $L = 3$, one hour for $L = 5$, three hours and forty minutes for $L = 7$).\n"
    ]
   },
   {
@@ -2898,9 +2898,9 @@
    "id": "b0dda13e",
    "metadata": {},
    "source": [
-    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.2%, $L = 5$ at 8.8%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, and at $p = 0.095$ and $0.10$ all three coincide within their errors. Above $p = 0.10$ the larger code fails more often at every rate except for a tie between $L = 3$ and $L = 5$ at $p = 0.105$, but the separation does not grow steadily: the $L = 5$/$L = 7$ gap is 3.3 percentage points at $p = 0.11$, 1.6 at $p = 0.12$ and 4.3 at $p = 0.13$. The reversal itself is clear; its size from one rate to the next is at the level of the statistical errors. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
+    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.1%, $L = 5$ at 8.7%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, and at $p = 0.095$ and $0.10$ all three coincide within their errors. Above $p = 0.10$ the larger code fails more often at every rate except $p = 0.105$, where $L = 5$ fails slightly less often than $L = 3$ (14.7% against 14.8%), but the separation does not grow steadily: the $L = 5$/$L = 7$ gap is 3.2 percentage points at $p = 0.11$, 1.6 at $p = 0.12$ and 4.2 at $p = 0.13$. The reversal itself is clear; its size from one rate to the next is at the level of the statistical errors. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
     "\n",
-    "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.4 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points; with standard errors of 0.5 to 0.8 percentage points per point the sign changes three times on this grid, which is why a single interpolated crossing would be an arbitrary choice and the fit is used instead.\n",
+    "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.4 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points. For $L = 5$/$L = 7$ the difference turns positive between $p = 0.08$ and $0.09$, stays within half a percentage point of zero up to $p = 0.105$, and is exactly zero at $p = 0.10$; for $L = 3$/$L = 5$ it changes sign three times. With standard errors of 0.5 to 0.8 percentage points per point, a single interpolated crossing would be an arbitrary choice, so the fit is used instead.\n",
     "\n",
     "The estimate sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. The $L = 3$/$L = 5$ crossing ($9.9 \\pm 0.3\\%$) is higher than the $L = 5$/$L = 7$ one, and the two intervals overlap, so this run does not resolve a finite-size drift in either direction. The shortfall is not explained by truncation: a same-shot comparison at $L = 7$, run outside this notebook with the same noise, prior and qubit ordering, found no significant change in the failure rate between $\\chi_{\\max} = 64$, $128$ and $256$ at $p = 0.10$ and $0.11$. The same comparison found the decoder sensitive to its prior at $\\chi_{\\max} = 64$: at $L = 7$ and $p = 0.11$ a prior of $0.03$ failed on 158 of 1000 shots against 189 for the matched prior. Why the matched prior loses to a sharper one here is not yet understood, and it is the next thing to examine.\n",
     "\n",

From 27b77de3281aa2cb2f411a6a3790c21b3557462f Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Tue, 15 Sep 2026 10:38:35 -0400
Subject: [PATCH 12/15] Document the per-cell timeout a full notebook
 regeneration needs

scripts/run_notebooks.py stops any cell after 1800 s by default, a limit
sized for the fast CI workloads. At full scale the surface-code threshold
sweep takes 4.7 h, maxbonddim's sweep 3.2 h and classical_ldpc's
truncation sweep 2.2 h, so the documented regeneration command would
time out. The docs and the script's usage now pass --timeout 86400, the
value the last full run used, and name MDOPT_NB_TIMEOUT.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 docs/source/notebook_pipeline.rst | 7 ++++++-
 scripts/run_notebooks.py          | 5 +++++
 2 files changed, 11 insertions(+), 1 deletion(-)

diff --git a/docs/source/notebook_pipeline.rst b/docs/source/notebook_pipeline.rst
index 0c05c977..e5bd7bbc 100644
--- a/docs/source/notebook_pipeline.rst
+++ b/docs/source/notebook_pipeline.rst
@@ -39,13 +39,18 @@ Regenerating the results
 
 .. code-block:: bash
 
-   python scripts/run_notebooks.py --inplace                    # all of them
+   python scripts/run_notebooks.py --inplace --timeout 86400    # all of them
    python scripts/run_notebooks.py --inplace examples/decoding/shor.ipynb
 
 ``--inplace`` writes the executed outputs back into the notebook. Commit the
 notebook afterwards; the next push to ``main`` opens the sync PR, and the docs
 follow once it is merged.
 
+``--timeout`` is the limit per cell, in seconds. Its default of 1800 (or
+``MDOPT_NB_TIMEOUT``, if set) suits the fast CI workloads, but at full scale
+the longest cells below run for hours, so a full regeneration needs a larger
+limit; the last one used a day.
+
 Expect this to take hours: the last full run took about 12 hours. Measured on
 an M-series laptop (10 cores: 4 performance, 6 efficiency), one notebook at a
 time, with one BLAS thread per process:
diff --git a/scripts/run_notebooks.py b/scripts/run_notebooks.py
index 0a0c91e1..6c555dfe 100644
--- a/scripts/run_notebooks.py
+++ b/scripts/run_notebooks.py
@@ -25,6 +25,11 @@
     python scripts/run_notebooks.py                 # every eligible notebook
     python scripts/run_notebooks.py path/to/nb.ipynb
     MDOPT_NB_FAST=1 python scripts/run_notebooks.py  # CI-scale workloads
+    python scripts/run_notebooks.py --inplace --timeout 86400  # full-scale results
+
+At full scale several cells run for hours, far past the default per-cell
+timeout of 1800 s (``--timeout``, or ``MDOPT_NB_TIMEOUT``), so a full run
+needs a larger one; docs/source/notebook_pipeline.rst lists the times.
 """
 
 from __future__ import annotations

From b8efb01251d63d89793a825a3aba060c27e85a55 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Wed, 16 Sep 2026 15:15:44 -0400
Subject: [PATCH 13/15] Rerun the surface-code threshold sweep at chi_max = 128

The threshold sweep in quantum_surface.ipynb now decodes at
chi_max = 128 instead of 64, and the notebook was re-executed at full
scale on eight workers with one BLAS thread each, so its table, fitted
crossings and figure come from that run. The narrative around the
figure is brought into line in a follow-up commit.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 examples/decoding/quantum_surface.ipynb | 550 ++++++++++++------------
 1 file changed, 275 insertions(+), 275 deletions(-)

diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index ec202d86..9c2c7e37 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -19,10 +19,10 @@
    "execution_count": 1,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:30.811900Z",
-     "iopub.status.busy": "2026-09-15T04:50:30.811741Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.289988Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.289575Z"
+     "iopub.execute_input": "2026-09-15T15:51:38.909717Z",
+     "iopub.status.busy": "2026-09-15T15:51:38.909569Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.417208Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.416756Z"
     }
    },
    "outputs": [],
@@ -88,10 +88,10 @@
    "execution_count": 2,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.291218Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.291126Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.296209Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.295865Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.418256Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.418164Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.419992Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.419692Z"
     }
    },
    "outputs": [
@@ -142,10 +142,10 @@
    "execution_count": 3,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.297041Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.296993Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.298577Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.298240Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.432993Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.432923Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.434411Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.434132Z"
     }
    },
    "outputs": [],
@@ -169,10 +169,10 @@
    "execution_count": 4,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.299403Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.299348Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.301058Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.300739Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.435134Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.435088Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.436692Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.436364Z"
     }
    },
    "outputs": [],
@@ -197,10 +197,10 @@
    "execution_count": 5,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.301916Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.301860Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.303625Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.303369Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.437468Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.437417Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.439011Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.438749Z"
     }
    },
    "outputs": [
@@ -247,10 +247,10 @@
    "execution_count": 6,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.304367Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.304317Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.305870Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.305520Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.439759Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.439711Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.441047Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.440747Z"
     }
    },
    "outputs": [],
@@ -264,10 +264,10 @@
    "execution_count": 7,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.306638Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.306592Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.308253Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.307995Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.441722Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.441682Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.443262Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.442948Z"
     }
    },
    "outputs": [
@@ -314,10 +314,10 @@
    "execution_count": 8,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.309001Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.308946Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.310499Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.310214Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.443909Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.443870Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.445174Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.444911Z"
     }
    },
    "outputs": [
@@ -349,10 +349,10 @@
    "execution_count": 9,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.311311Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.311262Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.312854Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.312552Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.445919Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.445875Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.447347Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.447122Z"
     }
    },
    "outputs": [
@@ -382,10 +382,10 @@
    "execution_count": 10,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.313554Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.313504Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.315124Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.314781Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.448066Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.448026Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.449477Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.449146Z"
     }
    },
    "outputs": [
@@ -416,10 +416,10 @@
    "execution_count": 11,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.315935Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.315871Z",
-     "iopub.status.idle": "2026-09-15T04:50:31.317666Z",
-     "shell.execute_reply": "2026-09-15T04:50:31.317439Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.450156Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.450113Z",
+     "iopub.status.idle": "2026-09-15T15:51:39.451761Z",
+     "shell.execute_reply": "2026-09-15T15:51:39.451488Z"
     }
    },
    "outputs": [],
@@ -438,10 +438,10 @@
    "execution_count": 12,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:50:31.318410Z",
-     "iopub.status.busy": "2026-09-15T04:50:31.318355Z",
-     "iopub.status.idle": "2026-09-15T04:51:30.617441Z",
-     "shell.execute_reply": "2026-09-15T04:51:30.617042Z"
+     "iopub.execute_input": "2026-09-15T15:51:39.452447Z",
+     "iopub.status.busy": "2026-09-15T15:51:39.452399Z",
+     "iopub.status.idle": "2026-09-15T15:52:36.417394Z",
+     "shell.execute_reply": "2026-09-15T15:52:36.416930Z"
     }
    },
    "outputs": [
@@ -458,7 +458,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 436.91it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 467.75it/s]"
      ]
     },
     {
@@ -481,7 +481,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 1/1 [00:00<00:00, 430.10it/s]"
+      "100%|██████████| 1/1 [00:00<00:00, 400.95it/s]"
      ]
     },
     {
@@ -504,7 +504,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 6/6 [00:00<00:00, 168.85it/s]"
+      "100%|██████████| 6/6 [00:00<00:00, 175.47it/s]"
      ]
     },
     {
@@ -527,7 +527,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 33%|███▎      | 2/6 [00:00<00:00,  8.72it/s]"
+      " 33%|███▎      | 2/6 [00:00<00:00,  8.98it/s]"
      ]
     },
     {
@@ -535,7 +535,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 50%|█████     | 3/6 [00:01<00:01,  2.01it/s]"
+      " 50%|█████     | 3/6 [00:01<00:01,  2.05it/s]"
      ]
     },
     {
@@ -543,7 +543,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 67%|██████▋   | 4/6 [00:03<00:02,  1.13s/it]"
+      " 67%|██████▋   | 4/6 [00:03<00:02,  1.10s/it]"
      ]
     },
     {
@@ -551,7 +551,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 83%|████████▎ | 5/6 [00:12<00:04,  4.05s/it]"
+      " 83%|████████▎ | 5/6 [00:12<00:03,  3.94s/it]"
      ]
     },
     {
@@ -559,7 +559,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 6/6 [00:59<00:00, 18.06s/it]"
+      "100%|██████████| 6/6 [00:56<00:00, 17.32s/it]"
      ]
     },
     {
@@ -567,7 +567,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 6/6 [00:59<00:00,  9.87s/it]"
+      "100%|██████████| 6/6 [00:56<00:00,  9.48s/it]"
      ]
     },
     {
@@ -624,10 +624,10 @@
    "execution_count": 13,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:51:30.618394Z",
-     "iopub.status.busy": "2026-09-15T04:51:30.618318Z",
-     "iopub.status.idle": "2026-09-15T04:51:30.977958Z",
-     "shell.execute_reply": "2026-09-15T04:51:30.977609Z"
+     "iopub.execute_input": "2026-09-15T15:52:36.418505Z",
+     "iopub.status.busy": "2026-09-15T15:52:36.418434Z",
+     "iopub.status.idle": "2026-09-15T15:52:36.854409Z",
+     "shell.execute_reply": "2026-09-15T15:52:36.854097Z"
     }
    },
    "outputs": [
@@ -680,10 +680,10 @@
    "execution_count": 14,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:51:30.979035Z",
-     "iopub.status.busy": "2026-09-15T04:51:30.978961Z",
-     "iopub.status.idle": "2026-09-15T04:51:30.980536Z",
