🌌 SHZ-BCC Phenomenology Toolkit

SHZ-BCC-Pheno-Toolkit is an open-source Python suite for simulating the phenomenological and cosmological consequences of the Horizon Boundary Consistency (SHZ-BCC) model.

The SHZ-BCC framework resolves the Cosmological Constant Problem by imposing discrete $Z_2^3$ constraints on causal horizons, projecting out divergent vacuum energy. When embedded in a Pati-Salam $SU(4)_C \times SU(2)_L \times SU(2)_R$ envelope, the model yields exact, parameter-free predictions for the CKM matrix, proton decay, and primordial gravitational waves.

🚀 Features

This toolkit provides numerical solvers and Monte Carlo simulations across four distinct frontiers of modern physics:

• Flavor Physics: Renormalization Group Equations (RGEs) for CKM parameters and validation of the analytically derived Cabibbo angle ($\lambda = (\pi\sqrt{2})^{-1}$).
• Collider Phenomenology: Monte Carlo generation of High-Luminosity LHC kinematics ($A^0 \to \tau^+\tau^-$) and Lepton Flavor Violation ($\mu \to e \gamma$).
• Cosmology: Simulations of False Vacuum Inflation, Cosmic Strings (GW backgrounds), and Boltzmann Equations for thermal Leptogenesis (Dark Matter).
• Quantum Gravity: Holographic Tensor Network simulations mapping the $Z_2^3$ constraints to Loop Quantum Gravity (LQG) $SU(2)$ spin networks and Entanglement Entropy.
• Machine Learning: Random Forest AI parameter scanning of 100,000 synthetic universes to determine the theory's Goldilocks survival zone.

📁 Repository Structure

• src/ - Python source code (Solvers, ML, Monte Carlo).
• docs/ - Comprehensive LaTeX articles, phenomenological notes, and Feynman diagrams.
• results/ - Output directory for generated high-resolution plots.
• web/ - Interactive HTML/JS portal for data visualization.

🛠️ Installation

Clone the repository and install the required dependencies:

git clone https://github.com/YourUsername/SHZ-BCC-Pheno-Toolkit.git
cd SHZ-BCC-Pheno-Toolkit
pip install -r requirements.txt

💻 Quick Start

Run the Grand Simulation (combining Black Hole Thermodynamics, Leptogenesis, Collider limits, and Hubble Tension):

python src/grand_simulation.py

Run the Machine Learning Parameter Scan:

python src/ai_parameter_scan.py

📖 Citation

If you use this toolkit in your research, please consider citing the original SHZ-BCC preprint:

Ślusarczyk, M. (2026). Horizon Boundary Consistency and Vacuum-Energy Cancellation: A Quantum-Horizon Effective Framework with Standard-Model Embedding. arXiv preprint.

📄 License

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