Going beyond Landauer: Information-cost relations from inference based on the maximum entropy principle

• URL: http://arxiv.org/abs/2509.17060v2
• Date: Sun, 09 Nov 2025 09:45:37 GMT
• Title: Going beyond Landauer: Information-cost relations from inference based on the maximum entropy principle
• Authors: Yuanyuan Xiao, Jian-Hua Jiang, Junjie Liu,
• Abstract summary: We derive general information-cost trade-off relations based on the maximum entropy principle.<n>We numerically validate our information-cost trade-off relations using a coupled-qubit system exchanging energy and excitations.<n>Our results underscore the broad utility of maximum-entropy inference in constraining thermodynamic costs for generic finite-time quantum processes.
• Score: 10.21983319647914
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: The Landauer's principle, a cornerstone of information thermodynamics, provides a fundamental lower bound on the energetic cost of information erasure in terms of the information content change. However, its traditional formulation is largely confined to systems exchanging solely energy with an ideal thermal bath. In this work, we derive general information-cost trade-off relations that go beyond the scope of Landauer's principle by developing a thermodynamic inference approach based on the maximum entropy principle. These relations require only information about the system and are applicable to complex quantum scenarios involving multiple conserved charges and non-thermal environments. Specifically, we present two key results: (i) In scenarios where only the mean values of observables are accessible, we derive an information-content-informed upper bound on the thermodynamic cost which complements an existing generalized Landauer lower bound. (ii) When second-order fluctuations can also be measured, we obtain an information-content-informed lower bound on the change in variances of observables, thereby extending the Landauer's principle to constrain higher-order fluctuation costs. We numerically validate our information-cost trade-off relations using a coupled-qubit system exchanging energy and excitations, a driven qubit implementing an information erasure process, and a driven double quantum dot system that can operate as an inelastic heat engine. Our results underscore the broad utility of maximum-entropy inference in constraining thermodynamic costs for generic finite-time quantum processes, with direct relevance to quantum information processing and quantum thermodynamic applications.

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