Graph-combinatorial approach for large deviations of Markov chains

Giorgio Carugno Carugno, Pierpaolo Vivo, Francesco Coghi*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)
45 Downloads (Pure)


We consider discrete-time Markov chains and study large deviations of the pair empirical occupation measure, which is useful to compute fluctuations of pure-additive and jump-type observables. We provide an exact expression for the finite-time moment generating function, which is split in cycles and paths contributions, and scaled cumulant generating function of the pair empirical occupation measure via a graph-combinatorial approach. The expression obtained allows us to give a physical interpretation of interaction and entropic terms, and of the Lagrange multipliers, and may serve as a starting point for sub-leading asymptotics. We illustrate the use of the method for a simple two-state Markov chain.
Original languageEnglish
Article number295001
JournalJournal of Physics A
Issue number29
Publication statusPublished - 4 Jul 2022


Dive into the research topics of 'Graph-combinatorial approach for large deviations of Markov chains'. Together they form a unique fingerprint.

Cite this