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ZENODO
Preprint . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
ZENODO
Preprint . 2026
License: CC BY
Data sources: Datacite
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Stable Histories, Entropic Time, and Branch Selection in the L(6+7) Framework

Authors: Zigangirov, Oleg;

Stable Histories, Entropic Time, and Branch Selection in the L(6+7) Framework

Abstract

This preprint formulates a structural law for selecting stable histories in the space of admissible branches under entropic time. An informal label sometimes used for this problem is “formula of fate”; here it is treated not as an everyday metaphor or mystical claim, but as a variational-entropic law according to which the realized branch is the one that accumulates the largest integral structural weight while preserving form, coherence, memory, returnability, and quality of self-view under noise suppression. We introduce the history-weight functional, normalized realization probability, logarithmic growth rate, a criterion of branch stability, a theorem for the transition from a rare branch to a dominant one, a geometric interpretation in a negatively curved history space, and an explicit bridge to the L(6+7) program through the statistical functional Θ = log Z and the flow S = D_aΘ. The paper claims a formal architecture and a testable selection law; it does not claim that all coefficients are already calibrated or uniquely derived from a completed microscopic closure.

Keywords

history space, time-branch, entropic time, self-view, stable histories, rare-to-dominant transition, L(6+7), branch engineering, branch weight

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average