English
Related papers

Related papers: Temperature Steerable Flows and Boltzmann Generato…

200 papers

Generative models based on invertible transformations provide a physics-aware route to sample equilibrium configurations directly from the Boltzmann distribution, enabling efficient exploration of complex thermodynamic landscapes. Here, we…

Statistical Mechanics · Physics 2026-03-06 Luigi de Santis , John Russo , Andrea Ninarello

Boltzmann's principle is used to select the "most probable" realization (macrostate) of an isolated or closed thermodynamic system, containing a small number of particles ($N \llsp \infty$), for both classical and quantum statistics. The…

Statistical Mechanics · Physics 2015-05-13 Robert K. Niven

The nonequilibrium steady state of an infinite-range Ising model is studied. The steady state is obtained by dividing the spins into two groups and attaching them to two heat baths generating spin flips at different temperatures. In the…

Statistical Mechanics · Physics 2011-11-29 Vivien Lecomte , Zoltan Racz , Frederic van Wijland

There is a common view in thermodynamics that the behavior of a macroscopic system can be described by only a few state variables. Although this is true for many cases, it is unclear whether it is meaningful to ask how many state variables…

Statistical Mechanics · Physics 2022-01-05 Koun Shirai

Sampling physical systems with rough energy landscapes is hindered by rare events and metastable trapping. While Boltzmann generators already offer a solution, their reliance on the reverse Kullback--Leibler divergence frequently induces…

Machine Learning · Computer Science 2026-04-08 Guang Lin , Christian Moya , Di Qi , Xuda Ye

The limit of small entropy production is reached in relaxing systems long after preparation, and in stationary driven systems in the limit of small driving power. Surprisingly, for extended systems this limit is not in general the…

Condensed Matter · Physics 2009-10-31 Leticia F. Cugliandolo , Jorge Kurchan

We extend the recently developed non-gaussian thermodynamic formalism \cite{tre98} of a (presumably strongly turbulent) non-Markovian medium to its most general form that allows for the formulation of a consistent thermodynamic theory. All…

Space Physics · Physics 2009-10-31 R. A. Treumann

The Boltzmann distribution describes a single parameter (temperature) family of probability distributions over a state space; at any given temperature, the ratio of probabilities of two states depends on their difference in energy. The same…

Probability · Mathematics 2020-07-01 Simone Cerreia-Vioglio , Fabio Maccheroni , Massimo Marinacci , Aldo Rustichini

Sampling from unnormalized target distributions, e.g.\ Boltzmann distributions $\mu_{\text{target}}(x) \propto \exp(-E(x)/T)$, is fundamental to many scientific applications yet computationally challenging due to complex, high-dimensional…

Machine Learning · Statistics 2026-04-22 Niclas Dern , Lennart Redl , Sebastian Pfister , Marcel Kollovieh , David Lüdke , Stephan Günnemann

Boltzmann machine is a powerful tool for modeling probability distributions that govern the training data. A thermal equilibrium state is typically used for Boltzmann machine learning to obtain a suitable probability distribution. The…

We investigate to what extent one can use a thermodynamic description of turbulent flow as a source of stochastic kinetic energy for three-dimensional self-assembly of magnetically interacting macroscopic particles. We confirm that the…

We find the moment generating function (mgf) of the nonequilibrium work for open systems undergoing a thermal process, ie, when the stochastic dynamics maps thermal states into time dependent thermal states. The mgf is given in terms of a…

Statistical Mechanics · Physics 2020-03-18 Domingos S. P. Salazar

The applicability of stochastic differential equations to thermodynamics is considered and a new form, different from the classical Ito and Stratonovich forms, is introduced. It is shown that the new presentation is more appropriate for the…

Statistical Mechanics · Physics 2015-06-05 R. Tsekov

The discretized equilibrium distributions of the lattice Boltzmann method are presented by using the coefficients of the Lagrange interpolating polynomials that pass through the points related to discrete velocities and using moments of the…

Computational Physics · Physics 2020-11-10 Jae Wan Shim

The stochastic thermodynamics provides a framework for the description of systems that are out of thermodynamic equilibrium. It is based on the assumption that the elementary constituents are acted by random forces that generate a…

Statistical Mechanics · Physics 2020-06-26 Mário J. de Oliveira

Normalizing flows are a class of deep generative models that are especially interesting for modeling probability distributions in physics, where the exact likelihood of flows allows reweighting to known target energy functions and computing…

Machine Learning · Statistics 2023-11-27 Leon Klein , Andreas Krämer , Frank Noé

The present paper reports our attempt to search for a new universal framework in nonequilibrium physics. We propose a thermodynamic formalism that is expected to apply to a large class of nonequilibrium steady states including a heat…

Statistical Mechanics · Physics 2007-05-23 Shin-ichi Sasa , Hal Tasaki

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

We study the single-particle distributions of three-dimensional hard sphere gas described by the Boltzmann equation. We focus on the steady homogeneous isotropic solutions in thermodynamically open conditions, i.e. in the presence of…

Chaotic Dynamics · Physics 2011-10-10 Davide Proment , Sergey Nazarenko , Pietro Asinari , Miguel Onorato

Normalizing flows have recently demonstrated the ability to learn the Boltzmann distribution of the Hubbard model, opening new avenues for generative modeling in condensed matter physics. In this work, we investigate the steps required to…

Strongly Correlated Electrons · Physics 2026-01-27 Janik Kreit , Andrea Bulgarelli , Lena Funcke , Thomas Luu , Dominic Schuh , Simran Singh , Lorenzo Verzichelli