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Thermodynamics describes large-scale, slowly evolving systems. Two modern approaches generalize thermodynamics: fluctuation theorems, which concern finite-time nonequilibrium processes, and one-shot statistical mechanics, which concerns…

Statistical Mechanics · Physics 2018-05-30 Nicole Yunger Halpern , Andrew J. P. Garner , Oscar C. O. Dahlsten , Vlatko Vedral

When reformulated as a resource theory, thermodynamics can analyze system behaviors in the single-shot regime. In this, the work required to implement state transitions is bounded by {\alpha}-Renyi divergences and so differs in identifying…

Quantum Physics · Physics 2024-06-25 Jinghao Lyu , Alexander B. Boyd , James P. Crutchfield

In a recent paper [Vaikuntanathan and Jarzynski, Phys. Rev. E {\bf 83}, 061120 (2011), arXiv:1105.1744] a model was introduced whereby work could be extracted from a thermal bath by measuring the energy of a particle that was thermalized by…

Statistical Mechanics · Physics 2015-06-17 Joakim Bergli

Evaluating the maximum amount of work extractable from a nanoscale quantum system is one of the central problems in quantum thermodynamics. Previous works identified the free energy of the input state as the optimal rate of extractable work…

Quantum Physics · Physics 2026-03-06 Kaito Watanabe , Ryuji Takagi

A central endeavor of thermodynamics is the measurement of free energy changes. Regrettably, although we can measure the free energy of a system in thermodynamic equilibrium, typically all we can say about the free energy of a…

Statistical Mechanics · Physics 2012-04-10 David A. Sivak , Gavin E. Crooks

We describe a formulation of multi-agents operating within a Cyber-Physical System, resulting in collaborative or adversarial games. We show that the non-determinism inherent in the communication medium between agents and the underlying…

Distributed, Parallel, and Cluster Computing · Computer Science 2024-07-09 Warisa Sritriratanarak , Paulo Garcia

Negotiation is a process where agents aim to work through disputes and maximize their surplus. As the use of deep reinforcement learning in bargaining games is unexplored, this paper evaluates its ability to exploit, adapt, and cooperate to…

Multiagent Systems · Computer Science 2020-02-19 Ho-Chun Herbert Chang

Auctions in which agents' payoffs are random variables have received increased attention in recent years. In particular, recent work in algorithmic mechanism design has produced mechanisms employing internal randomization, partly in…

Computer Science and Game Theory · Computer Science 2012-06-15 Shaddin Dughmi , Yuval Peres

We theoretically explore the Bochkov-Kuzovlev-Jarzynski-Crooks work theorems in a finite system subject to external control, which is coupled to a heat reservoir. We first elaborate the mechanical energy-balance between the system and the…

Statistical Mechanics · Physics 2015-09-02 Chang Sub Kim

We provide and axiomatize a representation for preferences over lotteries that generalizes the expected utility model. Since the representation uses different utility functions to evaluate different lotteries, the preferences can be…

Theoretical Economics · Economics 2026-03-17 Edward Honda , Keh-Kuan Sun

Consider a system in which players at nodes of an underlying graph G repeatedly play Prisoner's Dilemma against their neighbors. The players adapt their strategies based on the past behavior of their opponents by applying the so-called…

Discrete Mathematics · Computer Science 2008-12-08 Gabriel Istrate , Madhav V. Marathe , S. S. Ravi

In the real world, one almost never knows the parameters of a thermodynamic process to infinite precision. Reflecting this, here we investigate how to extend stochastic thermodynamics to systems with uncertain parameters, including…

Statistical Mechanics · Physics 2021-03-17 Jan Korbel , David H. Wolpert

In many multiagent settings, such as electric vehicle charging and traffic routing, agents must make decisions in the face of uncertain behavior exhibited by others. Often, this uncertainty arises from multiple sources, such as incomplete…

Computer Science and Game Theory · Computer Science 2026-04-28 Andreas Feik , Nicolas Lanzetti , Saverio Bolognani , Florian Dörfler , Dario Paccagnan

We consider the task of extracting work from quantum systems in the resource theory perspective of thermodynamics, where free states are arbitrary thermal states, and allowed operations are energy conserving unitary transformations. Taking…

Quantum Physics · Physics 2013-02-13 Paul Skrzypczyk , Anthony J. Short , Sandu Popescu

We analyze work extraction protocols using the long-lived quantum coherence of a three-level quantum system, which is coupled to a thermal bath through dipole-monopole interactions. We identify situations where persistent quantum coherence…

Quantum Physics · Physics 2025-08-05 Wenjing Chen , Si-Wei Han , Xiaoshan Feng , Jun Feng

The second law of thermodynamics uses change in free energy of macroscopic systems to set a bound on performed work. Ergotropy plays a similar role in microscopic scenarios, and is defined as the maximum amount of energy that can be…

Quantum Physics · Physics 2022-10-19 Tanmoy Biswas , Marcin Łobejko , Paweł Mazurek , Konrad Jałowiecki , Michał Horodecki

Adversarial risk quantifies the performance of classifiers on adversarially perturbed data. Numerous definitions of adversarial risk -- not all mathematically rigorous and differing subtly in the details -- have appeared in the literature.…

Machine Learning · Statistics 2022-01-25 Muni Sreenivas Pydi , Varun Jog

We present a critical examination of the difficulties with the quantum versions of a lifted weight that are widely used as work storage systems in quantum thermodynamics. To overcome those difficulties, we turn to the strong connections…

Quantum Physics · Physics 2019-06-05 Shang-Yung Wang

The generalization of the Zubarev nonequilibrium statistical operator method for the case of Renyi statistics is proposed when the relevant statistical operator (or distribution function) is obtained based on the principle of maximum for…

Statistical Mechanics · Physics 2011-01-11 B. Markiv , R. Tokarchuk , P. Kostrobij , M. Tokarchuk

We present a general framework for evolutionary learning to emergent unbiased state representation without any supervision. Evolutionary frameworks such as self-play converge to bad local optima in case of multi-agent reinforcement learning…

Machine Learning · Statistics 2023-02-03 Shohei Ohsawa
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