arXiv Analytics

Sign in

arXiv:1408.5477 [math.PR]AbstractReferencesReviewsResources

Flows, currents, and cycles for Markov Chains: large deviation asymptotics

L. Bertini, A. Faggionato, D. Gabrielli

Published 2014-08-23Version 1

We consider a continuous time Markov chain on a countable state space. We prove a joint large deviation principle (LDP) of the empirical measure and current in the limit of large time interval. The proof is based on results on the joint large deviations of the empirical measure and flow obtained in \cite{BFG}. By improving such results we also show, under additional assumptions, that the LDP holds with the strong L^1 topology on the space of currents. We deduce a general version of the Gallavotti-Cohen (GC) symmetry for the current field and show that it implies the so-called fluctuation theorem for the GC functional. We also analyze the large deviation properties of generalized empirical currents associated to a fundamental basis in the cycle space, which, as we show, are given by the first class homological coefficients in the graph underlying the Markov chain. Finally, we discuss in detail some examples.

Related articles: Most relevant | Search more
arXiv:1210.2004 [math.PR] (Published 2012-10-06, updated 2015-01-15)
Large deviations of the empirical flow for continuous time Markov chains
arXiv:1212.6908 [math.PR] (Published 2012-12-31)
From level 2.5 to level 2 large deviations for continuous time Markov chains
arXiv:1710.08001 [math.PR] (Published 2017-10-22)
Level 2.5 large deviations for continuous time Markov chains with time periodic rates