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- W4286233419 abstract "In statistical mechanics, measuring the number of available states and their probabilities, and thus the system's entropy, enables the prediction of the macroscopic properties of a physical system at equilibrium. This predictive capacity hinges on the knowledge of the a priori probabilities of observing the states of the system, given by the Boltzmann distribution. Unfortunately, the successes of equilibrium statistical mechanics are hard to replicate out of equilibrium, where the a-priori probabilities of observing states are in general not known, precluding the na{i}ve application of usual tools. In the last decade, exciting developments have occurred that enable the direct numerical estimation of the entropy and density of states of athermal and non-equilibrium systems, thanks to significant methodological advances in the computation of the volume of high-dimensional basins of attraction. Here, we provide a detailed account of these methods, underscoring the challenges that lie in such estimations, recent progress on the matter, and promising directions for future work." @default.
- W4286233419 created "2022-07-21" @default.
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- W4286233419 date "2022-07-17" @default.
- W4286233419 modified "2023-09-23" @default.
- W4286233419 title "When you can't count, sample! Computable entropies beyond equilibrium from basin volumes" @default.
- W4286233419 doi "https://doi.org/10.48550/arxiv.2207.08241" @default.
- W4286233419 hasPublicationYear "2022" @default.
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