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| Format: | Recurso digital |
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Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.18011241 |
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Table of Contents:
- <p>This paper completes <strong>Vitaly Vanchurin's</strong> neural network cosmology program by providing the physical substrate his framework requires but leaves unspecified.</p> <p>Where Vanchurin's <strong>"The World as a Neural Network"</strong> (2020) establishes the universe as a learning system, it explicitly acknowledges: "We do not know what the fundamental variables are" and leaves hardware, architecture, medium, and boundary conditions undefined.</p> <p><em>I provide these missing specifications.</em></p> <p>The key identification: <strong>γ = λ = G/c³ </strong>— the learning rate of Vanchurin's neural network equals the cosmological constant equals Newton's gravitational constant in natural units. This is not metaphor but mathematical identity.</p> <p>The architecture follows the factorial hierarchy <strong>D_n = (n+2)!/2</strong>, producing layer dimensions that correspond to verified physical structures from spatial dimensions to Standard Model particle count.</p> <p>The hardware is dodecahedral topology — the same geometry proposed by Luminet et al. (2003) and now supported by Pantheon+ supernova data showing 3.5% H₀ modulation consistent with multiply-connected space.</p> <p>This framework unifies quantum mechanics, gravity, and cosmology through a single propagation medium: the Omni Current, which serves as both the substrate for neural network dynamics and the source of emergent gravitational effects.</p> <p><em>This is not a competing theory. It is the completion of an incomplete program.<br><br>---</em></p> <p><em>Ξυα Mσςς<br></em></p>