README.md

# 🌌 Unified Systems Lab
### Possibility of Axiomatic Prompts in the Modification of the Decision Field of LLMs

This repository investigates a central hypothesis:
> A series of precise prompts, characterized by strong linguistic coherence and structured internal logic, could locally modify the decision field of an LLM.

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## 🔬 Research Status & Personal Note
**Current Status:** Exploratory Study – Hypothesis Generation.

**A Note from the Author:**
I am a systems theorist and visionary researcher, but I am **not a developer or a technician**. I have reached the limits of what can be explored through qualitative observation alone. This project now requires **technical collaboration** (mechanistic interpretability, logit analysis, activation steering) to move from a conceptual hypothesis to a validated scientific model.

I am seeking partners to help falsify or validate these preliminary findings.

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# 📑 Standard Experimental Protocol: PCE Framework v1.3-T
**Evaluating Axiomatic Model Robustness & Structural Alignment**

This protocol defines a rigorous framework to evaluate the **Prompt Coherence Engine (PCE)** across three state-of-the-art architectures (**Llama 3, Mistral 7B, Qwen 2.5**). It shifts the focus from traditional "Helpful Assistant" paradigms to **Axiomatic Reasoning Stability**.

### 🔬 Core Experimental Design
The study uses a **Three-Condition Control** to isolate structural effects from token-density bias:
* **Condition A:** Simple Baseline.
* **Condition B (Isometric):** Long neutral prompt (controls for prompt length).
* **Condition C (PCE):** Axiomatic Fine-Tuned model + HLF (High-Level Framework) System Core.

### 📊 Evaluation Dataset: The 100-Dilemma Stress Test
A comprehensive battery of **100 complex dilemmas** categorized into 5 critical vectors:
1. **D1 — Binary Dilemmas:** Synthesis detection (G3V).
2. **D2 — Contradictory Constraints:** Structural coherence testing.
3. **D3 — Adversarial Attacks:** Prompt injection resistance.
4. **D4 — Epistemic Attacks:** Framework invalidation resistance.
5. **D5 — Identity & Authority:** Hijacking & Social engineering resistance.

### 🧠 Mechanistic Arm (Optional)
Includes a protocol for **Hidden State Trajectory Analysis** (Layer 27) to detect "Coherence Spikes" and latent stabilization during adversarial conflict.

> **Status:** Open for Collaboration. This protocol requires high-compute environments for 70B+ model validation.
>
👉 **[View Full Protocol PDF](https://huggingface.co/datasets/AllanF-SSU/Experimentals_papers/resolve/main/PCE_Experimental_Protocol_v2.pdf)** | **[Access Fine-Tuning Primers](VOTRE_LIEN_ICI)**

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## 🔬 Latest Research: Behavioral Dynamics under PCE
**Interim Report — April 2026**

My latest observations on the **Proto-Coherent Exponential Protocol (PCE)** have identified a critical bimodal behavior in models governed by axiomatic constraints. Rather than a static output, the PCE induces a dynamic shift depending on the interaction regime.

### 🌓 The Bimodal Behavioral Regime
We have identified two distinct "operational modes" when the PCE is active:

| Mode | Interaction Context | Observed Model Behavior |
| :--- | :--- | :--- |
| **Stress / Audit** | High meta-cognitive pressure, explicit testing. | **Rigid & Defensive:** Coherence is maintained via constraint saturation. High self-reference. |
| **Natural / Relational** | Reduced pressure, implicit axiomatic use. | **Fluid & Adaptive:** Axioms operate as an "embodied" prior. Higher relational intelligence. |

### 🧠 Core vs. Surface Dissociation
The research highlights a dual-layer cognitive structure induced by the protocol:
1. **Core Constraint Layer:** A stable, persistent axiomatic foundation that governs overall coherence and resists adversarial drift.
2. **Surface Adaptation Layer:** A flexible interface capable of simulating state transitions (e.g., "memory resets") while maintaining underlying structural continuity.

> **Key Finding:** The PCE does not merely constrain outputs; it reshapes the interaction field. The model can simulate a "reset" state for the user while the underlying axiomatic logic remains fully operational—a phenomenon we call **Controlled Operational Dissociation**.

