Newton's Constant from the Proton Mass: A Locked Zero-Parameter Prediction
David Elliman · Neuro-Symbolic Ltd · 2 July 2026
Abstract
The fifth registered prediction and the sharpest single number in the programme: Newton's constant computed from the proton mass through a chain containing no fitted parameters — G = ħc/M_P² with M_P² = 990α₀³Λ²/r₆ and Λ = m_p/(2√2(1+3α₀²)) — where α₀ = 1/137 is an exact alphabet count, 990 = 2·9·55 an exact combinatoric, r₆ = (21q)³²/21 a computed queue current, and (1+3α₀²) the junction-billing correction: the three colour-singlet-forced legs of the baryon's Y-junction each fire a two-endpoint service coincidence per record tick and re-commit the record's own ledger entry. The result, G_pred = 6.674311×10⁻¹¹ m³ kg⁻¹ s⁻², lands at +0.07σ_G of CODATA-2022 — within a tenth of the experimental standard uncertainty (22 ppm), with the framework side exact at the 10⁻⁹ level, so the entire quoted uncertainty is experimental. The note pre-registers the derivation-history disclosure (the correction class was registered, with a two-sided lock/kill rule, before its landing was computed; the integer, exponent, and sign were forced with no freedom to fit), the frozen-integer no-fit rules, and the falsification protocol: a next-generation big-G measurement at ≲15 ppm that excludes G_pred kills the chain outright, and a companion discriminator rides alongside as an independent check — the single-string meson correction m_ρ → m_ρ(1+α₀²).
Keywords
How to cite
Elliman, D. (2026). Newton's Constant from the Proton Mass: A Locked Zero-Parameter Prediction. Neuro-Symbolic Ltd technical report. https://doi.org/10.5281/zenodo.21140770
@techreport{elliman2026gfromprotonprediction,
author = {Elliman, David},
title = {Newton's Constant from the Proton Mass: A Locked Zero-Parameter Prediction},
institution = {Neuro-Symbolic Ltd},
year = {2026},
doi = {10.5281/zenodo.21140770},
url = {https://neusym.ai/papers/g_from_proton_prediction}
} The version of record is archived on Zenodo at the DOI above; this page and PDF are the publisher copies at neusym.ai. See the full list of papers for the rest of the programme.