General linear thermodynamics for periodically driven systems with multiple reservoirs

Proesmans, Karel; Fiore, Carlos E.

doi:10.1103/physreve.100.022141

Cited by 16 publications

(30 citation statements)

References 39 publications

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“…The approach that we presented exploits the existence of a macroscopic limit with a LD principle and applies linear response to the LD rate function. A natural question to ask is whether this offers any advantage with respect to usual linear response theory [16][17][18][19][20][21], which directly gives the first order correction to the probability distribution (instead of the rate function associated to it), and does not require any macroscopic limit. We now show that our approach is more accurate than usual linear response and valid further away from equilibrium.…”

Section: Comparison With Usual Linear Responsementioning

confidence: 99%

“…We show that g(x) is fully determined by the deterministic dynamics, described by a drift vector field u(x), and the scalar field Ẇ (x) that indicates what is the rate at which work is performed on the system for a given state x. This result offers a practical method to determine g(x), which is applied to exactly solvable problems in electronics and chemistry , and is shown to be more accurate than usual linear response at the level of the probability distribution [16][17][18][19][20][21]. It can also be generalized to transient evolutions and non-autonomous settings.…”

Section: Introductionmentioning

confidence: 99%

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Linear response in large deviations theory: A method to compute non-equilibrium distributions

Freitas,

Falasco,

Esposito

2021

Preprint

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We consider thermodynamically consistent autonomous Markov jump processes displaying a macroscopic limit in which the logarithm of the probability distribution is proportional to a scaleindependent rate function (i.e., a large deviations principle is satisfied). In order to provide an explicit expression for the probability distribution valid away from equilibrium, we propose a linear response theory performed at the level of the rate function. We show that the first order nonequilibrium contribution to the steady state rate function, g(x), satisfies u(x) • ∇g(x) = −β Ẇ (x) where the vector field u(x) defines the macroscopic deterministic dynamics, and the scalar field Ẇ (x) equals the rate at which work is performed on the system in a given state x. This equation provides a practical way to determine g(x), significantly outperforms standard linear response theory applied at the level of the probability distribution, and approximates the rate function surprisingly well in some far-from-equilibrium conditions. The method applies to a wealth of physical and chemical systems, that we exemplify by two analytically tractable models -an electrical circuit and an autocatalytic chemical reaction network -both undergoing a non-equilibrium transition from a monostable phase to a bistable phase. Our approach can be easily generalized to transient probabilities and non-autonomous dynamics. Moreover, its recursive application generates a virtual flow in the probability space which allows to determine the steady state rate function arbitrarily far from equilibrium.

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Section: Comparison With Usual Linear Responsementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Linear response in large deviations theory: A method to compute non-equilibrium distributions

Freitas,

Falasco,

Esposito

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…The shape of Eq. (36) is similar to the linear irreversible thermodynamics [18,19,43], in which the entropy production is written down as a sum of flux-times-force expression. This similarity provides to reinterpret Eq.…”

Section: Bilinear Form and Onsager Coefficientsmentioning

confidence: 99%

“…Basically, a NESS can be generated under two fundamental ways: From fixed thermodynamic forces [15,16] or from time-periodic variation of external parameters [17][18][19][20]. In this contribution, we address a different kind of periodic driving, suitable for the description of engineered reservoirs, at which a system interacts sequentially and repeatedly with distinct environments [21][22][23].…”

Section: Introductionmentioning

confidence: 99%

Thermodynamics of collisional models for Brownian particles: General properties and efficiency

Stable

Noa

Oropesa

et al. 2020

Phys. Rev. Research

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We introduce the idea of collisional models for Brownian particles, in which a particle is sequentially placed in contact with distinct thermal environments and external forces. Thermodynamic properties are exactly obtained, irrespective of the number of reservoirs involved. In the presence of external forces, the entropy production presents a bilinear form in which Onsager coefficients are exactly calculated. Analysis of Brownian engines based on sequential thermal switchings is proposed and considerations about their efficiencies are investigated, taking into account distinct external forces protocols. Our results shed light to an alternative route for obtaining efficient thermal engines based on finite times Brownian machines.

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“…More recently, the stochastic thermodynamics of periodically driven systems [80,81,82,83] has attracted a great deal of interest in part because their thermodynamic properties can be experimentally accessible have attracted a great deal of interest [80,84,85,86,87,88,89,90,91,92,93,94,95,96,97,98,99,100,101]. In addition, some of their remarkable features, such as a general description in the linear regime ( in which Onsager coefficients and general reciprocal relations can be achieved), the existence of uncertainties constraints leading to existence of bounds among macroscopic averages and other features have been put under a firmer basis.…”

Section: Introductionmentioning

confidence: 99%

Entropy production and heat transport in harmonic chains under time-dependent periodic drivings

Akasaki¹

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Faço questão de escrever os agradecimentos em português para que todas as pessoas citadas possam entender a importância que tiveram para que essa dissertação se tornasse realidade.Primeiro, gostaria de agradecer o meu orientador, Carlos Fiore, por todo o auxílio desde que o conheci. Uma pessoa que ama imensamente o seu trabalho e se dedica a todo momento, e que conseguiu transmitir essa paixão por pesquisa e Física para mim. Além de ser um mentor, tenho a felicidade de dizer que é um grande amigo. Muito obrigado mesmo, pelas conversas, dicas e suporte. Sem você isso não teria sido possível.Agradeço aos meus pais, Jorge e Onilda, por todo o incentivo e por terem me apoiado quando tomei a decisão de seguir para o mestrado. Vocês servem de inspiração para que eu possa continuar me dedicando e me desafiando, e tem uma importância imensa em minha vida. Amo vocês! Agradeço ao Prof. Mario José de Oliveira pelas discussões e ideias em relação a esse trabalho, ao grupo do departamento pelas diversas conversas, ensinamentos e suporte, e aos professores que tive o prazer de conhecer durante esses dois anos.Por fim, gostaria de agradecer a minha família e amigos, que mesmo não os visitando tanto quanto gostaria, fizeram com que eu pudesse relaxar e me distrair em todas as vezes que nos vimos.

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General linear thermodynamics for periodically driven systems with multiple reservoirs

Cited by 16 publications

References 39 publications

Linear response in large deviations theory: A method to compute non-equilibrium distributions

Linear response in large deviations theory: A method to compute non-equilibrium distributions

Thermodynamics of collisional models for Brownian particles: General properties and efficiency

Entropy production and heat transport in harmonic chains under time-dependent periodic drivings

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