SCIENCE@home

Quantifying dissipation using fluctuating currents

Junang Li,J. Horowitz,Todd R. Gingrich,N. Fakhri

Published 2018 in Nature Communications

ABSTRACT

Systems coupled to multiple thermodynamic reservoirs can exhibit nonequilibrium dynamics, breaking detailed balance to generate currents. To power these currents, the entropy of the reservoirs increases. The rate of entropy production, or dissipation, is a measure of the statistical irreversibility of the nonequilibrium process. By measuring this irreversibility in several biological systems, recent experiments have detected that particular systems are not in equilibrium. Here we discuss three strategies to replace binary classification (equilibrium versus nonequilibrium) with a quantification of the entropy production rate. To illustrate, we generate time-series data for the evolution of an analytically tractable bead-spring model. Probability currents can be inferred and utilized to indirectly quantify the entropy production rate, but this approach requires prohibitive amounts of data in high-dimensional systems. This curse of dimensionality can be partially mitigated by using the thermodynamic uncertainty relation to bound the entropy production rate using statistical fluctuations in the probability currents. The determination of entropy production from experimental data is a challenge but a recently introduced theoretical tool, the thermodynamic uncertainty relation, allows one to infer a lower bound on entropy production. Here the authors provide a critical assessment of the practical implementation of this tool.

PUBLICATION RECORD

CITATION MAP

EXTRACTION MAP

CLAIMS

  • No claims are published for this paper.

CONCEPTS

  • No concepts are published for this paper.

REFERENCES

Showing 1-73 of 73 references · Page 1 of 1

CITED BY

Showing 1-100 of 237 citing papers · Page 1 of 3

123
Next