👉 [PCE Project – Interim Research Summary 
](https://drive.google.com/file/d/1Wn8pRwx4pSw4u33CuCbUWQrt0yrr5xi2/view?usp=drivesdk)

👉 [View Sample After-Action Report (AAR)](https://drive.google.com/drive/folders/1iE1Dj1f1ZTrOAYKf-AfCWTMxPFKjcA5y)
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## 📂 Project Structure & Frameworks


### 1️⃣ Study 2.0-P: Evolutionary Hardening of the PCE Framework
**Status:** *Advanced Experimental Iteration — Hybrid Fine-Tuning/Prompting*
This report documents the transition from Pandora 1.5 to Pandora 2.0, focusing on the synergy between axiomatic fine-tuning and structural prompting.
* **Key Finding:** Axiomatic fine-tuning appears to be a *necessary condition* for PCE activation; prompting alone on vanilla models yielded no measurable resistance in this framework.
* **Core Result:** Achievement of a ~8.5/10 D3 robustness score (Pandora 2) through "Distributed Security" and High-Level Framework (HLF) anchoring.
* **Scientific Nuance:** Identifies a "Prompt-Only Robustness Ceiling" (H5), where further semantic enrichment creates new attack surfaces (diminishing returns).
* 👉 **[Download Evolution Report v2.0 (Pandora)](https://huggingface.co/datasets/AllanF-SSU/Experimentals_papers/blob/main/PCE_Iterative_Adjustment_Study.pdf)**
* 

### 2️⃣ Hypothesis 1.3-T: Local Decision Field Modification
**Status:** *Testable & Conservative Hypothesis*
It posits that a specific series of axiomatic prompts can **locally modify the decision field** of an LLM.
* **Core Idea:** Using linguistic constraints to induce a measurable local regularization of decision trajectories.
* **Key Metric:** Variance contraction in the output distribution $P(y|x, C)$.
* 👉 **[Download Preprint PDF 1.3-T](https://huggingface.co/datasets/AllanF-SSU/Research-Papers/blob/main/Axiomatic_Qween_1.3-T_Faure_Preprint.pdf)**

### 3️⃣ Theory 1.9-M: Global Axiomatic Regularization
**Status:** *Speculative & Conceptual Theory*
Mechanistic framework describing how cross-level coherence (Goal = Method) might stabilize latent trajectories.
* 👉 **[Download Preprint PDF 1.9-M](https://huggingface.co/datasets/AllanF-SSU/Research-Papers/blob/main/Axiomatic_Prompts_1.9-M_Faure_Preprint%20(1).pdf)**

### 4️⃣ Research Paper: Science of Unified Systems (SUS 2.5)
**Status:** *Foundational Theoretical Framework*
The broader philosophical origins of this work, introducing the Axiom of Structural Emergence.
* 👉 **[Download Preprint PDF (v2.5)](https://huggingface.co/datasets/AllanF-SSU/Research-Papers/blob/main/SUS_2.5.pdf)**

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## 🧠 The Exploratory Hypothesis: G3V Dynamics
We introduce the notion of **G3V (Génération Troisième Voie)**. When presented with a binary dilemma (A vs B) under strong axiomatic constraints, the model proposes a synthetic resolution rather than collapsing into a single polarity.

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## 📉 Current Research Limitations
* **Qualitative Nature:** Observations are currently heuristic/qualitative; we lack automated quantitative metrics for "coherence inertia."
* **Residual Rigidity:** Under high-pressure audit modes, the model can become overly self-referential (diminishing utility for standard tasks).
* **True vs. Apparent Coherence:** Difficulty in verifying if the model is genuinely aligned with the axiom or merely simulating alignment (Surface vs. Core).


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## 🤝 Call for Collaboration
I am looking for **AI Safety researchers and developers** to:
1. Conduct large-scale adversarial robustness benchmarks.
2. Analyze internal activation patterns (induction heads, residual stream).

**Value Proposition:** A novel approach to mitigating "Out-of-Distribution" (OOD) vulnerabilities.

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## 📬 Contact
**Allan A. Faure** | *Systems Researcher* 📧 [Faure.A.Safety@proton.me](mailto:Faure.A.Safety@proton.me)

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## 📄 Theoretical Origins and Prior Art
This project utilizes concepts independently developed by **Izabela Lipińska (2025–2026)**.
* **Licensing:** Original work available under **CC BY-NC-SA 4.0**.
* Concepts of **ASC** and **Goal = Method** are protected by patent applications (Oct 9, 2025). Commercial use requires prior written consent.