repeated coarse graining

.github/workflows/publish.yaml

@@ -0,0 +1,34 @@
+name: Publish qemcmc to PyPI
+
+on:
+  push:
+    tags:
+      - "v*"
+
+jobs:
+  publish:
+    runs-on: ubuntu-latest
+
+    environment:
+      name: pypi
+
+    permissions:
+      id-token: write  # for trusted publishing
+
+    steps:
+      - uses: actions/checkout@v4
+        with:
+          fetch-depth: 0
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.13"
+
+      - name: Install build tool
+        run: pip install build
+
+      - name: Build
+        run: python -m build
+
+      - name: Publish
+        uses: pypa/gh-action-pypi-publish@release/v1

docs/source/github.md

@@ -0,0 +1,3 @@
+# Github
+
+The source code for QeMCMC can be found at [https://github.com/Stuartferguson00/QeMCMC](https://github.com/Stuartferguson00/QeMCMC). Contributions are welcome, and you can submit issues or pull requests to help improve the project. Please refer to the repository's README and contribution guidelines for more information on how to get involved.

docs/source/index.md

@@ -32,6 +32,7 @@ api/index
 :maxdepth: 2
 :caption: Development
 
+github
 license
 authors
 ```

pyproject.toml

@@ -1,9 +1,11 @@
 [project]
 name = "qemcmc"
-version = "0.0.0"
+# version = "0.0.0"
+dynamic = ["version"]
 description = "Quantum enhanced Markov Chain Monte Carlo sampler simulated using PennyLane"
 readme = "README.md"
 authors = [{ name = "Stuart Ferguson" }, { name = "Feroz Hassan" }]
+license = { text = "MIT" }
 requires-python = ">=3.13"
 dependencies = [
     "joblib>=1.5.0",
@@ -26,5 +28,10 @@ dependencies = [
 qemcmc = "qemcmc:main"
 
 [build-system]
-requires = ["setuptools>=61.0", "wheel"]
+requires = ["setuptools>=61.0", "wheel", "setuptools-scm"]
 build-backend = "setuptools.build_meta"
+
+[tool.setuptools_scm]
+
+[tool.setuptools.packages.find]
+where = ["src"]

src/qemcmc/circuits.py

@@ -72,6 +72,7 @@ def get_problem_hamiltonian(self, couplings, sign=-1):
             if order == 0:
                 continue
             spin_sign = (-1) ** order
+
             non_zero_indices = np.transpose(np.nonzero(coupling_tensor))
             for index_tuple in non_zero_indices:
                 index_tuple = tuple(int(i) for i in index_tuple)
@@ -102,14 +103,17 @@ def get_mixer_hamiltonian(self, num_wires: int = None):
 
     def get_state_vector(self, s: str) -> str:
         """Return the state vector."""
+        num_wires = len(s)
+        dev = self._get_device(num_wires)
+
         # Coefficients
         alpha = self.model.calculate_alpha(couplings=self.local_couplings)
         coeff_mixer = self.gamma
         coeff_problem = -(1 - self.gamma) * alpha
 
-        H_total = qml.Hamiltonian([coeff_mixer] + [1.0], [self.get_mixer_hamiltonian(), self.get_problem_hamiltonian(couplings=self.local_couplings, sign=coeff_problem)])
+        H_total = qml.Hamiltonian([coeff_mixer] + [1.0], [self.get_mixer_hamiltonian(num_wires), self.get_problem_hamiltonian(couplings=self.local_couplings, sign=coeff_problem)])
 
-        @qml.qnode(self.dev)
+        @qml.qnode(dev)
         def quantum_evolution(input_string):
             for i, bit in enumerate(input_string):
                 if bit == "1":