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

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

weaker assumptions

Scientific paper

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.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Averaging and large deviation principles for fully-coupled piecewise deterministic Markov processes and applications to molecular motors does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Averaging and large deviation principles for fully-coupled piecewise deterministic Markov processes and applications to molecular motors, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Averaging and large deviation principles for fully-coupled piecewise deterministic Markov processes and applications to molecular motors will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-584178

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.