# Item

ITEM ACTIONSEXPORT

Released

Journal Article

#### Statistics of Infima and Stopping Times of Entropy Production and Applications to Active Molecular Processes

##### MPS-Authors

There are no MPG-Authors available

##### External Ressource

https://publications.mpi-cbg.de/Neri_2017_6813.pdf

(Any fulltext)

##### Fulltext (public)

There are no public fulltexts stored in PuRe

##### Supplementary Material (public)

There is no public supplementary material available

##### Citation

Neri, I., Roldán, É., & Jülicher, F. (2017). Statistics of Infima and Stopping
Times of Entropy Production and Applications to Active Molecular Processes.* Physical Review X,*
*7*(1): 011019. doi:10.1103/PhysRevX.7.011019.

Cite as: http://hdl.handle.net/21.11116/0000-0002-8C5F-7

##### Abstract

We study the statistics of infima, stopping times, and passage probabilities of entropy production in nonequilibrium steady states, and we show that they are universal. We consider two examples of stopping times: first-passage times of entropy production and waiting times of stochastic processes, which are the times when a system reaches a given state for the first time. Our main results are as follows: (i) The distribution of the global infimum of entropy production is exponential with mean equal to minus Boltzmann's constant; (ii) we find exact expressions for the passage probabilities of entropy production; (iii) we derive a fluctuation theorem for stopping-time distributions of entropy production. These results have interesting implications for stochastic processes that can be discussed in simple colloidal systems and in active molecular processes. In particular, we show that the timing and statistics of discrete chemical transitions of molecular processes, such as the steps of molecular motors, are governed by the statistics of entropy production. We also show that the extreme-value statistics of active molecular processes are governed by entropy production; for example, we derive a relation between the maximal excursion of a molecular motor against the direction of an external force and the infimum of the corresponding entropy-production fluctuations. Using this relation, we make predictions for the distribution of the maximum backtrack depth of RNA polymerases, which follow from our universal results for entropy-production infima.