{ "id": "1907.01582", "version": "v1", "published": "2019-07-02T18:39:38.000Z", "updated": "2019-07-02T18:39:38.000Z", "title": "Minimum Power to Maintain a Nonequilibrium Distribution of a Markov Chain", "authors": [ "Dmitri S. Pavlichin", "Yihui Quek", "Tsachy Weissman" ], "comment": "9 pages, 5 figures", "categories": [ "cond-mat.stat-mech", "cs.IT", "math.IT", "physics.bio-ph" ], "abstract": "Biological systems use energy to maintain non-equilibrium distributions for long times, e.g. of chemical concentrations or protein conformations. What are the fundamental limits of the power used to \"hold\" a stochastic system in a desired distribution over states? We study the setting of an uncontrolled Markov chain $Q$ altered into a controlled chain $P$ having a desired stationary distribution. Thermodynamics considerations lead to an appropriately defined Kullback-Leibler (KL) divergence rate $D(P||Q)$ as the cost of control, a setting introduced by Todorov, corresponding to a Markov decision process with mean log loss action cost. The optimal controlled chain $P^*$ minimizes the KL divergence rate $D(\\cdot||Q)$ subject to a stationary distribution constraint, and the minimal KL divergence rate lower bounds the power used. While this optimization problem is familiar from the large deviations literature, we offer a novel interpretation as a minimum \"holding cost\" and compute the minimizer $P^*$ more explicitly than previously available. We state a version of our results for both discrete- and continuous-time Markov chains, and find nice expressions for the important case of a reversible uncontrolled chain $Q$, for a two-state chain, and for birth-and-death processes.", "revisions": [ { "version": "v1", "updated": "2019-07-02T18:39:38.000Z" } ], "analyses": { "keywords": [ "markov chain", "minimum power", "nonequilibrium distribution", "minimal kl divergence rate lower", "mean log loss action cost" ], "note": { "typesetting": "TeX", "pages": 9, "language": "en", "license": "arXiv", "status": "editable" } } }