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We consider overdamped Brownian particles with two degrees of freedom (DoF) that are confined in a time-varying quadratic potential and are in simultaneous contact with heat baths of different temperatures along the respective DoF. The…

Statistical Mechanics · Physics 2024-06-21 Jordi Ventura Siches , Olga Movilla Miangolarra , Tryphon T. Georgiou

Ergotropy, the maximum work extractable from a quantum system, is a central resource in quantum physics. Computing ergotropy is well established when the system state is fully known, but its estimation under partial information remains an…

We introduce a single-qubit quantum measurement engine fuelled by backaction energy input. To reduce energetic costs associated with information processing, the measurement outcomes are only used with a prescribed laziness probability in…

Quantum Physics · Physics 2025-06-25 Léa Bresque , Debraj Das , Édgar Roldán

Gathering information about a system enables greater control over it. This principle lies at the core of information engines, which use measurement-based feedback to rectify thermal noise and convert information into work. Originating from…

Statistical Mechanics · Physics 2025-01-24 Rémi Goerlich , Laura Hoek , Omer Chor , Saar Rahav , Yael Roichman

Quantum Szilard engine constitutes an adequate interplay of thermodynamics, information theory and quantum mechanics. Szilard engines are in general operated by a Maxwell's Demon where Landauer's principle resolves the apparent paradoxes.…

Quantum Physics · Physics 2020-04-22 Alhun Aydin , Altug Sisman , Ronnie Kosloff

We consider the efficiency of chemical energy extraction from the environment by the growth of a copolymer made of two constituent units in the entropy-driven regime. We show that the thermodynamic nonlinearity associated with the…

Statistical Mechanics · Physics 2015-05-13 Massimiliano Esposito , Katja Lindenberg , Christian Van den Broeck

In the Minimum Description Length (MDL) principle, learning from the data is equivalent to an optimal coding problem. We show that the codes that achieve optimal compression in MDL are critical in a very precise sense. First, when they are…

Methodology · Statistics 2018-10-03 Ryan John Cubero , Matteo Marsili , Yasser Roudi

We review recent studies of a colloidal information engine that consists of a bead in water and held by an optical trap. The bead is ratcheted upward without any apparent external work, by taking advantage of favorable thermal fluctuations.…

Statistical Mechanics · Physics 2024-12-30 Johan du Buisson , David A. Sivak , John Bechhoefer

This paper presents new lower and upper bounds for the optimal compression of binary prefix codes in terms of the most probable input symbol, where compression efficiency is determined by the nonlinear codeword length objective of…

Information Theory · Computer Science 2008-09-09 Michael Baer

Optimisation of heat engines at the micro-scale has applications in biological and artificial nano-technology, and stimulates theoretical research in non-equilibrium statistical physics. Here we consider non-interacting overdamped particles…

Soft Condensed Matter · Physics 2021-06-02 Giulia Gronchi , Andrea Puglisi

Maximum quantum work extraction is generally defined in terms of the ergotropy functional, no matter how experimentally complicated is the implementation of the optimal unitary allowing for it, especially in the case of multipartite…

Quantum Physics · Physics 2025-01-27 Riccardo Castellano , Ranieri Nery , Kyrylo Simonov , Donato Farina

Optimizing the performance of thermal machines is an essential task of thermodynamics. We here consider the optimization of information engines that convert information about the state of a system into work. We concretely introduce a…

Quantum Physics · Physics 2023-06-28 Paul Fadler , Alexander Friedenberger , Eric Lutz

Information erasure inevitably leads to heat dissipation. Minimizing this dissipation will be crucial for developing small-scale information processing systems, but little is known about the optimal procedures required. We have obtained…

Statistical Mechanics · Physics 2015-06-17 Patrick R. Zulkowski , Michael R. DeWeese

Ergotropy, as a measure for extractable work from a quantum system, has garnered significant attention due to its relevance in quantum thermodynamics and information processing. In this work, the dynamics of ergotropy will be investigated…

Quantum Physics · Physics 2024-06-04 Maryam Hadipour , Soroush Haseli

We consider a class of quantum heat engines consisting of two subsystems interacting via a unitary transformation and coupled to two separate baths at different temperatures $T_h > T_c$. The purpose of the engine is to extract work due to…

Statistical Mechanics · Physics 2009-11-13 Armen E. Allahverdyan , Ramandeep S. Johal , Guenter Mahler

Energy extraction is a central task in thermodynamics. In quantum physics, ergotropy measures the amount of work extractable under cyclic Hamiltonian control. As its full extraction requires perfect knowledge of the initial state, however,…

Quantum Physics · Physics 2023-05-31 Dominik Šafránek , Dario Rosa , Felix Binder

This letter exposes a tight connection between the thermodynamic efficiency of information processing and predictive inference. A generalized lower bound on dissipation is derived for partially observable information engines which are…

Statistical Mechanics · Physics 2020-02-12 Susanne Still

Quantum measurement of a system can change its mean energy, as well as entropy. A selective measurement (classical or quantum) can be used as a "Maxwell's demon" to power a single-temperature heat engine, by decreasing the entropy. Quantum…

Quantum Physics · Physics 2010-11-05 Noam Erez

Inspired by the available examples of Microcanonical Szil\'ard Engines and by the original Szil\'ard Engine, we devise a system with two degrees of freedom whose ensemble average energy, starting with a microcanical ensemble, decreases…

Statistical Mechanics · Physics 2019-08-23 Artur Soriani , Marcus V. S. Bonança

We propose a regularization framework inspired by thermodynamic work for guiding pre-trained probability flow generative models (e.g., continuous normalizing flows or diffusion models) by minimizing excess work, a concept rooted in…

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