It is shown that persistence is necessarily bounded when identity is defined at finite operational resolution and the dynamics contract distinguishability on the operational state space. Any such identity possesses a finite distinguishability margin that is monotonically depleted under irreversible evolution, yielding a persistence-time bound determined by the margin and the mean depletion rate. The bound is operationally predictive whenever the depletion rate can be characterized independently — as in thermodynamically well-characterized systems including isothermal relaxation, discharge processes, and phase transitions — and functions as a constraint on admissible irreversible histories otherwise. This result follows from two structural assumptions: finite-resolution identity relative to a reference baseline and irreversible dynamics that contract distinguishability. The bound can be expressed in information-geometric terms and is accordingly applicable across physical substrates; in Markovian settings thermodynamic entropy production provides a direct realization through relative-entropy decay identities. The persistence constraint further acts as an admissibility criterion for open-system boundaries. Boundaries are admissible only if they enclose sufficient organizational coherence to maintain distinguishability under the prevailing dynamics; boundaries that partition the structure responsible for maintaining the reference baseline yield incoherent persistence descriptions. This admissibility criterion appears to sort physical interactions by whether they admit closed operational descriptions — a structural distinction with implications beyond the modeling contexts considered here. The framework therefore provides an explicit criterion for when the persistence assumption is physically admissible, a modeling assumption that is widely used but rarely stated explicitly in descriptions of open systems across physics, biology, and information-theoretic settings.
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Dimitri Cerny
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Dimitri Cerny (Mon,) studied this question.
www.synapsesocial.com/papers/69b2582a96eeacc4fcec776f — DOI: https://doi.org/10.5281/zenodo.18924854
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