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Related papers: Thermodynamic reduction of contact dynamics

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In traditional thermodynamical and statistical-mechanical approaches one has (some) detailed knowledge of the principles governing the microdynamics of a system. However in many instances we may not have a Hamiltonian or good information…

Statistical Mechanics · Physics 2007-05-23 David Ford

Thermal contact is the archetype of non-equilibrium processes driven by constant non-equilibrium constraints when the latter are enforced by reservoirs exchanging conserved microscopic quantities. At a mesoscopic scale only the energies of…

Statistical Mechanics · Physics 2014-12-30 Michel Bauer , Françoise Cornu

We present a deterministic algorithm called contact density dynamics that generates any prescribed target distribution in the physical phase space. Akin to the famous model of Nos\'e-Hoover, our algorithm is based on a non-Hamiltonian…

Statistical Mechanics · Physics 2016-03-02 A. Bravetti , D. Tapias

An analytical method to compute thermodynamic properties of a given Hamiltonian system is proposed. This method combines ideas of both dynamical systems and ensemble approaches to thermodynamics, providing de facto a possible alternative to…

Statistical Mechanics · Physics 2009-10-31 Xavier Leoncini , Alberto D. Verga

In this work we introduce contact Hamiltonian mechanics, an extension of symplectic Hamiltonian mechanics, and show that it is a natural candidate for a geometric description of non-dissipative and dissipative systems. For this purpose we…

Mathematical Physics · Physics 2017-03-08 Alessandro Bravetti , Hans Cruz , Diego Tapias

A general method for deriving closed reduced models of Hamiltonian dynamical systems is developed using techniques from optimization and statistical estimation. As in standard projection operator methods, a set of resolved variables is…

Mathematical Physics · Physics 2015-10-05 Bruce Turkington

Ability of dynamical systems to relax to equilibrium has been investigated since the invention of statistical mechanics, which establishes the connection between dynamics of many-body Hamiltonian systems and phenomenological thermodynamics.…

Statistical Mechanics · Physics 2019-07-01 K. S. Glavatskiy , V. L. Kulinskii

We obtain macroscopic isothermal thermodynamic transformations by space-time scalings of a microscopic Hamiltonian dynamics in contact with a heat bath. The microscopic dynamics is given by a chain of anharmonic oscillators subject to a…

Statistical Mechanics · Physics 2013-10-03 Stefano Olla

In this article we develop a theory of contact systems with nonholonomic constraints. We obtain the dynamics from Herglotz's variational principle, by restricting the variations so that they satisfy the nonholonomic constraints. We prove…

Mathematical Physics · Physics 2019-11-14 Manuel de León , Víctor Manuel Jiménez , Manuel Lainz Valcázar

We derive the dynamics of several rigid bodies of arbitrary shape in a 2-dimensional inviscid and incompressible fluid, whose vorticity field is given by point vortices. We adopt the idea of Vankerschaver et al. (2009) to derive the…

Fluid Dynamics · Physics 2014-02-27 Steffen Weissmann

Stochastic contact Hamiltonian systems are a class of important mathematical models, which can describe the dissipative properties with odd dimensions in the stochastic environment. In this article, we investigate the numerical dynamics of…

Numerical Analysis · Mathematics 2024-11-19 Qingyi Zhan , Jinqiao Duan , Xiaofan Li , Lijin Wang

For the system with inhomogeneous distribution of macroscopic parameters we obtain thermodynamic relation which depends on the spatial point (coordinate). In our approach, to obtain such a relation we use the basic ideas of the method of…

Statistical Mechanics · Physics 2025-09-24 A. P. Rebesh , B. I. Lev , A. G. Zagorodny

The usual formulation of thermodynamics is based on the additivity of macroscopic systems. However, there are numerous examples of macroscopic systems that are not additive, due to the long-range character of the interaction among the…

Statistical Mechanics · Physics 2022-06-22 Ivan Latella , Agustín Pérez-Madrid , Alessandro Campa , Lapo Casetti , Stefano Ruffo

We present a framework for learning Hamiltonian systems using data. This work is based on a lifting hypothesis, which posits that nonlinear Hamiltonian systems can be written as nonlinear systems with cubic Hamiltonians. By leveraging this,…

Machine Learning · Computer Science 2024-02-09 Süleyman Yildiz , Pawan Goyal , Thomas Bendokat , Peter Benner

In this paper, we propose a discrete Hamilton--Jacobi theory for (discrete) Hamiltonian dynamics defined on a (discrete) contact manifold. To this end, we first provide a novel geometric Hamilton--Jacobi theory for continuous contact…

Mathematical Physics · Physics 2022-09-14 Oğul Esen , Cristina Sardón , Marcin Zajac

Thermodynamic relations are derived from first principles of mechanics for non-equilibrium processes. Since the key role herein is played by the law of increase of entropy, the latter is analyzed at first. It is shown that its derivation…

chao-dyn · Physics 2008-02-03 J. Kumicak , X. de Hemptinne

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

We obtain macroscopic adiabatic thermodynamic transformations by space-time scalings of a microscopic Hamiltonian dynamics subject to random collisions with the environment. The microscopic dynamics is given by a chain of oscillators…

Statistical Mechanics · Physics 2014-12-12 Stefano Olla , Marielle Simon

We consider macroscopic systems in weak contact with boundary reservoirs and under the action of external fields. We present an explicit formula for the Hamiltonian of such systems, from which we deduce the equation of motions, the action…

Probability · Mathematics 2022-11-14 Angèle Bouley , Claudio Landim

We develop a method to learn physical systems from data that employs feedforward neural networks and whose predictions comply with the first and second principles of thermodynamics. The method employs a minimum amount of data by enforcing…

Machine Learning · Computer Science 2020-11-16 Quercus Hernández , Alberto Badias , David Gonzalez , Francisco Chinesta , Elias Cueto
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