Spectral theoretic characterisation of Markov chain convergence

Fuente: arXiv
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Main Authors: Davies, Bryn, Xiao, Angelica Yu
Format: Preprint
Published: 2024
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_version_ 1866916957810327552
author Davies, Bryn
Xiao, Angelica Yu
author_facet Davies, Bryn
Xiao, Angelica Yu
contents In this work, we characterise the statistics of Markov chains by constructing an associated sequence of periodic differential operators. Studying the density of states of these operators reveals the absolutely continuous invariant measure of the Markov chain. This approach also leads to a direct proof of convergence to the invariant measure, along with explicit convergence rates. We show how our method can be applied to a class of related Markov chains including the logistic map, the tent map and Chebyshev maps of arbitrary order.
format Preprint
id arxiv_https___arxiv_org_abs_2410_15829
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Spectral theoretic characterisation of Markov chain convergence
Davies, Bryn
Xiao, Angelica Yu
Dynamical Systems
Classical Analysis and ODEs
Probability
37A05, 34L05, 58J51
In this work, we characterise the statistics of Markov chains by constructing an associated sequence of periodic differential operators. Studying the density of states of these operators reveals the absolutely continuous invariant measure of the Markov chain. This approach also leads to a direct proof of convergence to the invariant measure, along with explicit convergence rates. We show how our method can be applied to a class of related Markov chains including the logistic map, the tent map and Chebyshev maps of arbitrary order.
title Spectral theoretic characterisation of Markov chain convergence
topic Dynamical Systems
Classical Analysis and ODEs
Probability
37A05, 34L05, 58J51
url https://arxiv.org/abs/2410.15829