Update TECHNICAL_NOTES.md

TECHNICAL_NOTES.md

@@ -1,67 +1,76 @@
-# RFT-Ω Harmonic Validation Interface — v3
+Rendered Frame Theory — Stabilising System Verification Panel
 
-Interactive demonstrator for **Rendered Frame Theory (RFT)** harmonic stability under controlled synthetic noise.  
-This Space provides a **reproducible test harness** for anticipatory stability (QΩ) and synchronization coherence (ζ_sync) with:
-- **Domain profiles** (AI/Neural, SpaceX/Aerospace, Energy/RHES, Extreme)
-- **Adjustable noise slider (σ)** to probe robustness
-- **Adaptive baselines** (light “memory”) and **range validation** (no false 1.0 spikes)
+Interactive verification panel for Rendered Frame Theory (RFT) harmonic stability under controlled synthetic noise.
+This Space is a reproducible test harness for anticipatory stability (QΩ) and synchronisation coherence (ζ_sync) across multiple domains.
+	•	Domains: AI/Neural, SpaceX/Aerospace, Energy/RHES, Extreme Perturbation
+	•	Noise control: slider for σ (0.00–0.30) to probe robustness
+	•	Outputs: JSON with mean QΩ / ζ_sync, status classification, and timestamp
+	•	Logging: Save Run Log downloads a timestamped .json record for audit trails
+	•	Reference DOI: https://doi.org/10.5281/zenodo.17466722
 
----
+Live panel: https://rftsystems-rft-omega-api.hf.space
 
-## How to Use
-1) Open the Space → **https://rftsystems-rft-omega-api.hf.space**  
-2) Select a **System Profile** (AI/Neural, SpaceX/Aerospace, Energy/RHES, Extreme Perturbation).  
-3) Adjust **Synthetic Noise Level (σ)** with the slider (0.00–0.30).  
-4) Click **Submit** → JSON output appears with live values for QΩ, ζ_sync, status.
+⸻
 
-**Example output**
-```json
-{
-  "System": "AI / Neural",
-  "Noise Scale": 0.050,
-  "QΩ": 0.922,
-  "ζ_sync": 0.798,
-  "status": "perturbed"
-}
-```
-
----
+How to Use
+	1.	Open the panel → https://rftsystems-rft-omega-api.hf.space
+	2.	Select a System Profile (AI/Neural, SpaceX/Aerospace, Energy/RHES, Extreme Perturbation).
+	3.	Choose Noise Distribution (gauss or uniform).
+	4.	Adjust Synthetic Noise (σ) with the slider (0.00–0.30).
+	5.	Click Run Simulation → JSON output appears with live QΩ/ζ_sync and status.
+	6.	Click 💾 Save Run Log to download the result as a .json (timestamped).
 
-## What to Expect
+    Example output
+    {
+  "profile": "AI / Neural",
+  "noise_scale": 0.080,
+  "distribution": "gauss",
+  "QΩ_mean": 0.834,
+  "ζ_sync_mean": 0.799,
+  "status_majority": "perturbed",
+  "timestamp_utc": "2025-10-29T14:04:05.114382Z",
+  "rft_notice": "All Rights Reserved — RFT-IPURL v1.0 (UK / Berne). Research validation use only. No reverse-engineering without written consent."
+}
+What to Expect
 
-**Typical stable ranges (nominal conditions)**
-| Metric | Range | Meaning |
-|---|---|---|
-| **QΩ** | 0.82–0.89 | Harmonic stability factor (amplitude) |
-| **ζ_sync** | 0.75–0.88 | Synchronization coherence (phase) |
+Typical stable ranges (nominal conditions)
+Metric
+Range
+Meaning
+QΩ
+0.82–0.89
+Harmonic stability factor (amplitude)
+ζ_sync
+0.75–0.88
+Synchronisation coherence (phase)
+Status classification (qualitative)
+	•	nominal — low variance; coherent equilibrium
+	•	perturbed — moderate variance; coherent but stressed
+	•	critical — high variance; edge-of-instability
 
-**Status classification (qualitative)**
-- `nominal` — low variance; coherent equilibrium  
-- `perturbed` — moderate variance; coherent but stressed  
-- `critical` — high variance; edge-of-failure regime
+Noise guidance by profile (starting points)
+	•	AI / Neural: σ ≈ 0.01–0.10 (training drift / GPU jitter)
+	•	SpaceX / Aerospace: σ ≈ 0.03–0.12 (vibration / telemetry lag)
+	•	Energy / RHES: σ ≈ 0.02–0.10 (grid oscillations / load steps)
+	•	Extreme Perturbation: σ up to 0.30 (stress testing / failure modes)
 
-**Noise guidance by profile (rough starting points)**
-- **AI / Neural:** σ ≈ 0.01–0.10 (training drift / GPU jitter)  
-- **SpaceX / Aerospace:** σ ≈ 0.03–0.12 (vibration / telemetry lag)  
-- **Energy / RHES:** σ ≈ 0.02–0.10 (grid oscillations / load steps)  
-- **Extreme Perturbation:** σ up to 0.30 (stress testing / failure modes)
+Notes
+	•	The panel applies domain-specific weighting (relative importance of QΩ vs ζ_sync).
+	•	Outputs are bounded to [0.00, 0.99] to prevent saturation artifacts and maintain comparability.
+	•	Repeated runs at fixed σ typically show < 0.05 variance in stable regimes.
 
-**Notes**
-- The kernel applies **domain-specific weighting** (QΩ vs ζ_sync importance) and a **soft adaptive baseline** so repeated runs can show mild learning/self-stabilization.  
-- Outputs are **clamped to [0, 0.99]** to avoid saturation artifacts and to reflect realistic bounded metrics.  
-- Repeated runs at fixed σ typically show **< 0.05 variance** in stable regimes.
+⸻
 
----
+Validation Purpose
+	•	Benchmark harmonic resilience under controlled perturbations (σ sweeps).
+	•	Study predictive drift signals: observe divergence/convergence of QΩ and ζ_sync as σ increases.
+	•	Profile-specific tuning: compare AI vs Aerospace vs Energy with identical σ to see weighting effects.
 
-## Validation Purpose
-- **Benchmark harmonic resilience** under controlled perturbations (σ sweeps).  
-- **Study predictive drift signals**: observe how QΩ and ζ_sync diverge/converge as σ increases.  
-- **Profile-specific tuning**: compare AI vs Aerospace vs Energy domains with the same σ to see weighting effects.
+For deeper collaboration (e.g., xAI / RobustBench / GLUE-style testing), this panel can be extended with dataset hooks and richer logging while keeping internal parameters sealed under RFT-IPURL.
 
-For collaboration (e.g., xAI/RobustBench/GLUE-style testing), this interface can be extended with dataset hooks and logging while keeping internal parameters sealed.
+⸻
 
----
+Rights & Contact
 
-## Rights & Contact
-All Rights Reserved under **RFT-IPURL v1.0** and the **Berne Convention (UK Copyright Law)**.  
-**Author / Contact:** Liam Grinstead — [email protected]
+All Rights Reserved under RFT-IPURL v1.0 and the Berne Convention (UK Copyright Law).
+Author / Contact: Liam Grinstead — liamgrinstead2@gmail.com