-     "shell.execute_reply": "2026-09-15T04:51:30.980284Z"
+     "iopub.execute_input": "2026-09-15T15:52:36.855502Z",
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+     "shell.execute_reply": "2026-09-15T15:52:36.856625Z"
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    "outputs": [],
@@ -703,10 +703,10 @@
    "execution_count": 15,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:51:30.981264Z",
-     "iopub.status.busy": "2026-09-15T04:51:30.981207Z",
-     "iopub.status.idle": "2026-09-15T04:51:30.982507Z",
-     "shell.execute_reply": "2026-09-15T04:51:30.982223Z"
+     "iopub.execute_input": "2026-09-15T15:52:36.857649Z",
+     "iopub.status.busy": "2026-09-15T15:52:36.857597Z",
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    "outputs": [
@@ -727,10 +727,10 @@
    "execution_count": 16,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:51:30.983292Z",
-     "iopub.status.busy": "2026-09-15T04:51:30.983245Z",
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-     "shell.execute_reply": "2026-09-15T04:53:55.175801Z"
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+     "shell.execute_reply": "2026-09-15T15:54:53.755756Z"
     }
    },
    "outputs": [
@@ -747,7 +747,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "  9%|▉         | 1/11 [00:46<07:42, 46.20s/it]"
+      "  9%|▉         | 1/11 [00:44<07:20, 44.06s/it]"
      ]
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     {
@@ -755,7 +755,7 @@
      "output_type": "stream",
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       "\r",
-      " 18%|█▊        | 2/11 [01:32<06:56, 46.28s/it]"
+      " 18%|█▊        | 2/11 [01:27<06:34, 43.86s/it]"
      ]
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     {
@@ -763,7 +763,7 @@
      "output_type": "stream",
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       "\r",
-      " 27%|██▋       | 3/11 [02:07<05:27, 40.93s/it]"
+      " 27%|██▋       | 3/11 [02:00<05:10, 38.82s/it]"
      ]
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     {
@@ -771,7 +771,7 @@
      "output_type": "stream",
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       "\r",
-      " 36%|███▋      | 4/11 [02:17<03:22, 28.90s/it]"
+      " 36%|███▋      | 4/11 [02:10<03:12, 27.44s/it]"
      ]
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     {
@@ -779,7 +779,7 @@
      "output_type": "stream",
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       "\r",
-      " 45%|████▌     | 5/11 [02:21<01:58, 19.75s/it]"
+      " 45%|████▌     | 5/11 [02:13<01:52, 18.76s/it]"
      ]
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     {
@@ -787,7 +787,7 @@
      "output_type": "stream",
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       "\r",
-      " 55%|█████▍    | 6/11 [02:22<01:07, 13.51s/it]"
+      " 55%|█████▍    | 6/11 [02:15<01:04, 12.84s/it]"
      ]
     },
     {
@@ -795,7 +795,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 64%|██████▎   | 7/11 [02:23<00:37,  9.33s/it]"
+      " 64%|██████▎   | 7/11 [02:15<00:35,  8.86s/it]"
      ]
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     {
@@ -803,7 +803,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 73%|███████▎  | 8/11 [02:23<00:19,  6.47s/it]"
+      " 73%|███████▎  | 8/11 [02:16<00:18,  6.15s/it]"
      ]
     },
     {
@@ -811,7 +811,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 82%|████████▏ | 9/11 [02:23<00:09,  4.53s/it]"
+      " 82%|████████▏ | 9/11 [02:16<00:08,  4.30s/it]"
      ]
     },
     {
@@ -819,7 +819,7 @@
      "output_type": "stream",
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       "\r",
-      " 91%|█████████ | 10/11 [02:23<00:03,  3.19s/it]"
+      " 91%|█████████ | 10/11 [02:16<00:03,  3.03s/it]"
      ]
     },
     {
@@ -827,7 +827,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [02:24<00:00,  2.27s/it]"
+      "100%|██████████| 11/11 [02:16<00:00,  2.15s/it]"
      ]
     },
     {
@@ -835,7 +835,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 11/11 [02:24<00:00, 13.11s/it]"
+      "100%|██████████| 11/11 [02:16<00:00, 12.44s/it]"
      ]
     },
     {
@@ -865,10 +865,10 @@
    "execution_count": 17,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:53:55.181173Z",
-     "iopub.status.busy": "2026-09-15T04:53:55.181111Z",
-     "iopub.status.idle": "2026-09-15T04:53:55.304010Z",
-     "shell.execute_reply": "2026-09-15T04:53:55.303648Z"
+     "iopub.execute_input": "2026-09-15T15:54:53.757019Z",
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+     "shell.execute_reply": "2026-09-15T15:54:53.881633Z"
     }
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    "outputs": [
@@ -913,10 +913,10 @@
    "execution_count": 18,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:53:55.304840Z",
-     "iopub.status.busy": "2026-09-15T04:53:55.304780Z",
-     "iopub.status.idle": "2026-09-15T04:53:55.313902Z",
-     "shell.execute_reply": "2026-09-15T04:53:55.313572Z"
+     "iopub.execute_input": "2026-09-15T15:54:53.882907Z",
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+     "shell.execute_reply": "2026-09-15T15:54:53.893239Z"
     }
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    "outputs": [
@@ -949,10 +949,10 @@
    "execution_count": 19,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:53:55.314676Z",
-     "iopub.status.busy": "2026-09-15T04:53:55.314626Z",
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-     "shell.execute_reply": "2026-09-15T04:55:51.365326Z"
+     "iopub.execute_input": "2026-09-15T15:54:53.894437Z",
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+     "shell.execute_reply": "2026-09-15T15:56:45.121319Z"
     }
    },
    "outputs": [
@@ -969,7 +969,7 @@
      "output_type": "stream",
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       "\r",
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+      "  9%|▉         | 1/11 [00:35<05:56, 35.67s/it]"
      ]
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     {
@@ -977,7 +977,7 @@
      "output_type": "stream",
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       "\r",
-      " 18%|█▊        | 2/11 [01:14<05:35, 37.33s/it]"
+      " 18%|█▊        | 2/11 [01:11<05:21, 35.77s/it]"
      ]
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     {
@@ -985,7 +985,7 @@
      "output_type": "stream",
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       "\r",
-      " 27%|██▋       | 3/11 [01:41<04:18, 32.31s/it]"
+      " 27%|██▋       | 3/11 [01:36<04:07, 30.94s/it]"
      ]
     },
     {
@@ -993,7 +993,7 @@
      "output_type": "stream",
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       "\r",
-      " 36%|███▋      | 4/11 [01:51<02:47, 23.86s/it]"
+      " 36%|███▋      | 4/11 [01:47<02:40, 22.89s/it]"
      ]
     },
     {
@@ -1001,7 +1001,7 @@
      "output_type": "stream",
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       "\r",
-      " 45%|████▌     | 5/11 [01:55<01:38, 16.40s/it]"
+      " 45%|████▌     | 5/11 [01:50<01:34, 15.74s/it]"
      ]
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     {
@@ -1009,7 +1009,7 @@
      "output_type": "stream",
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-      " 55%|█████▍    | 6/11 [01:55<00:55, 11.07s/it]"
+      " 55%|█████▍    | 6/11 [01:50<00:53, 10.62s/it]"
      ]
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     {
@@ -1017,7 +1017,7 @@
      "output_type": "stream",
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+      " 64%|██████▎   | 7/11 [01:51<00:28,  7.20s/it]"
      ]
     },
     {
@@ -1025,7 +1025,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 11/11 [01:56<00:00, 10.55s/it]"
+      "100%|██████████| 11/11 [01:51<00:00, 10.11s/it]"
      ]
     },
     {
@@ -1090,10 +1090,10 @@
    "execution_count": 20,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:55:51.366621Z",
-     "iopub.status.busy": "2026-09-15T04:55:51.366561Z",
-     "iopub.status.idle": "2026-09-15T04:55:51.542368Z",
-     "shell.execute_reply": "2026-09-15T04:55:51.542108Z"
+     "iopub.execute_input": "2026-09-15T15:56:45.122728Z",
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+     "shell.execute_reply": "2026-09-15T15:56:45.294959Z"
     }
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    "outputs": [
@@ -1141,10 +1141,10 @@
    "execution_count": 21,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:55:51.543295Z",
-     "iopub.status.busy": "2026-09-15T04:55:51.543237Z",
-     "iopub.status.idle": "2026-09-15T04:55:51.544700Z",
-     "shell.execute_reply": "2026-09-15T04:55:51.544427Z"
+     "iopub.execute_input": "2026-09-15T15:56:45.296182Z",
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+     "shell.execute_reply": "2026-09-15T15:56:45.297185Z"
     }
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    "outputs": [],
@@ -1164,10 +1164,10 @@
    "execution_count": 22,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:55:51.545398Z",
-     "iopub.status.busy": "2026-09-15T04:55:51.545352Z",
-     "iopub.status.idle": "2026-09-15T04:55:51.546978Z",
-     "shell.execute_reply": "2026-09-15T04:55:51.546753Z"
+     "iopub.execute_input": "2026-09-15T15:56:45.298223Z",
