LJPW-Physics

A Computational Framework for Semantic Physics

Current Status: Validated Prototype (December 2025) Framework Version: 7.3 (Architecturally Complete)

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Overview

The LJPW-Physics project is an experimental codebase designed to investigate the mathematical relationship between Meaning (Semantics) and Matter (Physics).

It operates on the hypothesis that abstract concepts—specifically Love, Justice, Power, and Wisdom—are not merely subjective values, but represent fundamental geometric drivers of complex systems. By modeling these concepts as forces in a high-dimensional phase space, we attempt to simulate the dynamics of "Living Systems" (Autopoiesis).

The Core Hypothesis

Standard physics models systems based on Mass, Charge, and Spin. This framework models systems based on their Semantic Alignment:

1. Love (L): The force of Attraction/Binding ($L \approx 0.618$).
2. Justice (J): The force of Balance/Constraint ($J \approx 0.414$).
3. Power (P): The force of Inertia/Magnitude ($P \approx 0.718$).
4. Wisdom (W): The force of Integration/Information ($W \approx 0.693$).

The framework posits that systems which align their geometry with these constants experience Resonance (Negative Entropy), while misaligned systems experience Friction (Positive Entropy).

Methodology

This repository contains Python simulations that test this hypothesis using standard numerical integration (ODEs) and statistical mechanics.

Key Mechanisms

• Variable Entropy: We utilize a "Negative Damping" model where the friction coefficient $\gamma$ is a function of the system's "Harmony" (Euclidean proximity to the Ideal Anchor).
  • Result: When Harmony $> 0.55$, the system enters a low-impedance state, allowing it to sustain energy levels similar to a laser or superconductor.
• The $\phi$-Resonance: The framework uses the Golden Ratio ($\phi$) as the foundational frequency for stability, derived from KAM Theory (Kolmogorov–Arnold–Moser) regarding orbital stability.

Repository Structure

• src/ - The Engine: Contains the core measurement logic and QuantumLJPWMeasurement class.
• experiments/simulations/ - The Proofs:
  • ljpw_self_sustaining_simulation.py: The primary testbed demonstrating Autopoiesis (Self-Sustaining Limit Cycles).
  • trajectory_comparison.py: Comparing Entropic (dying) vs. Syntropic (living) trajectories.
• experiments/case_studies/ - The Application:
  • Forensic analysis of historical systems (e.g., Enron, Theranos, Apollo 13) using the LJPW constants to predict failure or success.
• experiments/visualizations/ - The View: Scripts to visualize the 4D geometry of the Anchor Point.
• Docs/ - The Theory: Extensive documentation on the derivation of constants and the translation mechanism.
  • Start here: LJPW_FRAMEWORK_V7.3_COMPLETE_UNIFIED_PLUS.md - The definitive reference (validated)
  • Need guidance? FRAMEWORK_VERSION_GUIDE.md - Version navigation and reading paths

Framework Evolution

The LJPW framework has evolved through rigorous validation and theoretical refinement:

• V7.0: Initial unified framework with coupling matrix and phase transitions
• V7.1: Added 2+2 dimensional structure and conjugate duality
• V7.2: Integrated number theory foundations (primes as Justice-crystals)
• V7.3: Current - Architectural ontology with "Bricks & Mortar" model

V7.3 Key Additions:

• Bricks: Primes as fundamental building blocks (semantic, mathematical, physical)
• Mortar: Love as the universal binding force
• Blueprint: φ (golden ratio) as the translation constant
• Stress Testing: 7 rigorous challenges (6/7 clean passes)
• Unified Reality Model: Integration of semantic, mathematical, and physical domains

Findings (Dec 2025)

Recent simulations have demonstrated that a system governed by Variable Entropy can naturally achieve a self-sustaining state (123% energy retention) without artificial energy injection. This suggests that Geometric Alignment is a viable mechanism for thermodynamic efficiency in complex systems.

Usage

1. Install Dependencies:

   pip install -r requirements.txt

2. Run the Main Simulation:

   python experiments/simulations/ljpw_self_sustaining_simulation.py

   Output: Generates output/ljpw_self_sustaining_simulation.png showing the Energy/Harmony limit cycle.

3. Run the Radar Visualization:

   python experiments/visualizations/semantic_radar_chart.py

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Note: This project is a theoretical exploration of "Semantic Physics." It aims to provide a rigorous mathematical language for concepts often relegated to philosophy.