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Landauer's principle states that erasure of each bit of information in a system requires at least a unit of energy $k_B T \ln 2$ to be dissipated. In return, the blank bit may possibly be utilized to extract usable work of the amount $k_B T…

Mesoscale and Nanoscale Physics · Physics 2018-06-20 A. Mert Bozkurt , Baris Pekerten , Inanc Adagideli

The Landauer limit is to irreversible logic what the Carnot cycle is to heat engines. This limit is approached in the adiabatic Quantum Flux Parametron (aQFP) by copying the inputs of standard logic gates to produce reversible logic gates,…

Applied Physics · Physics 2025-04-08 Quentin Herr

The Szilard engine stands as a compelling illustration of the intricate interplay between information and thermodynamics. While at thermodynamic equilibrium, the apparent breach of the second law of thermodynamics was reconciled by Landauer…

Statistical Mechanics · Physics 2024-01-17 Luca Cocconi , Letian Chen

The standard relations between information theory and thermodynamics are challenged. The Szilard engine is revisited and the bound proposed by Landauer is replaced by a different one which includes errors in information processing. Instead…

Quantum Physics · Physics 2014-02-12 Robert Alicki

The rapid scaling of artificial intelligence models has revealed a fundamental tension between model capacity (storage) and inference efficiency (computation). While classical information theory focuses on transmission and storage limits,…

Information Theory · Computer Science 2026-01-01 Jianfeng Xu , Zeyan Li

We present the minimal energy costs for the measurement and the information erase, using only the Helmholtz free energy and the entanglement of formation. The entanglement of formation appears in the form of difference which indicates the…

Quantum Physics · Physics 2013-11-07 Hiroyasu Tajima

1. Strong and weak notions of erasure are distinguished according to whether the single erasure procedure does or does not leave the environment in the same state independently of the pre-erasure state. 2. Purely thermodynamic…

History and Philosophy of Physics · Physics 2025-02-26 John D. Norton

Biological, artificial, and physical systems dissipate energy to accurately transmit information. While tools of information theory have been used to characterize information-processing capabilities, how reliably this information is…

Statistical Mechanics · Physics 2026-05-29 Giorgio Nicoletti , Daniel M. Busiello

We discuss some features of thermodynamics in the presence of multiple conserved quantities. We prove a generalisation of Landauer principle illustrating tradeoffs between the erasure costs paid in different "currencies". We then show how…

Quantum Physics · Physics 2017-04-10 Matteo Lostaglio , David Jennings , Terry Rudolph

Motivated by the recent proposed models of the information engine [D. Mandal and C. Jarzynski, Proc. Natl. Acad. Sci. 109, 11641 (2012)] and the information refrigerator [D. Mandal, H. T. Quan, and C. Jarzynski, Phys. Rev. Lett. 111, 030602…

Statistical Mechanics · Physics 2015-06-30 Yuansheng Cao , Zongping Gong , H. T. Quan

We implement a thermal-fluctuation driven logical bit reset on a superconducting flux logic cell. We show that the logical state of the system can be continuously monitored with only a small perturbation to the thermally activated dynamics…

Landauer's principle bridges information theory and thermodynamics by linking the entropy change of a system during a process to the average energy dissipated to its environment. Although typically discussed in the context of erasing a…

We apply evolutionary reinforcement learning to a simulation model in order to identify efficient time-dependent erasure protocols for a physical realization of a one-bit memory by an underdamped mechanical cantilever. We show that these…

Statistical Mechanics · Physics 2025-05-13 Nicolas Barros , Stephen Whitelam , Sergio Ciliberto , Ludovic Bellon

Performing thermodynamic tasks within finite time while minimizing thermodynamic costs is a central challenge in stochastic thermodynamics. Here, we develop a unified framework for optimizing the thermodynamic cost of performing various…

Statistical Mechanics · Physics 2025-09-16 Kaito Tojo , Rihito Nagase , Ken Funo , Takahiro Sagawa

Mutual information between particle positions before and after mixing provides a universal assumption-free measure of mixing efficiency at low Reynolds number which accounts for the kinematic reversibility of the Stokes equation. For a…

Statistical Mechanics · Physics 2025-06-19 Luca Cocconi , Yihong Shi , Andrej Vilfan

Thermodynamic cost of communication is a major factor in the thermodynamic cost of real-world computers, both biological and digital. Despite its importance, the fundamental principles underlying this cost remain poorly understood. This…

Statistical Mechanics · Physics 2025-12-29 Abhishek Yadav , David Wolpert

We explore the fundamental limits on thermodynamic irreversibility when cooling a quantum system in the presence of a finite-size reservoir. First, we prove that for any non-interacting $n$-particle reservoir, the entropy production…

Quantum Physics · Physics 2025-12-10 Patryk Lipka-Bartosik , Martí Perarnau-Llobet

We investigate the link between information and thermodynamics embodied by Landauer's principle in the open dynamics of a multipartite quantum system. Such irreversible dynamics is described in terms of a collisional model with a finite…

Quantum Physics · Physics 2015-09-23 S. Lorenzo , R. McCloskey , F. Ciccarello , M. Paternostro , G. M. Palma

Modularity dissipation identifies how locally-implemented computation entails costs beyond those required by Landauer's bound on thermodynamic computing. We establish a general theorem for efficient local computation, giving the necessary…

Quantum Physics · Physics 2020-04-22 Samuel P. Loomis , James P. Crutchfield

Neuromorphic or neurally-inspired optimizers rely on local but parallel parameter updates to solve problems that range from quadratic programming to Ising machines. An ideal realization of such an optimizer not only uses a compute-in-memory…

Machine Learning · Computer Science 2026-03-31 Zihao Chen , Faiek Ahsan , Johannes Leugering , Gert Cauwenberghs , Shantanu Chakrabartty