CCEGA Part V TOV Integration Code: GR vs CCEGA Numerical Comparison

Supplementary code and technical documentation for: López Sánchez, M. (2026). CCEGA: Information-Driven Gravity and the Mass Gap Problem. Zenodo. doi:10.5281/zenodo.19539744 Complete Python implementation of modified Tolman-Oppenheimer-Volkoff (TOV) solver for General Relativity baseline and CCEGA framework comparison with APR4 equation of state. CONTENTS:- GR_vs_CCEGA_VERIFIED.py: Executable Python code (3.8+)- CODE_DOCUMENTATION_V_FINAL.pdf: Technical documentation with line-by-line explanation, physical interpretation, and convergence analysis FEATURES:- RK45 (Dormand-Prince 5th order) numerical integration- Automatic surface detection and validity checking- Density scan: 15 logarithmically-spaced points- Separate GR baseline (4 variables) and CCEGA (5 variables) solvers- Mass-radius diagram plotting- Console output with convergence statistics RESULTS:- GR M_max = 1.9885 ± 0.0012 M_☉ (verified vs Read et al. 2009)- CCEGA M_max = 4.3479 ± 0.0085 M_☉- Enhancement: 2.19× (118.7% increase)- Convergence: 13/15 (GR), 15/15 (CCEGA) REQUIREMENTS:Python 3.8+ with scipy.integrate.solve_ivp, numpy, matplotlib USAGE:Option A (Google Colab): Copy code into single cell, execute, wait 2-3 minutesOption B (Local Python): pip install numpy scipy matplotlib, then python GR_vs_CCEGA_VERIFIED.py REPRODUCIBILITY:All numerical results in main paper (Part V) are fully reproducible from this code. APR4 equation of state parameters are hardcoded. No external data files required. PARAMETERS (user-adjustable):- RHO_C = 7.4 × RHO_NUC (critical density, MIT bag model)- Integration tolerances: rtol=1e-5, atol=1e-11- Density range: logspace(14.7, 15.698, 15) LIMITATIONS:- Spherically symmetric (no rotation)- Hydrostatic equilibrium only- Single EOS (APR4)- Quasi-static information field approximation- No perturbation stability analysis VERSION: 1.0AUTHOR: Marc López Sánchez (ORCID: 0009-0005-6356-3702)DATE: April 12, 2026