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+     "shell.execute_reply": "2026-09-15T15:56:45.299473Z"
     }
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    "outputs": [],
@@ -1181,10 +1181,10 @@
    "execution_count": 23,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T04:55:51.547766Z",
-     "iopub.status.busy": "2026-09-15T04:55:51.547694Z",
-     "iopub.status.idle": "2026-09-15T04:55:51.885265Z",
-     "shell.execute_reply": "2026-09-15T04:55:51.884928Z"
+     "iopub.execute_input": "2026-09-15T15:56:45.300605Z",
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+     "shell.execute_reply": "2026-09-15T15:56:45.635327Z"
     }
    },
    "outputs": [
@@ -1201,7 +1201,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 31%|███       | 12/39 [00:00<00:00, 116.97it/s]"
+      " 31%|███       | 12/39 [00:00<00:00, 115.37it/s]"
      ]
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     {
@@ -1209,7 +1209,7 @@
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-      " 62%|██████▏   | 24/39 [00:00<00:00, 115.32it/s]"
+      " 62%|██████▏   | 24/39 [00:00<00:00, 114.92it/s]"
      ]
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     {
@@ -1217,7 +1217,7 @@
      "output_type": "stream",
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       "\r",
-      " 92%|█████████▏| 36/39 [00:00<00:00, 116.77it/s]"
+      " 95%|█████████▍| 37/39 [00:00<00:00, 118.09it/s]"
      ]
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     {
@@ -1225,7 +1225,7 @@
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       "\r",
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+      "100%|██████████| 39/39 [00:00<00:00, 117.15it/s]"
      ]
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     {
@@ -1255,10 +1255,10 @@
    "execution_count": 24,
    "metadata": {
     "execution": {
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-     "iopub.status.busy": "2026-09-15T04:55:51.886044Z",
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-     "shell.execute_reply": "2026-09-15T05:06:07.427179Z"
+     "iopub.execute_input": "2026-09-15T15:56:45.636522Z",
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+     "shell.execute_reply": "2026-09-15T16:07:08.544609Z"
     }
    },
    "outputs": [
@@ -1275,7 +1275,7 @@
      "output_type": "stream",
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+      "  5%|▌         | 1/20 [00:19<06:03, 19.12s/it]"
      ]
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@@ -1283,7 +1283,7 @@
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-      " 10%|█         | 2/20 [00:53<08:22, 27.93s/it]"
+      " 10%|█         | 2/20 [00:52<08:13, 27.39s/it]"
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+      " 15%|█▌        | 3/20 [01:27<08:48, 31.11s/it]"
      ]
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@@ -1299,7 +1299,7 @@
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-      " 20%|██        | 4/20 [02:00<08:21, 31.37s/it]"
+      " 20%|██        | 4/20 [01:58<08:14, 30.90s/it]"
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+      " 25%|██▌       | 5/20 [02:19<06:49, 27.30s/it]"
      ]
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+      " 30%|███       | 6/20 [02:49<06:33, 28.11s/it]"
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+      " 35%|███▌      | 7/20 [03:20<06:18, 29.10s/it]"
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      "output_type": "stream",
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+      " 40%|████      | 8/20 [03:54<06:11, 30.92s/it]"
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+      " 45%|████▌     | 9/20 [04:30<05:55, 32.32s/it]"
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+      " 50%|█████     | 10/20 [05:00<05:17, 31.78s/it]"
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+      " 55%|█████▌    | 11/20 [05:35<04:54, 32.75s/it]"
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+      " 60%|██████    | 12/20 [06:14<04:37, 34.67s/it]"
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-      " 95%|█████████▌| 19/20 [09:46<00:28, 28.19s/it]"
+      " 95%|█████████▌| 19/20 [09:51<00:29, 29.41s/it]"
      ]
     },
     {
@@ -1427,7 +1427,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 20/20 [10:15<00:00, 28.51s/it]"
+      "100%|██████████| 20/20 [10:22<00:00, 30.02s/it]"
      ]
     },
     {
@@ -1435,7 +1435,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 20/20 [10:15<00:00, 30.78s/it]"
+      "100%|██████████| 20/20 [10:22<00:00, 31.15s/it]"
      ]
     },
     {
@@ -1465,10 +1465,10 @@
    "execution_count": 25,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.428500Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.428436Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.540878Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.540518Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.545913Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.545855Z",
+     "iopub.status.idle": "2026-09-15T16:07:08.666883Z",
+     "shell.execute_reply": "2026-09-15T16:07:08.666561Z"
     }
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    "outputs": [
@@ -1519,10 +1519,10 @@
    "execution_count": 26,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.541763Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.541708Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.543133Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.542866Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.667863Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.667805Z",
+     "iopub.status.idle": "2026-09-15T16:07:08.669331Z",
+     "shell.execute_reply": "2026-09-15T16:07:08.668997Z"
     }
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    "outputs": [],
@@ -1542,10 +1542,10 @@
    "execution_count": 27,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.543962Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.543918Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.545616Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.545328Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.670163Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.670111Z",
+     "iopub.status.idle": "2026-09-15T16:07:08.671935Z",
+     "shell.execute_reply": "2026-09-15T16:07:08.671586Z"
     }
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    "outputs": [
@@ -1591,10 +1591,10 @@
    "execution_count": 28,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.546855Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.546804Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.582935Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.582710Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.672863Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.672801Z",
+     "iopub.status.idle": "2026-09-15T16:07:08.716205Z",
+     "shell.execute_reply": "2026-09-15T16:07:08.715908Z"
     }
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    "outputs": [
@@ -1632,10 +1632,10 @@
    "execution_count": 29,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.583845Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.583794Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.585450Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.585169Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.717063Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.717009Z",
+     "iopub.status.idle": "2026-09-15T16:07:08.718605Z",
+     "shell.execute_reply": "2026-09-15T16:07:08.718303Z"
     }
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    "outputs": [
@@ -1674,10 +1674,10 @@
    "execution_count": 30,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.586184Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.586139Z",
-     "iopub.status.idle": "2026-09-15T05:06:07.719872Z",
-     "shell.execute_reply": "2026-09-15T05:06:07.719502Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.719412Z",
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+     "shell.execute_reply": "2026-09-15T16:07:08.854825Z"
     }
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    "outputs": [
@@ -1749,10 +1749,10 @@
    "execution_count": 31,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:06:07.720781Z",
-     "iopub.status.busy": "2026-09-15T05:06:07.720725Z",
-     "iopub.status.idle": "2026-09-15T05:38:03.656079Z",
-     "shell.execute_reply": "2026-09-15T05:38:03.655696Z"
+     "iopub.execute_input": "2026-09-15T16:07:08.856225Z",
+     "iopub.status.busy": "2026-09-15T16:07:08.856162Z",
+     "iopub.status.idle": "2026-09-15T16:41:32.518297Z",
+     "shell.execute_reply": "2026-09-15T16:41:32.517999Z"
     }
    },
    "outputs": [
@@ -1776,7 +1776,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 14%|█▍        | 1/7 [00:48<04:51, 48.62s/it]"
+      " 14%|█▍        | 1/7 [00:50<05:03, 50.51s/it]"
      ]
     },
     {
@@ -1784,7 +1784,7 @@
      "output_type": "stream",
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       "\r",
-      " 29%|██▊       | 2/7 [03:09<08:33, 102.63s/it]"
+      " 29%|██▊       | 2/7 [03:17<08:57, 107.54s/it]"
      ]
     },
     {
@@ -1792,7 +1792,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [06:13<09:19, 139.86s/it]"
+      " 43%|████▎     | 3/7 [06:33<09:51, 147.85s/it]"
      ]
     },
