UUON Foundation Inc. — Phillip Aguilar Ruiz III
Perception before compression. The prefrontal cortex of clouud.
Originally conceived and documented as ψcience, using the Greek letter ψ (psi) — the standard symbol for the quantum wavefunction, the state of a system before measurement collapses it to a single value. The substitution ψ = ps is phonetically exact: ψcience reads identically to "science" while encoding the mechanism in the symbol.
The repository name pscience-perception-engine was adopted because GitHub does not permit the ψ character in repository names. The conceptual identity is unchanged. All internal documentation, academic records, and clouud API references preserve ψcience as the original name.
Original name: ψcience
Repository name: pscience-perception-engine
Reason: GitHub repository name character restriction — ψ not permitted
Date of substitution: 2025-08-02 UTC
All documents updated: confirmed
clouud is a living computational system. Each engine fills a biological function structurally, not metaphorically. The mathematics governing biological systems and these engines is the same mathematics.
Every engine currently in clouud either generates form (WFE, Kleinian, Pythagorean), tracks state (Propagation Engine), enforces binary boundaries (BSE), or routes signal (uuon-clouud spine). None of them reason about what generated form means before committing to an output. The system generates and routes — but it has no layer that holds competing interpretations open while evaluating them against each other.
pscience is the first engine in clouud that operates on interpretation rather than form.
It doesn't generate geometry. It evaluates what geometry other engines produce. The moiré interference fringe rendered by the visual layer is exactly what happens when two candidate interpretations of the same signal overlap: the bright fringe is where they agree, the dark band is where they cancel. This is not a visual metaphor — it is the interference equation rendered directly.
| Biological system | clouud component | Status |
|---|---|---|
| Prefrontal cortex / executive reasoning | pscience | Accepted — implementation in progress |
| Visual cortex | Recursive Fractal Engine | Live — /api/fractal active |
| Proprioception | Propagation Engine | Built — not yet wired to clouud |
| Decision layer | Boundary State Engine | Built — not yet wired to clouud |
| Skeleton | Wave Field 3D Engine | Live |
| Spine / CNS | uuon-clouud routing | Live |
| Immune system | USAL-1.0 + gitleaks + NOTICE | Live |
| Trabecular bone | Kleinian-Hybrid IFS Engine | Built — non-manifold edges pending |
| Vascular branching | Pythagorean Graph Engine | Live |
The prefrontal cortex is the only biological system that delays commitment while simultaneously holding active interpretations in competition. Every other organ in clouud is reactive. The PFC is the only one that holds. This makes pscience structurally prior to any output decision clouud makes — it must sit in the pipeline before the compression layer fires.
| Symbol | Name | Definition | This Engine |
|---|---|---|---|
| P | Parameters | Minimal seed | 7 P-dimensions + collapse threshold τ — ~56 bytes |
| E | Encoding | Deterministic expansion | ψ(P) = Σᵢ αᵢ|hᵢ⟩ — superposition of N hypothesis candidates |
| M | Mapping | Translation chain | hypothesis graph → entropy rank → invariant detection → Φ(τ) collapse selector |
| R | Representation | Output format | Hypothesis graph JSON, ranked candidate set, collapsed reasoning proof |
| C | Compression | Ratio R/P | P=56B → R≈4–40KB → C≈70:1 to 700:1 (pre-clouud compression) |
ψ(P) = Σᵢ αᵢ|hᵢ⟩ — all hypotheses held open simultaneously
H(ψ) = −Σ pᵢ log₂ pᵢ — Shannon field entropy across hypothesis set
I(h) = Σ M(hᵢ,hⱼ) · S(hᵢ) — information density score per candidate
Φ(τ) = argmax[I(h)] · e^−H(ψ)τ — collapse: high entropy slows commitment
M(h,h') = |⟨h|h'⟩|² — hypothesis overlap matrix
S(h) = BSE_H(h) · η — Boltzmann efficiency rank from BSE engine
Each P-dimension is a distinct computational lens. Every dimension applies a pre() transform to coordinates before the wave is sampled, and a post() transform to the output value after. This gives each dimension its own physical character grounded in a real law.
