AI RESEARCH
Phase Transitions as the Breakdown of Statistical Indistinguishability
arXiv CS.AI
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ArXi:2604.15773v1 Announce Type: cross In our formulation, a phase transition is defined as the breakdown of statistical indistinguishability under vanishing parameter perturbations in the thermodynamic limit. This perspective provides a general, order-parameter-free framework that does not rely on model-specific insights or learning procedures. We show that conventional approaches, such as those based on the Binder parameter, can be reinterpreted as special cases within this framework.