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April 21, 20260 citationsOpen Access

Neutrino Mass Sum from Spacetime Dimensionality A prediction of the Relational-Structural Framework

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MHMalin Hess

Key Points

  • To predict neutrino mass using the Relational-Structural Framework and its relation to dark matter and spacetime dimensionality.
  • Analysis of (D+1)-dimensional spacetime and its degrees of freedom
  • Prediction of dark matter ratio using scalar entropy and structural entropy
  • Verification against Planck CMB power spectrum with CLASS Boltzmann code
  • Predicted dark matter ratio: Ωstruct/Ωb = 5, compared to observed Ωcdm/Ωb = 5.36
  • Neutrino mass prediction: Σmν = 0.76 eV (or 0.34 eV with correction)
  • Finding is testable with upcoming observational missions like DESI, Euclid, and CMB-S4.

Abstract

The Relational-Structural Framework identifies dark matter as the structural entropy of the causal graph — the information content of spacetime's topological degrees of freedom. In (D+1)-dimensional spacetime, the physical metric has (D+1)D/2 independent degrees of freedom. The scalar entropy field captures one. The remaining (D+1)D/2 1 are structural entropy, − which gravitates as cold dark matter. For D = 3: the predicted dark matter ratio is Ωstruct/Ωb = 5. The observed ratio Ωcdm/Ωb = 5.36 exceeds this by 0.36, which is attributed to massive neutrinos. This yields a zero-parameter prediction: Σmν = (Ωcdm/Ωb 5) × ωb × 93.14 eV = 0.76 eV (or 0.34 eV if the h² − correction applies — see Section 5). The prediction is verified against the Planck CMB power spectrum using the CLASS Boltzmann code and is falsifiable by DESI, Euclid, and CMB-S4 within the coming decade. DISCLAIMER Generative AI was used to assist with literature screening / coding support / draft language revision. All AI-assisted outputs were independently checked by the author, and the author takes full responsibility for the final analysis and text. This is encompassing all the work that has been done and will be done. All code is under MIT licensing. All research papers are under Creative Commons License. All code, outputs and notes are included in the reproducibility bundle zip file.

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Cite This Study

Malin Hess (2026) studied this question.

synapsesocial.com/papers/69e713b4cb99343efc98d203https://doi.org/10.5281/zenodo.19654184
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