| Dimension | Symbol | Pre-transform | Post-transform | Physical law |
|---|---|---|---|---|
| Perception | Pₚ | identity — raw signal | √|f| |
Weber-Fechner law — logarithmic sensory compression |
| Pattern | Pₐ | |x|, |y| — bilateral fold |
f² — power law |
Bilateral symmetry + threshold detection |
| Perspective | Pᵥ | x/(1+d·y/H) — projective |
identity | Perspective projection — actual horizon recession |
| Probability | Pᵦ | identity | ½(1+erf(f·σ)) |
Born rule — amplitude → probability density |
| Provenance | Pₒ | log(1+r)·r̂ — log-radial |
f·(1−e^{−r/λ}) |
Logarithmic distance decay, origin suppression |
| Projection | Pⱼ | x+s·y — oblique shear |
∂f/∂x finite diff |
Future state = gradient of current field |
| Process | Pᵈ | rotate by ωt |
sign(f)·|f|^0.6 |
Nonlinear logic gate, time-rotating frame |
What each produces visually and why it is that character:
- Pₚ Perception — soft field, edges feathered. Weak signals emerge from noise rather than clipping at zero. This is what unmediated observation does.
- Pₐ Pattern — quadrant symmetry plus sharp fringe edges. Power law enforces threshold: things either match or they don't.
- Pᵥ Perspective — all fringes converge to a horizon. The field recedes spatially. No post needed — geometry is the character.
- Pᵦ Probability — field reads as probability density map, grainy-to-saturated gradient. Born rule applied iteratively per frame.
- Pₒ Provenance — concentric rings of decreasing authority radiating from origin. History dominates the center, weakens at distance.
- Pⱼ Projection — edges and transitions visible, not fringes. You see the velocity of the field, not its position. Derivative of sine = cosine, 90° phase shifted.
- Pᵈ Process — rotating field with hard-edged but unclipped geometry. Compressive nonlinear gate. Deterministic path, nonlinear output.
INPUT
↓
pscience — expansion layer
├─ Pₚ Pattern discovery (perception)
├─ Pₐ Structural symmetry detection (pattern)
├─ Pᵥ Multi-frame perspective evaluation
├─ Pᵦ Probability density ranking (Born rule)
├─ Pₒ Provenance mapping per candidate
├─ Pⱼ Future state projection (gradient)
└─ Pᵈ Deterministic process gate
↓
Φ(τ) = argmax[I(h)] · e^−H(ψ)τ — collapse to best candidates
↓
clouud — semantic compression
↓
Compact reasoning proof → Verification → Publication
| Engine | What pscience reads |
|---|---|
| Propagation Engine | Activation field as expansion substrate — ~62% equilibrium maps to stable superposition state |
| Boundary State Engine | Shannon H + Boltzmann η ranks competing hypotheses by information density |
| Recursive Fractal Engine | Quantum generators 14 + 15 — Born rule p=|ψ|² iteratively applied |
| Wave Field 3D Engine | WFE_surfCoord() for geometric invariant detection across candidate interpretations |
| Component | Location | Visibility |
|---|---|---|
| Hypothesis graph engine | core/pscience-pipeline.js |
PROPRIETARY — .gitignored, served from uuon.world |
| Invariant detector | core/pscience-invariants.js |
PROPRIETARY — .gitignored |
| Provenance recorder | core/pscience-provenance.js |
PROPRIETARY — .gitignored |
| P-dimension pre/post functions | index.html shell |
PUBLIC — fallback renderer |
| API surface | api/README.md |
PUBLIC |
| Origin record | docs/pscience-perception-engine.docx |
PUBLIC |
| Pipeline diagram | docs/pscience-clouud-pipeline.svg |
PUBLIC |
| Academic record | docs/ACADEMIC-RECORD.md |
PUBLIC |
Core served from https://uuon.world/engine/pscience/core.js.
| Field | Value |
|---|---|
| Org | UUON-Foundation |
| Repo | pscience-perception-engine |
| Remote | git@github.com:UUON-Foundation/pscience-perception-engine.git |
| Branch | main |
| Pages | https://uuon-foundation.github.io/pscience-perception-engine/ |
| npm | @uuon-foundation/pscience-perception-engine |
| Engine core | https://uuon.world/engine/pscience/core.js (in progress) |
USAL-1.0 — UUON Source Attribution License
Author: Phillip Aguilar Ruiz III
Contact: phi1@uuonfoundation.com
Attribution required. AI training use prohibited.