Microtubule Simulation

Introduction

This repository contains Python simulations exploring quantum coherence in microtubules, with a novel application of Fibonacci scaling principles. The project bridges quantum mechanics, mathematical patterns, and biological phenomena.

Features

• Fibonacci Scaling in Quantum Coherence: Demonstrates the unique impact of Fibonacci scaling on wavefunction behavior.
• Modular Codebase: Separate scripts for core functionality, wavefunction evolution, and refactored optimizations.
• Visualizations: Generate time-dependent plots of quantum probability density to observe coherence evolution.
• Comprehensive Documentation: Includes theoretical background, usage instructions, and LaTeX-based formatted outputs.

Installation

Prerequisites

Ensure you have Python 3.7+ installed. Clone the repository and install dependencies:

git clone https://github.com/TheonlyqueenAC/Microtubule_Simulation.git
cd Microtubule_Simulation
pip install -r requirements.txt

Usage
1. Run the simulation: python fibonacci_simulation.py
2. Generate outputs:
	•	Visualization: quantum_coherence_evolution.png
	•	Logs and metrics saved in output.log.
3. Documentation:
	•	Review theoretical background and derivations in docs/.

Repository Structure
├── fibonacci_simulation.py               # Core simulation script
├── fibonacci_simulation_evolve_wave_function.py  # Wavefunction evolution
├── fibonacci_simulation_refactored.py    # Optimized version
├── output/                               # Generated output files
│   ├── quantum_coherence_evolution.png   # Plot of quantum coherence evolution
├── docs/                                 # LaTeX documentation
├── README.md                             # Project overview and usage instructions

Theoretical Background

This project explores the behavior of wavefunctions in quantum systems using Fibonacci scaling, hypothesizing its potential role in coherence phenomena in biological systems like microtubules. The scaling provides unique insights into the dynamics of quantum systems, offering a bridge between numerical patterns and physical realities.

Acknowledgments

This project utilizes state-of-the-art tools, including:
	•	AI-driven coding assistance for rapid development and debugging.
	•	IDE-based integration and visualization.

We acknowledge the contributions of pioneers in quantum physics and biology for laying the theoretical foundation on which this work builds.

License

This project is licensed under the MIT License. See the LICENSE file for details.