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For a broad class of input-output maps, arguments based on the coding theorem from algorithmic information theory (AIT) predict that simple (low Kolmogorov complexity) outputs are exponentially more likely to occur upon uniform random…

Data Analysis, Statistics and Probability · Physics 2019-10-03 Kamaludin Dingle , Guillermo Valle Pérez , Ard A. Louis

The paper moves a step towards the full integration of statistical mechanics and information theory. Starting from the assumption that the thermodynamical system is composed by particles whose quantized energies can be modelled as…

Statistical Mechanics · Physics 2023-02-01 Arnaldo Spalvieri

Information dynamics is an emerging description of information processing in complex systems which describes systems in terms of intrinsic computation, identifying computational primitives of information storage and transfer. In this paper…

Statistical Mechanics · Physics 2018-10-03 Richard E. Spinney , Joseph T. Lizier , Mikhail Prokopenko

Statistical mechanics is a powerful framework for analyzing optimization yielding analytical results for matching, optimal transport, and other combinatorial problems. However, these methods typically target the zero-temperature limit,…

Statistical Mechanics · Physics 2026-02-18 Riccardo Piombo , Lorenzo Buffa , Dario Mazzilli , Aurelio Patelli

We investigate fundamental connections between thermodynamics and quantum information theory. First, we show that the operational framework of thermal operations is nonequivalent to the framework of Gibbs-preserving maps, and we comment on…

Quantum Physics · Physics 2016-07-13 Philippe Faist

Integrated information theory (IIT) is a theoretical framework that provides a quantitative measure to estimate when a physical system is conscious, its degree of consciousness, and the complexity of the qualia space that the system is…

Artificial Intelligence · Computer Science 2022-12-12 Eduardo C. Garrido-Merchán , Javier Sánchez-Cañizares

We recently introduced the Alchemical Integral Transform (AIT) enabling the prediction of energy differences, and guessed an Ansatz to parametrize space $\pmb{r}$ in some alchemical change $\lambda$. Here, we present a rigorous derivation…

Chemical Physics · Physics 2024-12-10 Simon León Krug , O. Anatole von Lilienfeld

I give a quick overview of some of the theoretical background necessary for using modern non-equilibrium statistical physics to investigate the thermodynamics of computation. I first present some of the necessary concepts from information…

Statistical Mechanics · Physics 2019-06-20 David H. Wolpert

We extend the Carath\'{e}odory principle of the Second Law to quantum thermodynamics with energy levels depending on macroscopic variables, such as volume and magnetic field. This extension introduces the concept of Quantum Thermodynamic…

Statistical Mechanics · Physics 2025-09-09 Ruo-Xun Zhai , C. P. Sun

We present a relativistic quantum mechanics of a point mass with absolute thermodynamic time and temperature, combined to a single complex parameter of evolution. In this theory, the geometric time is introduced as one of space-time…

High Energy Physics - Theory · Physics 2007-05-23 Vadim V. Asadov , Oleg V. Kechkin

(abridged) In this paper, we present the issues we consider as essential as far as the statistical mechanics of finite systems is concerned. In particular, we emphasis our present understanding of phase transitions in the framework of…

Statistical Mechanics · Physics 2012-02-20 P. Chomaz , F. Gulminelli

Generalized Probabilistic Theories (GPTs) provide a unified framework for describing probabilistic physical theories, encompassing classical and quantum theories as well as hypothetical theories beyond quantum mechanics. Since most GPTs are…

Quantum Physics · Physics 2026-05-14 Koki Ono , Shun Umekawa , Hiroyasu Tajima

The statistical mechanical description of small systems staying in thermal equilibrium with an environment can be achieved by means of the Hamiltonian of mean force. In contrast to the reduced density matrix of an open quantum system, or…

Statistical Mechanics · Physics 2020-10-28 Peter Talkner , Peter Hänggi

One of the primary motivations of the research in the field of computation is to optimize the cost of computation. The major ingredient that a computer needs is the energy to run a process, i.e., the thermodynamic cost. The analysis of the…

Quantum Physics · Physics 2024-08-28 Pritam Chattopadhyay , Goutam Paul

Thermodynamics (in concert with its sister discipline, statistical physics) can be regarded as a data reduction scheme based on partitioning a total system into a subsystem and a bath that weakly interact with each other. The ubiquity and…

Statistical Mechanics · Physics 2009-11-11 David Ford , Steven Huntsman

Operational quantum stochastic thermodynamics is a recently proposed theory to study the thermodynamics of open systems based on the rigorous notion of a quantum stochastic process or quantum causal model. In there, a stochastic trajectory…

Quantum Physics · Physics 2020-03-04 Philipp Strasberg

The development of a self-consistent thermodynamic theory of quantum systems is of fundamental importance for modern physics. Still, despite its essential role in quantum science and technology, there is no unifying formalism for…

Quantum Physics · Physics 2022-11-30 André Malavazi , Frederico Brito

Thermodynamics relies on the possibility to describe systems composed of a large number of constituents in terms of few macroscopic variables. Its foundations are rooted into the paradigm of statistical mechanics, where thermal properties…

Quantum Physics · Physics 2016-10-04 Antonella De Pasquale , Davide Rossini , Rosario Fazio , Vittorio Giovannetti

We introduce a framework designed to analyze the thermodynamics of an abstractly defined logical computer like a deterministic finite automaton (DFA) or a Turing machine, without specifying any extraneous parameters (like rate matrices,…

Statistical Mechanics · Physics 2022-12-29 Gülce Kardeş , David Wolpert

Many Artificial Intelligence (AI) algorithms are inspired by physics and employ stochastic fluctuations. We connect these physics-inspired AI algorithms by unifying them under a single mathematical framework that we call Thermodynamic AI.…

Emerging Technologies · Computer Science 2023-06-14 Patrick J. Coles , Collin Szczepanski , Denis Melanson , Kaelan Donatella , Antonio J. Martinez , Faris Sbahi