Proves an H-theorem for monotonic decrease of a convex functional under iteration and gradient flow of a self-referential operator Omega within the local kernel approximation, with perturbative stability of the Tsallis index and numerical confirmation of a re-entrant disordered phase at kappa > 0.5.
Possible generalization of Boltzmann–Gibbs statistics
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2026 1verdicts
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Irreversibility from Self-Reference: Gradient Flow and an H-Theorem for a Self-Referential Statistical Operator Framework
Proves an H-theorem for monotonic decrease of a convex functional under iteration and gradient flow of a self-referential operator Omega within the local kernel approximation, with perturbative stability of the Tsallis index and numerical confirmation of a re-entrant disordered phase at kappa > 0.5.