{"title":"从随时间变化的时刻推断熵的产生","authors":"Prashant Singh, Karel Proesmans","doi":"10.1038/s42005-024-01725-3","DOIUrl":null,"url":null,"abstract":"Measuring entropy production of a system directly from the experimental data is highly desirable since it gives a quantifiable measure of the time-irreversibility for non-equilibrium systems and can be used as a cost function to optimize the performance of the system. Although numerous methods are available to infer the entropy production of stationary systems, there are only a limited number of methods that have been proposed for time-dependent systems and, to the best of our knowledge, none of these methods have been applied to experimental systems. Herein, we develop a general non-invasive methodology to infer a lower bound on the mean total entropy production for arbitrary time-dependent continuous-state Markov systems in terms of the moments of the underlying state variables. The method gives quite accurate estimates for the entropy production, both for theoretical toy models and for experimental bit erasure, even with a very limited amount of experimental data. Directly measuring entropy production from experimental data without prior knowledge of the underlying model is highly desirable, as it quantifies time-irreversibility in non-equilibrium systems and can be used to optimize system performance. In this work, the authors have developed a general methodology to infer entropy production for arbitrary time-dependent systems from its first few moments. The method gives quite accurate estimates both for theoretical examples as well as for experimental data on bit erasure.","PeriodicalId":10540,"journal":{"name":"Communications Physics","volume":null,"pages":null},"PeriodicalIF":5.4000,"publicationDate":"2024-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s42005-024-01725-3.pdf","citationCount":"0","resultStr":"{\"title\":\"Inferring entropy production from time-dependent moments\",\"authors\":\"Prashant Singh, Karel Proesmans\",\"doi\":\"10.1038/s42005-024-01725-3\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Measuring entropy production of a system directly from the experimental data is highly desirable since it gives a quantifiable measure of the time-irreversibility for non-equilibrium systems and can be used as a cost function to optimize the performance of the system. Although numerous methods are available to infer the entropy production of stationary systems, there are only a limited number of methods that have been proposed for time-dependent systems and, to the best of our knowledge, none of these methods have been applied to experimental systems. Herein, we develop a general non-invasive methodology to infer a lower bound on the mean total entropy production for arbitrary time-dependent continuous-state Markov systems in terms of the moments of the underlying state variables. The method gives quite accurate estimates for the entropy production, both for theoretical toy models and for experimental bit erasure, even with a very limited amount of experimental data. Directly measuring entropy production from experimental data without prior knowledge of the underlying model is highly desirable, as it quantifies time-irreversibility in non-equilibrium systems and can be used to optimize system performance. In this work, the authors have developed a general methodology to infer entropy production for arbitrary time-dependent systems from its first few moments. The method gives quite accurate estimates both for theoretical examples as well as for experimental data on bit erasure.\",\"PeriodicalId\":10540,\"journal\":{\"name\":\"Communications Physics\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":5.4000,\"publicationDate\":\"2024-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.nature.com/articles/s42005-024-01725-3.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Communications Physics\",\"FirstCategoryId\":\"101\",\"ListUrlMain\":\"https://www.nature.com/articles/s42005-024-01725-3\",\"RegionNum\":1,\"RegionCategory\":\"物理与天体物理\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"PHYSICS, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Communications Physics","FirstCategoryId":"101","ListUrlMain":"https://www.nature.com/articles/s42005-024-01725-3","RegionNum":1,"RegionCategory":"物理与天体物理","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"PHYSICS, MULTIDISCIPLINARY","Score":null,"Total":0}
Inferring entropy production from time-dependent moments
Measuring entropy production of a system directly from the experimental data is highly desirable since it gives a quantifiable measure of the time-irreversibility for non-equilibrium systems and can be used as a cost function to optimize the performance of the system. Although numerous methods are available to infer the entropy production of stationary systems, there are only a limited number of methods that have been proposed for time-dependent systems and, to the best of our knowledge, none of these methods have been applied to experimental systems. Herein, we develop a general non-invasive methodology to infer a lower bound on the mean total entropy production for arbitrary time-dependent continuous-state Markov systems in terms of the moments of the underlying state variables. The method gives quite accurate estimates for the entropy production, both for theoretical toy models and for experimental bit erasure, even with a very limited amount of experimental data. Directly measuring entropy production from experimental data without prior knowledge of the underlying model is highly desirable, as it quantifies time-irreversibility in non-equilibrium systems and can be used to optimize system performance. In this work, the authors have developed a general methodology to infer entropy production for arbitrary time-dependent systems from its first few moments. The method gives quite accurate estimates both for theoretical examples as well as for experimental data on bit erasure.
期刊介绍:
Communications Physics is an open access journal from Nature Research publishing high-quality research, reviews and commentary in all areas of the physical sciences. Research papers published by the journal represent significant advances bringing new insight to a specialized area of research in physics. We also aim to provide a community forum for issues of importance to all physicists, regardless of sub-discipline.
The scope of the journal covers all areas of experimental, applied, fundamental, and interdisciplinary physical sciences. Primary research published in Communications Physics includes novel experimental results, new techniques or computational methods that may influence the work of others in the sub-discipline. We also consider submissions from adjacent research fields where the central advance of the study is of interest to physicists, for example material sciences, physical chemistry and technologies.