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May 14, 20260 citationsOpen Access

Version 2: Quantum Theory of Gravity– Mathematical Derivation of Nuclear Spin Quantisation – Jianhao M. Yang's Extended Least Action Principle and Testable Prediction

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AMAsif Majeed

Key Points

  • This paper aims to mathematically derive and demonstrate nuclear spin quantisation within the framework of Quantum Theory of Gravity.
  • Derivation using Jianhao M. Yang's extended least action principle and Tsallis divergence.
  • Calculation of probability distribution for nuclear spin orientation.
  • Analyzing the implications of strong interactions on nuclear spin states.
  • Nuclear spin distribution collapses to two states (spin-up and spin-down) under strong interactions.
  • The predicted spin-dependent fine structure shift in atomic spectra correlates with nuclear spin magnitude.
  • The approach differs from standard magnetic hyperfine splitting predictions.

Abstract

Abstract: This paper provides the mathematical derivation for the nuclear spin quantisation postulated in Version 1 of the Quantum Theory of Gravity (DOI: 10.5281/zenodo.20020593). Using Jianhao M. Yang's extended least action principle with Tsallis divergence, we derive the probability distribution for nuclear spin orientation. In the limit of strong interaction, the distribution collapses to two discrete states (spin‑up and spin‑down). This yields a testable prediction: a spin‑dependent fine structure shift in atomic spectra proportional to the nuclear spin magnitude, distinct from standard magnetic hyperfine splitting. Keywords: Nuclear spin quantisation, extended least action principle, Tsallis divergence, Yang's method, spin‑dependent fine structure, cosmic energy compression, no graviton. License (this paper): Creative Commons Attribution (CC BY) 4.0 Copyright: © Asif Majeed, 2026. This work adapts methods from Yang 1 under CC BY 4.0. Zenodo DOI: 10.5281/zenodo.20141173

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Asif Majeed (2026) studied this question.

synapsesocial.com/papers/6a0567fda550a87e60a2056ahttps://doi.org/10.5281/zenodo.20141173
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