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A new approach to non-extensive thermodynamical systems with non-additive energy and entropy is proposed. The main idea of the paper is based on the statistical matching of the thermodynamical systems with the additive multi-step Markov…

Data Analysis, Statistics and Probability · Physics 2007-05-23 S. S. Apostolov , Z. A. Mayzelis , O. V. Usatenko , V. A. Yampol'skii

A definition of the thermodynamic entropy based on the time-dependent probability distribution of the macroscopic variables is developed. When a constraint in a composite system is released, the probability distribution for the new…

Statistical Mechanics · Physics 2016-11-23 Robert H. Swendsen

Concepts of everyday use like energy, heat, and temperature have acquired a precise meaning after the development of thermodynamics. Thermodynamics provides the basis for understanding how heat and work are related and with the general…

Statistical Mechanics · Physics 2007-05-23 D. Reguera , J. M. Rubi , J. M. G. Vilar

Some analogies between different nonequilibrium heat conduction models, particularly, random walk, discrete variable model, and Boltzmann transport equation with the single relaxation time approximation, have been discussed. We show that…

Statistical Mechanics · Physics 2018-02-21 Sergey Sobolev

We set up a framework for quantum stochastic thermodynamics based solely on experimentally controllable, but otherwise arbitrary interventions at discrete times. Using standard assumptions about the system-bath dynamics and insights from…

Quantum Physics · Physics 2019-08-22 Philipp Strasberg

In this paper the analogy between a thermal engine and a waterwheel is developed in details, showing that the analogous of the flow of water in an hydraulic engine is the flow of entropy in a thermal one. This analogy mat serve to analyse…

General Physics · Physics 2016-11-01 Franco Bagnoli

This paper is a non-technical, informal presentation of our theory of the second law of thermodynamics as a law that is independent of statistical mechanics and that is derivable solely from certain simple assumptions about adiabatic…

Mathematical Physics · Physics 2009-10-31 Elliott H. Lieb , Jakob Yngvason

Several recent results on thermodynamics have been obtained using the tools of quantum information theory and resource theories. So far, the resource theories utilised to describe thermodynamics have assumed the existence of an infinite…

Quantum Physics · Physics 2017-11-16 Carlo Sparaciari , Jonathan Oppenheim , Tobias Fritz

Entropy is a quantity for counting physical degrees of freedom in a system. At a finite temperature, one can use thermal entropy to study thermodynamical properties. At zero temperature, entanglement entropy is expected to provide a…

High Energy Physics - Theory · Physics 2018-10-29 Chen-Te Ma

The maximum entropy principle from statistical mechanics states that a closed system attains an equilibrium distribution that maximizes its entropy. We first show that for graphs with fixed number of edges one can define a stochastic edge…

Disordered Systems and Neural Networks · Physics 2007-05-23 Jesse S. A. Bridgewater , P. Oscar Boykin , Vwani P. Roychowdhury

Thermodynamics provides a unified perspective of thermodynamic properties of various substances. To formulate thermodynamics in the language of sophisticated mathematics, thermodynamics is described by a variety of differential geometries,…

Mathematical Physics · Physics 2023-03-13 Shin-itiro Goto

Transitivity, the existence of periodic points and positive topological entropy can be used to characterize complexity in dynamical systems. It is known that for graphs that are not trees, for every $\varepsilon>0,$ there exist (complicate)…

Dynamical Systems · Mathematics 2018-07-05 Lluís Alsedà , Liane Bordignon , Jorge Groisman

Recently, some of us developed a novel model glass-forming liquid with k extra interactions with pseudo neighbours to each liquid particle over and above the regular interactions with its neighbours. Analysis of the structure and dynamics…

One of the key objectives in investigating small stochastic systems is the development of micrometer-sized engines and the understanding of their thermodynamics. However, the primary mathematical tool used for this purpose, the overdamped…

Statistical Mechanics · Physics 2025-03-31 Shakul Awasthi , Hyunggyu Park , Jae Sung Lee

In the general case of a many-body Hamiltonian system, described by an autonomous Hamiltonian $H$, and with $K\geq 0$ independent conserved quantities, we derive the microcanonical thermodynamics. By a simple approach, based on the…

Statistical Mechanics · Physics 2015-06-04 Roberto Franzosi

This paper presents a method to simulate the thermal behavior of 3D systems using a graph neural network. The method discussed achieves a significant speed-up with respect to a traditional finite-element simulation. The graph neural network…

Computational Engineering, Finance, and Science · Computer Science 2022-09-29 Helios Sanchis-Alepuz , Monika Stipsitz

The physical foundations of a variety of emerging technologies --- ranging from the applications of quantum entanglement in quantum information to the applications of nonequilibrium bulk and interface phenomena in microfluidics, biology,…

Quantum Physics · Physics 2014-03-25 Gian Paolo Beretta , Enzo Zanchini

In recent years, the unified theory of information and thermodynamics has been intensively discussed in the context of stochastic thermodynamics. The unified theory reveals that information theory would be useful to understand…

Statistical Mechanics · Physics 2018-07-23 Sosuke Ito

A set of core features is set forth as the essence of a thermodynamic description, which derive from large-deviation properties in systems with hierarchies of timescales, but which are \emph{not} dependent upon conservation laws or…

Statistical Mechanics · Physics 2020-10-28 Eric Smith

Thermodynamics-informed neural networks employ inductive biases for the enforcement of the first and second principles of thermodynamics. To construct these biases, a metriplectic evolution of the system is assumed. This provides excellent…

Machine Learning · Computer Science 2025-01-22 Alicia Tierz , Iciar Alfaro , David González , Francisco Chinesta , Elías Cueto