An approximation theory for Markov chain compression

Fuente: arXiv
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Autores principales: Fornace, Mark, Lindsey, Michael
Formato: Preprint
Publicado: 2025
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author Fornace, Mark
Lindsey, Michael
author_facet Fornace, Mark
Lindsey, Michael
contents We develop a framework for the compression of reversible Markov chains with rigorous error control. Given a subset of selected states, we construct reduced dynamics that can be lifted to an approximation of the full dynamics, and we prove simple spectral and nuclear norm bounds on the recovery error in terms of a suitably interpreted Nyström approximation error. We introduce two compression schemes: a projective compression based on committor functions and a structure-preserving compression defined in terms of an induced Markov chain over the selected states. The Nyström error appearing in our bounds can be controlled using recent results on column subset selection by nuclear maximization. Numerical experiments validate our theory and demonstrate the scalability of our approach.
format Preprint
id arxiv_https___arxiv_org_abs_2506_22918
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle An approximation theory for Markov chain compression
Fornace, Mark
Lindsey, Michael
Numerical Analysis
Probability
We develop a framework for the compression of reversible Markov chains with rigorous error control. Given a subset of selected states, we construct reduced dynamics that can be lifted to an approximation of the full dynamics, and we prove simple spectral and nuclear norm bounds on the recovery error in terms of a suitably interpreted Nyström approximation error. We introduce two compression schemes: a projective compression based on committor functions and a structure-preserving compression defined in terms of an induced Markov chain over the selected states. The Nyström error appearing in our bounds can be controlled using recent results on column subset selection by nuclear maximization. Numerical experiments validate our theory and demonstrate the scalability of our approach.
title An approximation theory for Markov chain compression
topic Numerical Analysis
Probability
url https://arxiv.org/abs/2506.22918