Needham's Recursive Shell Model: A First-Principles Approach to Particle Mass Prediction

Deriving all Particles uniquely from the Light Constant: Needham’s Recursive Shell Model: A First-Principles Approach to Particle MassThis paper introduces a novel theoretical framework in which elementary particles arise from a hierarchy of recursively nested “shells.” By applying quantization rules to successive radial zones, Needham’s model derives particle masses, interaction signatures, and classification directly from first principles—offering a unified scheme for both known and predicted particles across shell indices 0–100. All particles are predicted and a reproducible CSV file will be produced by the python script. Included in this Zenodo upload: fixed-particle-identification.py Scans shell indices 0–100 using Needham’s recursion rules Outputs Universal_Particle_Table.csv with columns: shell_index, zone, sector, particle_name, mass, unit, detection_signature, theoretical csv-generator-enhancement.py Extends the above to create Enhanced_Universal_Particle_Table.csv Adds: theoretical basis formulae, experimental status, discovery year, predicted coupling strengths, prediction confidence scores needhams_particle_table.pdf The full paper “Needham’s Recursive Shell Model: A First-Principles Approach to Particle Mass” (May 2, 2025) paper.tex LaTeX source for the PDF Dependencies: Python 3.x, pandas, numpyUsage: pip install pandas numpy python fixed-particle-identification.py python csv-generator-enhancement.py License: CC BY 4.0 (Creative Commons Attribution 4.0 International)Disclaimer: Provided “as is.” No warranties or guarantees are made regarding accuracy or suitability; we accept no liability for any issues arising from use.