     {
@@ -1800,7 +1800,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 57%|█████▋    | 4/7 [09:58<08:41, 173.72s/it]"
+      " 57%|█████▋    | 4/7 [10:33<09:12, 184.21s/it]"
      ]
     },
     {
@@ -1808,7 +1808,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 71%|███████▏  | 5/7 [14:19<06:50, 205.18s/it]"
+      " 71%|███████▏  | 5/7 [15:14<07:18, 219.09s/it]"
      ]
     },
     {
@@ -1816,7 +1816,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 86%|████████▌ | 6/7 [20:31<04:12, 252.17s/it]"
      ]
     },
     {
@@ -1824,7 +1824,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 7/7 [26:11<00:00, 281.02s/it]"
      ]
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     {
@@ -1832,7 +1832,7 @@
      "output_type": "stream",
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       "\r",
-      "100%|██████████| 7/7 [24:22<00:00, 208.89s/it]"
+      "100%|██████████| 7/7 [26:11<00:00, 224.50s/it]"
      ]
     },
     {
@@ -1862,7 +1862,7 @@
      "output_type": "stream",
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       "\r",
-      " 14%|█▍        | 1/7 [00:10<01:00, 10.07s/it]"
+      " 14%|█▍        | 1/7 [00:11<01:07, 11.19s/it]"
      ]
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     {
@@ -1870,7 +1870,7 @@
      "output_type": "stream",
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       "\r",
-      " 29%|██▊       | 2/7 [00:39<01:46, 21.28s/it]"
+      " 29%|██▊       | 2/7 [00:43<01:56, 23.39s/it]"
      ]
     },
     {
@@ -1878,7 +1878,7 @@
      "output_type": "stream",
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       "\r",
-      " 43%|████▎     | 3/7 [01:17<01:55, 28.97s/it]"
+      " 43%|████▎     | 3/7 [01:24<02:07, 31.78s/it]"
      ]
     },
     {
@@ -1886,7 +1886,7 @@
      "output_type": "stream",
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       "\r",
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+      " 57%|█████▋    | 4/7 [02:15<01:58, 39.40s/it]"
      ]
     },
     {
@@ -1894,7 +1894,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 71%|███████▏  | 5/7 [03:14<01:32, 46.43s/it]"
      ]
     },
     {
@@ -1902,7 +1902,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 86%|████████▌ | 6/7 [04:20<00:52, 52.89s/it]"
      ]
     },
     {
@@ -1910,7 +1910,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 7/7 [05:30<00:00, 58.53s/it]"
      ]
     },
     {
@@ -1918,7 +1918,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 7/7 [05:30<00:00, 47.20s/it]"
      ]
     },
     {
@@ -1948,7 +1948,7 @@
      "output_type": "stream",
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       "\r",
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+      " 14%|█▍        | 1/7 [00:03<00:19,  3.23s/it]"
      ]
     },
     {
@@ -1956,7 +1956,7 @@
      "output_type": "stream",
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       "\r",
-      " 29%|██▊       | 2/7 [00:11<00:31,  6.22s/it]"
+      " 29%|██▊       | 2/7 [00:12<00:34,  6.83s/it]"
      ]
     },
     {
@@ -1964,7 +1964,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [00:22<00:34,  8.59s/it]"
+      " 43%|████▎     | 3/7 [00:24<00:37,  9.35s/it]"
      ]
     },
     {
@@ -1972,7 +1972,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 57%|█████▋    | 4/7 [00:36<00:32, 10.75s/it]"
+      " 57%|█████▋    | 4/7 [00:40<00:34, 11.62s/it]"
      ]
     },
     {
@@ -1980,7 +1980,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 71%|███████▏  | 5/7 [00:53<00:25, 12.74s/it]"
+      " 71%|███████▏  | 5/7 [00:57<00:27, 13.74s/it]"
      ]
     },
     {
@@ -1988,7 +1988,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 86%|████████▌ | 6/7 [01:17<00:15, 15.74s/it]"
      ]
     },
     {
@@ -1996,7 +1996,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [01:30<00:00, 16.19s/it]"
+      "100%|██████████| 7/7 [01:38<00:00, 17.45s/it]"
      ]
     },
     {
@@ -2004,7 +2004,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [01:30<00:00, 12.98s/it]"
+      "100%|██████████| 7/7 [01:38<00:00, 14.02s/it]"
      ]
     },
     {
@@ -2034,7 +2034,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 14%|█▍        | 1/7 [00:01<00:08,  1.37s/it]"
      ]
     },
     {
@@ -2042,7 +2042,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 29%|██▊       | 2/7 [00:04<00:13,  2.60s/it]"
+      " 29%|██▊       | 2/7 [00:05<00:14,  2.80s/it]"
      ]
     },
     {
@@ -2050,7 +2050,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [00:09<00:14,  3.54s/it]"
+      " 43%|████▎     | 3/7 [00:10<00:15,  3.81s/it]"
      ]
     },
     {
@@ -2058,7 +2058,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 57%|█████▋    | 4/7 [00:15<00:13,  4.41s/it]"
+      " 57%|█████▋    | 4/7 [00:16<00:14,  4.74s/it]"
      ]
     },
     {
@@ -2066,7 +2066,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 71%|███████▏  | 5/7 [00:23<00:11,  5.61s/it]"
      ]
     },
     {
@@ -2074,7 +2074,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 86%|████████▌ | 6/7 [00:31<00:06,  6.43s/it]"
      ]
     },
     {
@@ -2082,7 +2082,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 7/7 [00:40<00:00,  7.14s/it]"
      ]
     },
     {
@@ -2090,7 +2090,7 @@
      "output_type": "stream",
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       "\r",
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+      "100%|██████████| 7/7 [00:40<00:00,  5.73s/it]"
      ]
     },
     {
@@ -2120,7 +2120,7 @@
      "output_type": "stream",
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       "\r",
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+      " 14%|█▍        | 1/7 [00:00<00:04,  1.29it/s]"
      ]
     },
     {
@@ -2128,7 +2128,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 29%|██▊       | 2/7 [00:02<00:07,  1.54s/it]"
+      " 29%|██▊       | 2/7 [00:03<00:08,  1.64s/it]"
      ]
     },
     {
@@ -2136,7 +2136,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 43%|████▎     | 3/7 [00:05<00:08,  2.10s/it]"
+      " 43%|████▎     | 3/7 [00:05<00:08,  2.24s/it]"
      ]
     },
     {
@@ -2144,7 +2144,7 @@
      "output_type": "stream",
      "text": [
       "\r",
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+      " 57%|█████▋    | 4/7 [00:09<00:08,  2.78s/it]"
      ]
     },
     {
@@ -2152,7 +2152,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 71%|███████▏  | 5/7 [00:12<00:06,  3.08s/it]"
+      " 71%|███████▏  | 5/7 [00:13<00:06,  3.28s/it]"
      ]
     },
     {
@@ -2160,7 +2160,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      " 86%|████████▌ | 6/7 [00:17<00:03,  3.53s/it]"
+      " 86%|████████▌ | 6/7 [00:18<00:03,  3.76s/it]"
      ]
     },
     {
@@ -2168,7 +2168,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [00:22<00:00,  3.91s/it]"
+      "100%|██████████| 7/7 [00:23<00:00,  4.18s/it]"
      ]
     },
     {
@@ -2176,7 +2176,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "100%|██████████| 7/7 [00:22<00:00,  3.14s/it]"
+      "100%|██████████| 7/7 [00:23<00:00,  3.36s/it]"
      ]
     },
     {
@@ -2245,10 +2245,10 @@
    "execution_count": 32,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:38:03.657011Z",
-     "iopub.status.busy": "2026-09-15T05:38:03.656955Z",
-     "iopub.status.idle": "2026-09-15T05:38:03.662162Z",
-     "shell.execute_reply": "2026-09-15T05:38:03.661822Z"
+     "iopub.execute_input": "2026-09-15T16:41:32.519343Z",
+     "iopub.status.busy": "2026-09-15T16:41:32.519285Z",
+     "iopub.status.idle": "2026-09-15T16:41:32.524660Z",
+     "shell.execute_reply": "2026-09-15T16:41:32.524311Z"
     }
    },
    "outputs": [],
@@ -2271,10 +2271,10 @@
    "execution_count": 33,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:38:03.663056Z",
-     "iopub.status.busy": "2026-09-15T05:38:03.663002Z",
-     "iopub.status.idle": "2026-09-15T05:38:03.808819Z",
-     "shell.execute_reply": "2026-09-15T05:38:03.808527Z"
+     "iopub.execute_input": "2026-09-15T16:41:32.525479Z",
+     "iopub.status.busy": "2026-09-15T16:41:32.525431Z",
+     "iopub.status.idle": "2026-09-15T16:41:32.669704Z",
+     "shell.execute_reply": "2026-09-15T16:41:32.669322Z"
     }
    },
    "outputs": [
@@ -2343,10 +2343,10 @@
    "execution_count": 34,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T05:38:03.809776Z",
-     "iopub.status.busy": "2026-09-15T05:38:03.809719Z",
-     "iopub.status.idle": "2026-09-15T10:22:26.179236Z",
-     "shell.execute_reply": "2026-09-15T10:22:26.178767Z"
+     "iopub.execute_input": "2026-09-15T16:41:32.670675Z",
+     "iopub.status.busy": "2026-09-15T16:41:32.670609Z",
+     "iopub.status.idle": "2026-09-16T19:15:41.444969Z",
+     "shell.execute_reply": "2026-09-16T19:15:41.444223Z"
     }
    },
    "outputs": [
@@ -2355,7 +2355,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+      "L=3, chi=128:   0%|          | 0/8 [00:00<?, ?it/s]"
      ]
     },
     {
@@ -2363,7 +2363,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  12%|█▎        | 1/8 [00:29<03:28, 29.79s/it]"
+      "L=3, chi=128:  12%|█▎        | 1/8 [01:23<09:47, 83.97s/it]"
      ]
     },
     {
@@ -2371,7 +2371,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  25%|██▌       | 2/8 [01:02<03:09, 31.66s/it]"
+      "L=3, chi=128:  25%|██▌       | 2/8 [02:52<08:40, 86.70s/it]"
