Dissipation-induced collective advantage of a quantum thermal machine

Author:

Carrega Matteo1ORCID,Razzoli Luca23ORCID,Erdman Paolo Andrea4ORCID,Cavaliere Fabio15ORCID,Benenti Giuliano236ORCID,Sassetti Maura15ORCID

Affiliation:

1. CNR-SPIN 1 , Via Dodecaneso 33, 16146 Genova, Italy

2. Center for Nonlinear and Complex Systems, Dipartimento di Scienza e Alta Tecnologia, Università degli Studi dell'Insubria 2 , Via Valleggio 11, 22100 Como, Italy

3. Istituto Nazionale di Fisica Nucleare, Sezione di Milano 3 , Via Celoria 16, 20133 Milano, Italy

4. Department of Mathematics and Computer Science, Freie Universität Berlin 4 , Arnimallee 6, 14195 Berlin, Germany

5. Dipartimento di Fisica, Università di Genova 5 , Via Dodecaneso 33, 16146 Genova, Italy

6. NEST, Istituto Nanoscienze-CNR 6 , Piazza San Silvestro 12, I-56127 Pisa, Italy

Abstract

Do quantum correlations lead to better performance with respect to several different systems working independently? For quantum thermal machines, the question is whether a working medium (WM) made of N constituents exhibits better performance than N independent engines working in parallel. Here, by inspecting a microscopic model with the WM composed by two non-interacting quantum harmonic oscillators, we show that the presence of a common environment can mediate non-trivial correlations in the WM leading to better quantum heat engine performance—maximum power and efficiency—with respect to an independent configuration. Furthermore, this advantage is striking for strong dissipation, a regime in which two independent engines cannot deliver any useful power. Our results show that dissipation can be exploited as a useful resource for quantum thermal engines and are then corroborated by optimization techniques here extended to non-Markovian quantum heat engines.

Funder

Ministero dell'Università e della Ricerca

Julian Schwinger Foundation for Physics Research

Instituto Nazionale di Fisica Nucleare

Berlin Mathematics Research Center MATH+

Publisher

American Vacuum Society

Reference93 articles.

Cited by 3 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3