Inferring broken detailed balance in the absence of observable currents

Non-equilibrium systems with hidden states are relevant for biological systems such as molecular motors. Here the authors introduce a method for quantifying irreversibility in such a system by exploiting the fluctuations in the waiting times of time series data.

Bibliographic Details
Main Authors: Ignacio A. Martínez, Gili Bisker, Jordan M. Horowitz, Juan M. R. Parrondo
Format: Article
Language:English
Published: Nature Portfolio 2019-08-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-019-11051-w
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author Ignacio A. Martínez
Gili Bisker
Jordan M. Horowitz
Juan M. R. Parrondo
author_facet Ignacio A. Martínez
Gili Bisker
Jordan M. Horowitz
Juan M. R. Parrondo
author_sort Ignacio A. Martínez
collection DOAJ
description Non-equilibrium systems with hidden states are relevant for biological systems such as molecular motors. Here the authors introduce a method for quantifying irreversibility in such a system by exploiting the fluctuations in the waiting times of time series data.
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spelling doaj.art-eae2441ec1554852a2432f46a495c4a12022-12-21T23:38:58ZengNature PortfolioNature Communications2041-17232019-08-0110111010.1038/s41467-019-11051-wInferring broken detailed balance in the absence of observable currentsIgnacio A. Martínez0Gili Bisker1Jordan M. Horowitz2Juan M. R. Parrondo3Departamento de Estructura de la Materia, Física Termica y Electronica and GISC, Universidad Complutense de MadridDepartment of Biomedical Engineering, Faculty of Engineering, Center for Physics and Chemistry of Living Systems, Center for Nanoscience and Nanotechnology, Center for Light-Matter Interaction, Tel Aviv UniversityDepartment of Biophysics, University of MichiganDepartamento de Estructura de la Materia, Física Termica y Electronica and GISC, Universidad Complutense de MadridNon-equilibrium systems with hidden states are relevant for biological systems such as molecular motors. Here the authors introduce a method for quantifying irreversibility in such a system by exploiting the fluctuations in the waiting times of time series data.https://doi.org/10.1038/s41467-019-11051-w
spellingShingle Ignacio A. Martínez
Gili Bisker
Jordan M. Horowitz
Juan M. R. Parrondo
Inferring broken detailed balance in the absence of observable currents
Nature Communications
title Inferring broken detailed balance in the absence of observable currents
title_full Inferring broken detailed balance in the absence of observable currents
title_fullStr Inferring broken detailed balance in the absence of observable currents
title_full_unstemmed Inferring broken detailed balance in the absence of observable currents
title_short Inferring broken detailed balance in the absence of observable currents
title_sort inferring broken detailed balance in the absence of observable currents
url https://doi.org/10.1038/s41467-019-11051-w
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