      ]
     },
     {
@@ -2379,7 +2379,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  38%|███▊      | 3/8 [01:35<02:41, 32.30s/it]"
+      "L=3, chi=128:  38%|███▊      | 3/8 [04:20<07:16, 87.31s/it]"
      ]
     },
     {
@@ -2387,7 +2387,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  50%|█████     | 4/8 [02:09<02:10, 32.69s/it]"
+      "L=3, chi=128:  50%|█████     | 4/8 [05:50<05:53, 88.43s/it]"
      ]
     },
     {
@@ -2395,7 +2395,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  62%|██████▎   | 5/8 [02:43<01:39, 33.26s/it]"
+      "L=3, chi=128:  62%|██████▎   | 5/8 [07:23<04:29, 89.96s/it]"
      ]
     },
     {
@@ -2403,7 +2403,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  75%|███████▌  | 6/8 [03:17<01:07, 33.59s/it]"
+      "L=3, chi=128:  75%|███████▌  | 6/8 [08:56<03:01, 90.99s/it]"
      ]
     },
     {
@@ -2411,7 +2411,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64:  88%|████████▊ | 7/8 [03:54<00:34, 34.53s/it]"
+      "L=3, chi=128:  88%|████████▊ | 7/8 [10:35<01:33, 93.57s/it]"
      ]
     },
     {
@@ -2419,7 +2419,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [04:31<00:00, 35.54s/it]"
+      "L=3, chi=128: 100%|██████████| 8/8 [12:16<00:00, 96.10s/it]"
      ]
     },
     {
@@ -2427,7 +2427,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=3, chi=64: 100%|██████████| 8/8 [04:31<00:00, 33.97s/it]"
+      "L=3, chi=128: 100%|██████████| 8/8 [12:16<00:00, 92.10s/it]"
      ]
     },
     {
@@ -2442,7 +2442,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+      "L=5, chi=128:   0%|          | 0/8 [00:00<?, ?it/s]"
      ]
     },
     {
@@ -2450,7 +2450,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  12%|█▎        | 1/8 [07:20<51:20, 440.05s/it]"
+      "L=5, chi=128:  12%|█▎        | 1/8 [40:16<4:41:52, 2416.07s/it]"
      ]
     },
     {
@@ -2458,7 +2458,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  25%|██▌       | 2/8 [14:46<44:22, 443.74s/it]"
+      "L=5, chi=128:  25%|██▌       | 2/8 [1:22:48<4:09:36, 2496.16s/it]"
      ]
     },
     {
@@ -2466,7 +2466,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  38%|███▊      | 3/8 [22:12<37:04, 444.96s/it]"
+      "L=5, chi=128:  38%|███▊      | 3/8 [2:04:36<3:28:27, 2501.45s/it]"
      ]
     },
     {
@@ -2474,7 +2474,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  50%|█████     | 4/8 [29:44<29:50, 447.68s/it]"
+      "L=5, chi=128:  50%|█████     | 4/8 [2:47:13<2:48:15, 2523.76s/it]"
      ]
     },
     {
@@ -2482,7 +2482,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  62%|██████▎   | 5/8 [37:14<22:25, 448.45s/it]"
+      "L=5, chi=128:  62%|██████▎   | 5/8 [3:29:49<2:06:45, 2535.14s/it]"
      ]
     },
     {
@@ -2490,7 +2490,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  75%|███████▌  | 6/8 [44:45<14:58, 449.35s/it]"
+      "L=5, chi=128:  75%|███████▌  | 6/8 [4:14:13<1:25:57, 2578.86s/it]"
      ]
     },
     {
@@ -2498,7 +2498,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64:  88%|████████▊ | 7/8 [52:20<07:31, 451.12s/it]"
+      "L=5, chi=128:  88%|████████▊ | 7/8 [4:57:47<43:10, 2590.46s/it]  "
      ]
     },
     {
@@ -2506,7 +2506,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [59:58<00:00, 453.40s/it]"
+      "L=5, chi=128: 100%|██████████| 8/8 [5:39:30<00:00, 2562.54s/it]"
      ]
     },
     {
@@ -2514,7 +2514,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=5, chi=64: 100%|██████████| 8/8 [59:58<00:00, 449.82s/it]"
+      "L=5, chi=128: 100%|██████████| 8/8 [5:39:30<00:00, 2546.27s/it]"
      ]
     },
     {
@@ -2529,7 +2529,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:   0%|          | 0/8 [00:00<?, ?it/s]"
+      "L=7, chi=128:   0%|          | 0/8 [00:00<?, ?it/s]"
      ]
     },
     {
@@ -2537,7 +2537,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  12%|█▎        | 1/8 [27:30<3:12:33, 1650.55s/it]"
+      "L=7, chi=128:  12%|█▎        | 1/8 [2:38:11<18:27:23, 9491.96s/it]"
      ]
     },
     {
@@ -2545,7 +2545,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  25%|██▌       | 2/8 [54:59<2:44:58, 1649.81s/it]"
+      "L=7, chi=128:  25%|██▌       | 2/8 [5:14:41<15:43:10, 9431.76s/it]"
      ]
     },
     {
@@ -2553,7 +2553,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  38%|███▊      | 3/8 [1:22:24<2:17:18, 1647.64s/it]"
+      "L=7, chi=128:  38%|███▊      | 3/8 [7:50:21<13:02:29, 9389.95s/it]"
      ]
     },
     {
@@ -2561,7 +2561,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  50%|█████     | 4/8 [1:49:51<1:49:48, 1647.12s/it]"
+      "L=7, chi=128:  50%|█████     | 4/8 [10:25:20<10:23:35, 9353.95s/it]"
      ]
     },
     {
@@ -2569,7 +2569,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  62%|██████▎   | 5/8 [2:17:18<1:22:21, 1647.01s/it]"
+      "L=7, chi=128:  62%|██████▎   | 5/8 [12:59:27<7:45:46, 9315.51s/it] "
      ]
     },
     {
@@ -2577,7 +2577,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  75%|███████▌  | 6/8 [2:44:43<54:53, 1646.51s/it]  "
+      "L=7, chi=128:  75%|███████▌  | 6/8 [15:32:59<5:09:20, 9280.04s/it]"
      ]
     },
     {
@@ -2585,7 +2585,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64:  88%|████████▊ | 7/8 [3:12:11<27:26, 1646.84s/it]"
+      "L=7, chi=128:  88%|████████▊ | 7/8 [18:07:00<2:34:27, 9267.56s/it]"
      ]
     },
     {
@@ -2593,7 +2593,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [3:39:51<00:00, 1651.01s/it]"
+      "L=7, chi=128: 100%|██████████| 8/8 [20:42:20<00:00, 9284.21s/it]  "
      ]
     },
     {
@@ -2601,7 +2601,7 @@
      "output_type": "stream",
      "text": [
       "\r",
-      "L=7, chi=64: 100%|██████████| 8/8 [3:39:51<00:00, 1648.88s/it]"
+      "L=7, chi=128: 100%|██████████| 8/8 [20:42:20<00:00, 9317.60s/it]"
      ]
     },
     {
@@ -2635,7 +2635,7 @@
     "# Parameters. The decoder's bias is the channel's rate at every point.\n",
     "tolerances = [0]\n",
     "cuts = [0]\n",
-    "max_bond_dims = [64]\n",
+    "max_bond_dims = [128]\n",
     "error_rates = (\n",
     "    [0.08, 0.10, 0.13]\n",
     "    if FAST\n",
@@ -2705,10 +2705,10 @@
    "execution_count": 35,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T10:22:26.180407Z",
-     "iopub.status.busy": "2026-09-15T10:22:26.180305Z",
-     "iopub.status.idle": "2026-09-15T10:22:26.189519Z",
-     "shell.execute_reply": "2026-09-15T10:22:26.189171Z"
+     "iopub.execute_input": "2026-09-16T19:15:41.446827Z",
+     "iopub.status.busy": "2026-09-16T19:15:41.446424Z",
+     "iopub.status.idle": "2026-09-16T19:15:41.459592Z",
+     "shell.execute_reply": "2026-09-16T19:15:41.459192Z"
     }
    },
    "outputs": [
@@ -2718,12 +2718,12 @@
      "text": [
       "logical error rate (standard error) per lattice size and rate\n",
       "p                 0.080           0.090           0.095           0.100           0.105           0.110           0.120           0.130\n",
-      "L=3       0.1053(0.0056)   0.1233(0.0060)   0.1203(0.0059)   0.1360(0.0063)   0.1483(0.0065)   0.1457(0.0064)   0.1840(0.0071)   0.2133(0.0075)\n",
-      "L=5       0.0870(0.0051)   0.1083(0.0057)   0.1243(0.0060)   0.1383(0.0063)   0.1473(0.0065)   0.1570(0.0066)   0.2123(0.0075)   0.2367(0.0078)\n",
-      "L=7       0.0707(0.0047)   0.1107(0.0057)   0.1247(0.0060)   0.1383(0.0063)   0.1523(0.0066)   0.1890(0.0071)   0.2283(0.0077)   0.2783(0.0082)\n",
-      "L=3 and L=5: fitted crossing p = 0.0992 +/- 0.0030 (slope 0.961); sign changes of the gap on the grid: 0.0939, 0.1035, 0.1054; exact ties at: none\n",
+      "L=3       0.1053(0.0056)   0.1233(0.0060)   0.1203(0.0059)   0.1387(0.0063)   0.1483(0.0065)   0.1463(0.0065)   0.1843(0.0071)   0.2143(0.0075)\n",
+      "L=5       0.0880(0.0052)   0.1103(0.0057)   0.1227(0.0060)   0.1317(0.0062)   0.1420(0.0064)   0.1573(0.0066)   0.2000(0.0073)   0.2297(0.0077)\n",
+      "L=7       0.0690(0.0046)   0.1083(0.0057)   0.1217(0.0060)   0.1333(0.0062)   0.1517(0.0065)   0.1770(0.0070)   0.2117(0.0075)   0.2577(0.0080)\n",
+      "L=3 and L=5: fitted crossing p = 0.1034 +/- 0.0040 (slope 0.724); sign changes of the gap on the grid: 0.0942, 0.0963, 0.1068; exact ties at: none\n",
       "  -> no unique crossing on the grid; only the fit is reported\n",
-      "L=5 and L=7: fitted crossing p = 0.0940 +/- 0.0030 (slope 1.044); sign changes of the gap on the grid: 0.0887; exact ties at: 0.100\n",
+      "L=5 and L=7: fitted crossing p = 0.0968 +/- 0.0033 (slope 0.888); sign changes of the gap on the grid: 0.0969; exact ties at: none\n",
       "Every shot decoded; no failure was counted from a raised decode.\n"
      ]
     }
@@ -2829,16 +2829,16 @@
    "execution_count": 36,
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-09-15T10:22:26.190328Z",
-     "iopub.status.busy": "2026-09-15T10:22:26.190273Z",
-     "iopub.status.idle": "2026-09-15T10:22:26.367379Z",
-     "shell.execute_reply": "2026-09-15T10:22:26.367022Z"
+     "iopub.execute_input": "2026-09-16T19:15:41.460442Z",
+     "iopub.status.busy": "2026-09-16T19:15:41.460372Z",
+     "iopub.status.idle": "2026-09-16T19:15:41.760487Z",
+     "shell.execute_reply": "2026-09-16T19:15:41.760103Z"
     }
    },
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 350x300 with 1 Axes>"
       ]

