Yating Wang, Enmai Lei, Yu-Han Ma, Z. C. Tu, Geng Li
{"title":"Thermodynamic Geometric Control of Active Matter","authors":"Yating Wang, Enmai Lei, Yu-Han Ma, Z. C. Tu, Geng Li","doi":"arxiv-2409.09994","DOIUrl":null,"url":null,"abstract":"Active matter represents a class of non-equilibrium systems that constantly\ndissipate energy to produce directed motion. The thermodynamic control of\nactive matter holds great potential for advancements in synthetic molecular\nmotors, targeted drug delivery, and adaptive smart materials. However, the\ninherently non-equilibrium nature of active matter poses a significant\nchallenge in achieving optimal control with minimal energy cost. In this work,\nwe extend the concept of thermodynamic geometry, traditionally applied to\npassive systems, to active matter, proposing a systematic geometric framework\nfor minimizing energy cost in non-equilibrium driving processes. We derive a\ncost metric that defines a Riemannian manifold for control parameters, enabling\nthe use of powerful geometric tools to determine optimal control protocols. The\ngeometric perspective reveals that, unlike in passive systems, minimizing\nenergy cost in active systems involves a trade-off between intrinsic and\nexternal dissipation, leading to an optimal transportation speed that coincides\nwith the self-propulsion speed of active matter. This insight enriches the\nbroader concept of thermodynamic geometry. We demonstrate the application of\nthis approach by optimizing the performance of an active monothermal engine\nwithin this geometric framework.","PeriodicalId":501520,"journal":{"name":"arXiv - PHYS - Statistical Mechanics","volume":"8 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - PHYS - Statistical Mechanics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.09994","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Active matter represents a class of non-equilibrium systems that constantly
dissipate energy to produce directed motion. The thermodynamic control of
active matter holds great potential for advancements in synthetic molecular
motors, targeted drug delivery, and adaptive smart materials. However, the
inherently non-equilibrium nature of active matter poses a significant
challenge in achieving optimal control with minimal energy cost. In this work,
we extend the concept of thermodynamic geometry, traditionally applied to
passive systems, to active matter, proposing a systematic geometric framework
for minimizing energy cost in non-equilibrium driving processes. We derive a
cost metric that defines a Riemannian manifold for control parameters, enabling
the use of powerful geometric tools to determine optimal control protocols. The
geometric perspective reveals that, unlike in passive systems, minimizing
energy cost in active systems involves a trade-off between intrinsic and
external dissipation, leading to an optimal transportation speed that coincides
with the self-propulsion speed of active matter. This insight enriches the
broader concept of thermodynamic geometry. We demonstrate the application of
this approach by optimizing the performance of an active monothermal engine
within this geometric framework.