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The simulation of low-temperature properties of many-body systems remains one of the major challenges in theoretical and experimental quantum information science. We present, and demonstrate experimentally, a universal cooling method which…

We introduce a family of Maxwellian Demons for which correlations among information bearing degrees of freedom can be calculated exactly and in compact analytical form. This allows one to precisely determine Demon functional thermodynamic…

Statistical Mechanics · Physics 2016-03-23 A. B. Boyd , D. Mandal , J. P. Crutchfield

Using classical thermodynamics, we argue that Maxwell's demon loses its battle against Clausius as any temperature difference or other thermodynamic forces it creates is immediately compensated by spontaneous counterbalancing flows that…

Classical Physics · Physics 2022-01-03 P. D. Gujrati

The problem of possible violation of the second law of thermodynamics is discussed. It is noted that the task of the well known challenge to the second law called Maxwell's demon is put in order a chaotic perpetual motion and if any ordered…

Statistical Mechanics · Physics 2009-11-10 V. V. Aristov , A. V. Nikulov

Converting information into work has during the last decade gained renewed interest as it gives insight into the relation between information theory and thermodynamics. Here we theoretically investigate an implementation of Maxwell's demon…

Mesoscale and Nanoscale Physics · Physics 2020-04-09 Björn Annby-Andersson , Peter Samuelsson , Ville F. Maisi , Patrick P. Potts

Maxwell's demon elucidates the value of information in thermodynamics, using measurement and feedback: he evolves an equilibrated gas into a nonequilibrium state, from which one might extract work. The demon can evolve the system farther…

A quantum mechanical Maxwell demon is proposed in a quantum dot setting. The demon avoids continuous-measurement induced decoherence by exploiting an undetailed charge detector. The control of coherent tunneling via…

Mesoscale and Nanoscale Physics · Physics 2026-03-10 Lucas Trigal , Rafael Sánchez

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

Biology achieves novel functions like error correction, ultra-sensitivity and accurate concentration measurement at the expense of free energy through Maxwell Demon-like mechanisms. The design principles and free energy trade-offs have been…

Molecular Networks · Quantitative Biology 2016-05-27 Arvind Murugan , Suriyanarayanan Vaikuntanathan

The remarkable progress of artificial intelligence (AI) has revealed the enormous energy demands of modern digital architectures, raising deep concerns about sustainability. In stark contrast, the human brain operates efficiently on only…

Biological Physics · Physics 2025-11-03 Toshio Yanagida , Keisuke Fujita , Mitsuhiro Iwaki

We consider the stationary state of a Markov process on a bipartite system from the perspective of stochastic thermodynamics. One subsystem is used to extract work from a heat bath while being affected by the second subsystem. We show that…

Statistical Mechanics · Physics 2014-03-03 David Hartich , Andre C. Barato , Udo Seifert

The paradox of Maxwell's demon motivated the development of information thermodynamics and the creation of nanoscale information engines. We now understand that machines such as the molecular motors within cells can in principle harvest…

Maxwell's demon principle of extracting valuable resources through measuring fluctuations in the system already stimulated modern quantum physics. In contrast to classical physics, a free coupling to a probe and its free measurement…

Quantum Physics · Physics 2023-03-03 Atirach Ritboon , Radim Filip

We describe a minimal model of a quantum Maxwell demon obeying Hamiltonian dynamics. The model is solved exactly, and we analyze its steady-state behavior. We find that writing information to a quantum memory induces a probability current…

Statistical Mechanics · Physics 2013-12-18 Sebastian Deffner

Maxwell's Demon, 'a being whose faculties are so sharpened that he can follow every molecule in its course', has been the centre of much debate about its abilities to violate the second law of thermodynamics. Landauer's hypothesis, that the…

Logic in Computer Science · Computer Science 2015-11-06 Samson Abramsky , Dominic Horsman

With the increasing interest for the control of the system at the nano and mesoscopic scales, studies have been focused on the limit of the energy dissipation in an open system by refining the concept of the Maxwell's demon. The well-known…

Statistical Mechanics · Physics 2020-08-26 Qian Zeng , Jin Wang

In order to describe quantum heat engines, here we systematically study isothermal and isochoric processes for quantum thermodynamic cycles. Based on these results the quantum versions of both the Carnot heat engine and the Otto heat engine…

Quantum Physics · Physics 2007-10-29 H. T. Quan , Yu-xi Liu , C. P. Sun , Franco Nori

Quantum correlation, or entanglement, is now believed to be an indispensable physical resource for certain tasks in quantum information processing, for which classically correlated states cannot be useful. Besides information processing,…

Quantum Physics · Physics 2009-11-10 K. Maruyama , F. Morikoshi , V. Vedral

We identify that quantum coherence is a valuable resource in the quantum heat engine, which is designed in a quantum thermodynamic cycle assisted by a quantum Maxwell's demon. This demon is in a superposed state. The quantum work and heat…

Quantum Physics · Physics 2025-09-09 Yun-Hao Shi , Hai-Long Shi , Xiao-Hui Wang , Ming-Liang Hu , Si-Yuan Liu , Wen-Li Yang , Heng Fan

Scientific Machine Learning (SciML) integrates physics and data into the learning process, offering improved generalization compared with purely data-driven models. Despite its potential, applications of SciML in prognostics remain limited,…

Machine Learning · Computer Science 2025-11-04 Ibai Ramirez , Jokin Alcibar , Joel Pino , Mikel Sanz , David Pardo , Jose I. Aizpurua