Lokesh Muruga,Felix Ginot,Sarah A. M. Loos,Clemens Bechinger
{"title":"The extraction of work from hidden degrees of freedom","authors":"Lokesh Muruga,Felix Ginot,Sarah A. M. Loos,Clemens Bechinger","doi":"10.1038/s41567-026-03442-w","DOIUrl":null,"url":null,"abstract":"Abstract Thermodynamics establishes that information acquired through measurement can be converted into work, as exemplified by Maxwell’s demon and Szilard engines. Most experimental realizations of information engines, however, implicitly assume Markovian environments, in which information exchanged with the surroundings is irreversibly lost. Many physical systems instead exhibit environmental memory, with hidden degrees of freedom retaining correlations with the history of the system and giving rise to non-Markovian dynamics. Whether and how such concealed memory can be harnessed as a thermodynamic resource has remained an open question. Here we experimentally demonstrate the extraction of work from environmental memory. Using time-resolved measurements on an optically trapped Brownian particle in equilibrium, we implement a time-delayed double-measurement protocol that retrieves information through backflow from hidden bath degrees of freedom. We show that this information backflow alters the relaxation dynamics, can be quantified independently of initial state effects and—when appropriately exploited—enhances work extraction. Notably, we identify regimes in which the extracted work exceeds the energy stored in the observable degree of freedom alone. Our results establish environmental memory as an experimentally accessible thermodynamic resource and reveal how non-Markovian dynamics can be systematically explored to improve the performance of information engines operating in time-correlated environments.","PeriodicalId":19100,"journal":{"name":"Nature Physics","volume":"23 1","pages":""},"PeriodicalIF":18.0000,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature Physics","FirstCategoryId":"101","ListUrlMain":"https://doi.org/10.1038/s41567-026-03442-w","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}
引用次数: 0
Abstract
Abstract Thermodynamics establishes that information acquired through measurement can be converted into work, as exemplified by Maxwell’s demon and Szilard engines. Most experimental realizations of information engines, however, implicitly assume Markovian environments, in which information exchanged with the surroundings is irreversibly lost. Many physical systems instead exhibit environmental memory, with hidden degrees of freedom retaining correlations with the history of the system and giving rise to non-Markovian dynamics. Whether and how such concealed memory can be harnessed as a thermodynamic resource has remained an open question. Here we experimentally demonstrate the extraction of work from environmental memory. Using time-resolved measurements on an optically trapped Brownian particle in equilibrium, we implement a time-delayed double-measurement protocol that retrieves information through backflow from hidden bath degrees of freedom. We show that this information backflow alters the relaxation dynamics, can be quantified independently of initial state effects and—when appropriately exploited—enhances work extraction. Notably, we identify regimes in which the extracted work exceeds the energy stored in the observable degree of freedom alone. Our results establish environmental memory as an experimentally accessible thermodynamic resource and reveal how non-Markovian dynamics can be systematically explored to improve the performance of information engines operating in time-correlated environments.
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