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Averaging and large deviation principles for fully-coupled piecewise deterministic Markov processes and applications to molecular motors

2008/08/13 by Alessandra Faggionato, A. Faggionato, Davide Gabrielli +5 · 1 citation
Biochemistry, Genetics and Molecular Biology · Mathematics · Physics and Astronomy · #34C29 #60F10 #80A30 #FOS: Mathematics #FOS: Physical sciences #Force Microscopy Techniques and Applications #Mathematical Physics (math-ph) #Probability (math.PR) #Protein Structure and Dynamics #math-ph #math.MP #math.PR #msc:34C29 #msc:60F10 #msc:80A30 #stochastic dynamics and bifurcation

paper · pdf · doi:10.48550/arxiv.0808.1910

weaker assumptions

openalex publication_date 2008/08/13 · arxiv created 2008/09/16 · arxiv updated 2009/12/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We consider Piecewise Deterministic Markov Processes (PDMPs) with a finite set of discrete states. In the regime of fast jumps between discrete states, we prove a law of large number and a large deviation principle. In the regime of fast and slow jumps, we analyze a coarse-grained process associated to the original one and prove its convergence to a new PDMP with effective force fields and jump rates. In all the above cases, the continuous variables evolve slowly according to ODEs. Finally, we discuss some applications related to the mechanochemical cycle of macromolecules, including strained--dependent power--stroke molecular motors. Our analysis covers the case of fully--coupled slow and fast motions.

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