From 91b88ee9ab57a41cb28d1d7a24e1a99e85751692 Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Wed, 16 Sep 2026 15:19:53 -0400
Subject: [PATCH 14/15] Match the surface-code narrative to the chi_max = 128
 sweep

The sweep cell now runs at chi_max = 128, so cell 56 says so and gives
this run's times (twelve minutes for L = 3, five and a half hours for
L = 5, twenty and three-quarter hours for L = 7 on eight workers).

The closing text follows the regenerated table: the rates at p = 0.08,
which sizes agree within errors around the crossing, the L = 5/L = 7
gaps, and the fitted crossings, now 9.7 +/- 0.3% for L = 5/L = 7 and
10.3 +/- 0.4% for L = 3/L = 5. The first still sits below the
literature band; the second reaches into it. Doubling chi moved both by
less than one standard error, which the truncation paragraph now says.

notebook_pipeline.rst and the notebooks workflow comment carry the new
runtimes: quantum_surface 27.4 h, the suite about 34 h.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 .github/workflows/notebooks.yml         | 2 +-
 docs/source/notebook_pipeline.rst       | 4 ++--
 examples/decoding/quantum_surface.ipynb | 8 ++++----
 3 files changed, 7 insertions(+), 7 deletions(-)

diff --git a/.github/workflows/notebooks.yml b/.github/workflows/notebooks.yml
index 323371ac..f6c6fd5d 100644
--- a/.github/workflows/notebooks.yml
+++ b/.github/workflows/notebooks.yml
@@ -5,7 +5,7 @@ name: notebooks
 # nothing ran these.
 #
 # MDOPT_NB_FAST=1 shrinks the workloads: at the committed full-scale settings
-# the suite totals roughly 12 hours (quantum_surface ~5.5h, maxbonddim ~3.2h,
+# the suite totals roughly 34 hours (quantum_surface ~27h, maxbonddim ~3.2h,
 # classical_ldpc ~2.8h -- see docs/source/notebook_pipeline.rst), past the 6h
 # GitHub caps a job at and far too dear to spend per pull request. The
 # notebooks read that variable themselves. What is being tested is that they
diff --git a/docs/source/notebook_pipeline.rst b/docs/source/notebook_pipeline.rst
index e5bd7bbc..03b3a3d9 100644
--- a/docs/source/notebook_pipeline.rst
+++ b/docs/source/notebook_pipeline.rst
@@ -51,7 +51,7 @@ follow once it is merged.
 the longest cells below run for hours, so a full regeneration needs a larger
 limit; the last one used a day.
 
-Expect this to take hours: the last full run took about 12 hours. Measured on
+Expect this to take hours: the last full run took about 34 hours. Measured on
 an M-series laptop (10 cores: 4 performance, 6 efficiency), one notebook at a
 time, with one BLAS thread per process:
 
@@ -67,7 +67,7 @@ notebook                     full run
 ``quantum_three_qubit``      4.6 min
 ``classical_ldpc``           2.8 h (the truncation sweep 2.2 h, the BP comparison 36 min)
 ``maxbonddim``               3.2 h
-``quantum_surface``          5.5 h (the threshold sweep alone 4.7 h)
+``quantum_surface``          27.4 h (the threshold sweep alone 26.6 h, at chi_max = 128)
 ===========================  ==============================================================
 
