Structural Asymmetry in Finite Systems: Geometry-Induced Negative Drift

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Auteur principal: Minh, Ho
Format: Recurso digital
Langue:anglais
Publié: Zenodo 2026
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_version_ 1866901785911754752
author Minh, Ho
author_facet Minh, Ho
contents <p>This work introduces the Structural Asymmetry Principle, a minimal, model-independent framework explaining why instability and negative drift arise generically in finite systems.</p> <p>We show that when structured states occupy a vanishing fraction of the state space, stochastic dynamics induce an inherent asymmetry in transitions: trajectories are more likely to leave structured regions than to return to them. Under mild conditions, this leads to a strictly negative long-run expectation.</p> <p>The result does not rely on entropy, specific mechanisms, or domain-dependent assumptions. Instead, it follows directly from geometric sparsity and ergodic exploration. Consequently, stability is not a generic outcome but requires sustained compensation.</p> <p>This formulation provides a unified structural explanation for instability across domains, including stochastic processes, learning systems, and decision dynamics.</p> <p>Technical proofs are provided in the Appendix.</p> <p>Stability is non-generic in finite systems and requires sustained compensation.</p>
format Recurso digital
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language eng
publishDate 2026
publisher Zenodo
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spellingShingle Structural Asymmetry in Finite Systems: Geometry-Induced Negative Drift
Minh, Ho
structural asymmetry
negative drift
finite systems
stochastic dynamics
Markov chains
ergodicity
geometric sparsity
stability
non-equilibrium systems
long-run behavior
system dynamics
decision processes
<p>This work introduces the Structural Asymmetry Principle, a minimal, model-independent framework explaining why instability and negative drift arise generically in finite systems.</p> <p>We show that when structured states occupy a vanishing fraction of the state space, stochastic dynamics induce an inherent asymmetry in transitions: trajectories are more likely to leave structured regions than to return to them. Under mild conditions, this leads to a strictly negative long-run expectation.</p> <p>The result does not rely on entropy, specific mechanisms, or domain-dependent assumptions. Instead, it follows directly from geometric sparsity and ergodic exploration. Consequently, stability is not a generic outcome but requires sustained compensation.</p> <p>This formulation provides a unified structural explanation for instability across domains, including stochastic processes, learning systems, and decision dynamics.</p> <p>Technical proofs are provided in the Appendix.</p> <p>Stability is non-generic in finite systems and requires sustained compensation.</p>
title Structural Asymmetry in Finite Systems: Geometry-Induced Negative Drift
topic structural asymmetry
negative drift
finite systems
stochastic dynamics
Markov chains
ergodicity
geometric sparsity
stability
non-equilibrium systems
long-run behavior
system dynamics
decision processes
url https://doi.org/10.5281/zenodo.19582028