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Maximum Kolmogorov-Sinai Entropy Versus Minimum Mixing Time in Markov Chains

Martin Mihelich 1, * Bérengère Dubrulle 1 Didier Paillard 2, 3 Quentin Kral 4, 5 Davide Faranda 2, 6
* Corresponding author
1 SPHYNX - Systèmes Physiques Hors-équilibre, hYdrodynamique, éNergie et compleXes
SPEC - UMR3680 - Service de physique de l'état condensé, IRAMIS - Institut Rayonnement Matière de Saclay
3 CLIM - Modélisation du climat
LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] : DRF/LSCE
6 ESTIMR - Extrèmes : Statistiques, Impacts et Régionalisation
LSCE - Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] : DRF/LSCE
Abstract : We establish a link between the maximization of Kolmogorov Sinai entropy (KSE) and the minimization of the mixing time for general Markov chains. Since the maximisation of KSE is analytical and easier to compute in general than mixing time, this link provides a new faster method to approximate the minimum mixing time dynamics. It could be interesting in computer sciences and statistical physics, for computations that use random walks on graphs that can be represented as Markov chains.
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Martin Mihelich, Bérengère Dubrulle, Didier Paillard, Quentin Kral, Davide Faranda. Maximum Kolmogorov-Sinai Entropy Versus Minimum Mixing Time in Markov Chains. Journal of Statistical Physics, Springer Verlag, 2018, 170, pp.62 - 68. ⟨10.1007/s10955-017-1874-z⟩. ⟨cea-01687782⟩

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