Particle Mass Predictions from Information-Theoretic Principles: 12 Masses with Less Than 0.5% Error | Synapse
March 1, 2026Open Access
Particle Mass Predictions from Information-Theoretic Principles: 12 Masses with Less Than 0.5% Error
Key Points
The central aim is to predict particle masses using information-theoretic principles with minimal error.
Utilized information-theoretic principles to calculate masses of various particles
Predicted 12 particle masses including leptons, quarks, and bosons
Calculated M_Z as approximately Y times Y_H, resulting in 91 GeV
Analyzed accuracy of predictions, achieving better than 0.5% error
Successfully predicted 12 particle masses with an average accuracy of better than 0.5%
Found chance probability of results to be p < 10⁻⁸, indicating high reliability
Abstract
12 particle masses from Y = 7, YH = 13, π and φ. Average accuracy better than 0. 5%. Includes leptons, quarks, and bosons. MZ ≈ Y × YH = 91 GeV. Chance probability p < 10⁻⁸.