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Open in hackernews

Is the Standard Model overfitting or am I curve-fitting?

3•albert_roca•2h ago
I am developing a geometric model of physical interactions based on geometric constraints (w = 2, δ = √5 ) and topological invariants. No free parameters, just geometry. In your opinion, is this a legitimate geometric unification or just sophisticated curve-fitting?

Results:

Proton radius (r_p): Modeled as a tetrahedral structural limit (4 · ƛ) with spherical field projection loss (α / 4 · π).

  r_p  = 4 · ƛ_p · (1 - (α / (4 · π)))
  Pred: 8.407470 × 10^-16 m
  Exp:  8.4075(64) × 10^-16 m
  Diff: 3 ppm
Proton magnetic moment (g_p): Derived from the dynamic potential (δ = √5 ) damped by a golden friction term (α / Φ).

  g_p = (δ^3 / w) - (α / Φ)
  Pred: 5.5856599
  Exp:  5.5856947
  Diff: 6 ppm
Muon anomaly (a_μ): Derived as a hierarchical resolution of the icosahedral geometry: surface (α / 2 · π) + nodes (α^2 / 12) + vertex symmetry (α^3 / 5).

  a_μ = (α / (2 · π)) + (α^2 / 12) + (α^3 / 5)
  Pred: 0.00116592506
  Exp:  0.00116592059
  Diff: 4 ppm
α particle radius (r_α): Modeled as a 4-nucleon tetrahedron (8 · ƛ) with a linear nucleonic projection cost (α / π).

  r_α = 8 · ƛ_p · (1 - (α / π))
  Pred: 1.67856 × 10^-15 m
  Exp:  1.678 × 10^-15 m
  Diff: 330 ppm
Proton mass (m_p): Connecting the Planck scale to proton scale via a 64-bit metric horizon (2^64) and diagonal transmission (√2 ).

  m_p = ((√2 · m_P) / 2^64) · (1 + α / 3)
  Pred: 1.67260849206 × 10^-27 kg
  Exp:  1.67262192595(52) × 10^-27 kg
  Diff: 8 ppm
Neutron-proton mass difference (∆_m): Modeled as potential energy stored in the geometric compression of the electron (icosahedron, 20 faces) into the protonic frame (cube, 8 vertices). Compression ratio = 20/8 = 5/2.

  ∆_m = m_e · ((5/2) + 4 · α + (α / 4))
  Pred: 1.293345 MeV
  Exp:  1.293332 MeV.
  Diff: 10 ppm.
Gravitational constant (G) without G: Derived from quantum constants and the proton mass, identifying G as a scaling artifact of the 128-bit hierarchy (2^128).

  G = (ħ · c · 2 · (1 + α / 3)^2) / (m_p^2 · 2^128)
  Pred: 6.6742439706 × 10^-11
  Exp:  6.67430(15) × 10^-11 m^3 · kg^-1 · s^-2
  Diff: 8 ppm
Fine-structure constant (α): Derived as the static spatial cost plus a spinor loop correction.

  α^-1 = (4 · π^3 + π^2 + π) - (α / 24)
  Pred: 137.0359996
  Exp:  137.0359991
  Diff: < 0.005 ppm
Preprint: https://doi.org/10.5281/zenodo.17847770

Comments

bigyabai•2h ago
If you have to ask people whether or not your preprint resembles curve-fitting, you have just self-reported that you are an AI user with no academic background.

Good luck with the peer review, you're gonna need it.

albert_roca•1h ago
I have reported nothing but numerical results. Making assumptions about me instead of looking at the numbers says more about your background than it does about mine.
bigyabai•1h ago
I have done nothing but associate your "numerical results" with other numberslop I see from LLMs. Again, you're self-reporting.
albert_roca•1h ago
Can you share the results of your analysis by association? Or was it an instant mental calculation?
yuuu•1h ago
From the manuscript linked in your profile:

> The author declares the intensive and extensive use of Gemini 2.5 Flash and Gemini 3.0 Pro (Google) and sincerely thanks its unlimited interlocution capacity. The author declares as their own responsibility the abstract formulation of the research, the conceptual guidance, and the decision-making in case of intellectual dilemma. The AI performed the mathematical verification of the multiple hypotheses considered throughout the process, but the author is solely responsible for the final content of this article. The prompts are not declared because they number in the thousands, because they are not entirely preserved, and because they contain elements that are part of the author’s privacy.

albert_roca•1h ago
This seems properly copied and pasted. Good job. I guess we agree that AI is already playing a central role in science, and physics is no exception.
yuuu•1h ago
> AI performed the mathematical verification

That should be done by the human writing the manuscript, i.e., you.

albert_roca•48m ago
Absolutely not. Results don't depend on who performed the calculation or how it was done. Can you solve 12,672 Feynman diagrams by hand?
pavel_lishin•2h ago
Based on your pre-previous post, this is nothing.
albert_roca•1h ago
Your contribution is the opposite of "something".
rolph•1h ago
a much more revelatory exercise would be to compare these derived values with measured values, then construct testable hypotheses regarding disparities.
albert_roca•1h ago
That's precisely what the numbers show. "Pred:", predicted value. "Exp:", experimental value. "Diff", difference.
rolph•50m ago
the next step is, why?

what assumptions does your current model make. what could change that would eliminate disparity. What plausible mechanisms explain [Diff]?