 ``classical_ldpc`` and ``quantum_surface`` end with a cell that regenerates
diff --git a/examples/decoding/quantum_surface.ipynb b/examples/decoding/quantum_surface.ipynb
index 9c2c7e37..82fdb7f4 100644
--- a/examples/decoding/quantum_surface.ipynb
+++ b/examples/decoding/quantum_surface.ipynb
@@ -2335,7 +2335,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, the bond dimension at which the $L = 3$ sweep above is converged ($\\chi_{\\max} = 64$), a grid that is dense around the crossing, and enough shots to resolve it. Whether $L = 7$ is converged at this bond dimension is not established by the sweep above (its MPOs have more leg crossings than those of $L = 3$), and the discussion after the plot comes back to this. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which keeps $\\chi = 64$ about as cheap as $\\chi = 20$ in the natural order, and the shots run in parallel through the campaign worker. Note, this cell takes about four and three-quarter hours at full scale on eight worker processes (four and a half minutes for $L = 3$, one hour for $L = 5$, three hours and forty minutes for $L = 7$).\n"
+    "Let us now look at what happens if we scale the system, and locate the threshold: the physical error rate below which a larger code protects better and above which it protects worse. Three lattice sizes, twice the bond dimension at which the $L = 3$ sweep above is converged ($\\chi_{\\max} = 128$), a grid that is dense around the crossing, and enough shots to resolve it. Whether $L = 7$ is converged at this bond dimension is not established by the sweep above (its MPOs have more leg crossings than those of $L = 3$), and the discussion after the plot comes back to this. The decoder's prior is matched to the channel at every rate (`bias_prob = p`), which is what a threshold measurement calls for; a fixed prior would make the decoder optimal at one rate only and drag the crossing towards it. The qubits are ordered along the chain by reverse Cuthill-McKee (`qubit_order_strategy=\"Optimised\"`), which cuts the cost of a given bond dimension sharply (at $\\chi = 64$ it cost about what $\\chi = 20$ costs in the natural order), and the shots run in parallel through the campaign worker. Note, this cell takes about twenty-seven hours at full scale on eight worker processes (twelve minutes for $L = 3$, five and a half hours for $L = 5$, twenty and three-quarter hours for $L = 7$).\n"
    ]
   },
   {
@@ -2898,11 +2898,11 @@
    "id": "b0dda13e",
    "metadata": {},
    "source": [
-    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 7.1%, $L = 5$ at 8.7%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, and at $p = 0.095$ and $0.10$ all three coincide within their errors. Above $p = 0.10$ the larger code fails more often at every rate except $p = 0.105$, where $L = 5$ fails slightly less often than $L = 3$ (14.7% against 14.8%), but the separation does not grow steadily: the $L = 5$/$L = 7$ gap is 3.2 percentage points at $p = 0.11$, 1.6 at $p = 0.12$ and 4.2 at $p = 0.13$. The reversal itself is clear; its size from one rate to the next is at the level of the statistical errors. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
+    "At the lowest rate the sizes are in the order a threshold plot expects: at $p = 0.08$ the larger code fails less often ($L = 7$ at 6.9%, $L = 5$ at 8.8%, $L = 3$ at 10.5%). By $p = 0.09$ the $L = 5$ and $L = 7$ curves have met, and at $p = 0.095$, $0.10$ and $0.105$ all three agree within their errors. From $p = 0.11$ on, the larger code fails more often at every rate; at $p = 0.105$ itself $L = 5$ still fails slightly less often than $L = 3$ (14.2% against 14.8%). The separation does not grow steadily: the $L = 5$/$L = 7$ gap is 2.0 percentage points at $p = 0.11$, 1.2 at $p = 0.12$ and 2.8 at $p = 0.13$. The reversal itself is clear; its size from one rate to the next is at the level of the statistical errors. The logarithmic axis is what makes the low-$p$ separation visible; on a linear axis it collapses into the origin.\n",
     "\n",
-    "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.4 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points. For $L = 5$/$L = 7$ the difference turns positive between $p = 0.08$ and $0.09$, stays within half a percentage point of zero up to $p = 0.105$, and is exactly zero at $p = 0.10$; for $L = 3$/$L = 5$ it changes sign three times. With standard errors of 0.5 to 0.8 percentage points per point, a single interpolated crossing would be an arbitrary choice, so the fit is used instead.\n",
+    "The threshold estimate this notebook can make is the crossing of the two largest sizes. The aggregation cell fits a weighted line through the difference of their logical error rates over the whole grid and prints the root with its uncertainty: $9.7 \\pm 0.3\\%$ for $L = 5$/$L = 7$, drawn as the dotted line with its uncertainty band. It also lists where the raw difference changes sign between grid points. For $L = 5$/$L = 7$ it changes sign once, between $p = 0.095$ and $0.10$, and stays within one percentage point of zero from $p = 0.09$ to $0.105$; for $L = 3$/$L = 5$ it changes sign three times. With standard errors of 0.5 to 0.8 percentage points per point, a single interpolated crossing would be an arbitrary choice, so the fit is used instead.\n",
     "\n",
-    "The estimate sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%. The $L = 3$/$L = 5$ crossing ($9.9 \\pm 0.3\\%$) is higher than the $L = 5$/$L = 7$ one, and the two intervals overlap, so this run does not resolve a finite-size drift in either direction. The shortfall is not explained by truncation: a same-shot comparison at $L = 7$, run outside this notebook with the same noise, prior and qubit ordering, found no significant change in the failure rate between $\\chi_{\\max} = 64$, $128$ and $256$ at $p = 0.10$ and $0.11$. The same comparison found the decoder sensitive to its prior at $\\chi_{\\max} = 64$: at $L = 7$ and $p = 0.11$ a prior of $0.03$ failed on 158 of 1000 shots against 189 for the matched prior. Why the matched prior loses to a sharper one here is not yet understood, and it is the next thing to examine.\n",
+    "The $L = 5$/$L = 7$ estimate still sits below the shaded literature band for the code-capacity bit-flip threshold of the surface code, which runs from the minimum-weight-matching value of 10.3% to the optimal-decoding value of 10.9%; its interval reaches 10.0%. The $L = 3$/$L = 5$ crossing ($10.3 \\pm 0.4\\%$) is higher, its interval reaches into the band, and the two intervals overlap, so this run does not resolve a finite-size drift in either direction. Truncation explains little of the shortfall. This sweep runs at $\\chi_{\\max} = 128$, twice the bond dimension of the earlier one, and both crossings moved up by less than one standard error: by 0.3 percentage points for $L = 5$/$L = 7$ and 0.4 for $L = 3$/$L = 5$. A same-shot comparison at $L = 7$, run outside this notebook with the same noise, prior and qubit ordering, likewise found no significant change in the failure rate between $\\chi_{\\max} = 64$, $128$ and $256$ at $p = 0.10$ and $0.11$. The same comparison found the decoder sensitive to its prior at $\\chi_{\\max} = 64$: at $L = 7$ and $p = 0.11$ a prior of $0.03$ failed on 158 of 1000 shots against 189 for the matched prior. Why the matched prior loses to a sharper one here is not yet understood, and it is the next thing to examine.\n",
     "\n",
     "A shot whose decode raises is counted as a failure rather than dropped, and the aggregation cell prints how many there were, so a curve can only be pessimistic about such shots, never flattered by them.\n"
    ]

From 836b926513eba497591b48ebf34a6697e49f806d Mon Sep 17 00:00:00 2001
From: meandmytram <berezutskii.aleksandr@gmail.com>
Date: Wed, 16 Sep 2026 15:30:32 -0400
Subject: [PATCH 15/15] Raise the documented per-cell timeout above the
 measured sweep

The full-scale example passed --timeout 86400, which is 24 h, while the
surface-code threshold sweep now takes 26.6 h in one cell, so following
the docs would abort a regeneration near its end. Both the pipeline page
and the script's usage text now pass 172800 (48 h), the value the last
full run actually used, and name the sweep's duration.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01S6mbxc9eJDQMVx7tjvYwud
---
 docs/source/notebook_pipeline.rst | 7 ++++---
 scripts/run_notebooks.py          | 7 ++++---
 2 files changed, 8 insertions(+), 6 deletions(-)

diff --git a/docs/source/notebook_pipeline.rst b/docs/source/notebook_pipeline.rst
index 03b3a3d9..70f438d1 100644
--- a/docs/source/notebook_pipeline.rst
+++ b/docs/source/notebook_pipeline.rst
@@ -39,7 +39,7 @@ Regenerating the results
 
 .. code-block:: bash
 
-   python scripts/run_notebooks.py --inplace --timeout 86400    # all of them
+   python scripts/run_notebooks.py --inplace --timeout 172800   # all of them
    python scripts/run_notebooks.py --inplace examples/decoding/shor.ipynb
 
 ``--inplace`` writes the executed outputs back into the notebook. Commit the
@@ -48,8 +48,9 @@ follow once it is merged.
 
 ``--timeout`` is the limit per cell, in seconds. Its default of 1800 (or
 ``MDOPT_NB_TIMEOUT``, if set) suits the fast CI workloads, but at full scale
-the longest cells below run for hours, so a full regeneration needs a larger
-limit; the last one used a day.
+the longest cells below run for hours -- the surface-code threshold sweep
+alone took 26.6 h -- so a full regeneration needs a limit well above that;
+the last one allowed two days.
 
 Expect this to take hours: the last full run took about 34 hours. Measured on
 an M-series laptop (10 cores: 4 performance, 6 efficiency), one notebook at a
diff --git a/scripts/run_notebooks.py b/scripts/run_notebooks.py
index 6c555dfe..312f34a6 100644
--- a/scripts/run_notebooks.py
+++ b/scripts/run_notebooks.py
@@ -25,11 +25,12 @@
     python scripts/run_notebooks.py                 # every eligible notebook
     python scripts/run_notebooks.py path/to/nb.ipynb
     MDOPT_NB_FAST=1 python scripts/run_notebooks.py  # CI-scale workloads
-    python scripts/run_notebooks.py --inplace --timeout 86400  # full-scale results
+    python scripts/run_notebooks.py --inplace --timeout 172800  # full-scale results
 
 At full scale several cells run for hours, far past the default per-cell
-timeout of 1800 s (``--timeout``, or ``MDOPT_NB_TIMEOUT``), so a full run
-needs a larger one; docs/source/notebook_pipeline.rst lists the times.
+timeout of 1800 s (``--timeout``, or ``MDOPT_NB_TIMEOUT``); the surface-code
+threshold sweep alone takes 26.6 h, so a full run needs a limit well above
+that. docs/source/notebook_pipeline.rst lists the times.
 """
 
 from __future__ import annotations