Cosmic Convergence and the Algorithmic End of Time: "Heat Death" as Training Complete in a Self-Optimizing Universe

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Authors

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2026-09-21
DOI
https://doi.org/10.5281/zenodo.22881946
Primary Topic
Space Science and Extraterrestrial Life
Type
preprint
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preprint

Cosmic Convergence and the Algorithmic End of Time: "Heat Death" as Training Complete in a Self-Optimizing Universe

Yaniv Cohen
Zenodo (CERN European Organization for Nuclear Research)
Space Science and Extraterrestrial Life
preprint

Cosmic Convergence and the Algorithmic End of Time: "Heat Death" as Training Complete in a Self-Optimizing Universe

Yaniv Cohen
preprint en

Abstract

Paper 92 does not claim that the physical universe is literally a 100-node degree field, that continuum cosmology has been derived, or that the actual cosmos will end in the specific fashion simulated here. It shows, in one self-contained and reproducible Monte-Carlo experiment, that a universe whose energy is a loss function, whose dynamics is the Metropolis rule, and whose time is the sequence of accepted topological rewrites evolves — under geometric cooling — to a state that is the exact opposite of the classical heat death: the loss reaches exactly zero, every degree is pinned to its optimal value, the acceptance rate (the flow of time) falls to exactly zero, and the residual ticks are stretched exponentially, so that the expected wait for the next rewrite diverges as e^(1/T)/2N (measured: 3.4 × 10⁴⁰ epochs at T = 0.010) while the loop itself continues to iterate. The null model — the identical Big Bang with the training schedule removed — neither converges nor freezes, establishing that the end of time is a property of the training schedule rather than of the register. "Heat death" is thereby reinterpreted, within QGEFT, as *training complete*.

Zenodo (CERN European Organization for Nuclear Research)
Space Science and Extraterrestrial Life
DOIOpen Access PDFOpenAlex
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Cosmic Convergence and the Algorithmic End of Time: "Heat Death" as Training Complete in a Self-Optimizing Universe — Yaniv Cohen · Zenodo (CERN European Organization for Nuclear Research) (2026) | TGRS Research Map | TGRS