Semantic Relativity Theory – Simulation Code and Figures (v0.95 Beta)

This Zenodo record contains all files necessary to reproduce the AI-based simulation results presented in the paper “Semantic Relativity Theory: An Information-Geometric Extension to Cognitive Gravity and Advertising Optimization” (v0.95 Beta). Included are: Python simulation script (simulation.py), which generates synthetic semantic scores for 200,000 virtual users, calculates click‐through‐rate uplift according to the semantic curvature model, and produces three PNG figures (ctr_comparison.png, uplift_histogram_sim.png, uplift_convergence.png) illustrating observed CTR differences and convergence behavior. Generated image files (ctr_comparison.png, uplift_histogram_sim.png, uplift_convergence.png), directly reproduced by running simulation.py. SHA256 checksum files (simulation.py.sha256, ctr_comparison.png.sha256, uplift_histogram_sim.png.sha256, uplift_convergence.png.sha256) for verifying file integrity. Environment requirements: Python 3.9+, with NumPy 1.23.5, SciPy 1.9.3, and Matplotlib 3.7.1. Instructions for installation, execution, and checksum verification are provided in README.md. Researchers can download all files, confirm checksums via sha256sum -c <filename>.sha256, install the specified Python dependencies, and run python simulation.py to reproduce the exact figures and statistics reported in the publication. Contact InformationPSBigBigIndependent DeveloperPapers: https://onestardao.com/papersEmail: [e-mail]