FQFT Series Computational Companion: Reproducible Prediction Framework for Papers I–X

Python 3 computational companion for the Fractal Quantum Field Theory (FQFT) research series.

This software package reproduces the numerical prediction framework associated with the FQFT Papers I–X program, including spectral-geometry-derived parameter evaluations, hierarchical scaling structures, and comparative prediction tables against contemporary experimental reference datasets.

The implementation is designed as a reproducible computational artifact accompanying the formal FQFT theoretical framework. The codebase is lightweight, deterministic, and structured for independent verification using standard scientific Python environments.

Core features include:

• Spectral geometric computation routines
• Recursive scaling evaluation
• Fixed-point parameter analysis
• Prediction table generation
• Numerical comparison outputs
• Reproducible execution pipeline

The software is intended as the primary reproducibility layer for the FQFT publication stack and serves as the computational counterpart to the formal kernel papers and phenomenological prediction documents.

Runtime environment:

• Python 3
• NumPy
• SciPy

This upload forms part of the Fractal Quantum Field Theory (FQFT) research program developed under the Global Institute of Logic & Cybernetics (GILC).