English
Related papers

Related papers: Temperature Steerable Flows and Boltzmann Generato…

200 papers

We introduce a solvable stochastic model inspired by granular gases for driven dissipative systems. We characterize far from equilibrium steady states of such systems through the non-Boltzmann energy distribution and compare different…

Statistical Mechanics · Physics 2007-05-23 Yair Srebro , Dov Levine

Distribution-to-distribution generative models support scientific imaging tasks ranging from modeling cellular perturbation responses to translating medical images across conditions. Trustworthy generation requires reliability, or…

Machine Learning · Computer Science 2026-05-22 Dongxia Wu , Yuhui Zhang , Serena Yeung-Levy , Emma Lundberg , Emily B. Fox

We present a polar coordinate lattice Boltzmann kinetic model for compressible flows. A method to recover the continuum distribution function from the discrete distribution function is indicated. Within the model, a hybrid scheme being…

Soft Condensed Matter · Physics 2018-03-09 Chuandong Lin , Aiguo Xu , Guangcai Zhang , Yingjun Li , Sauro Succi

Quantum computing raises the possibility of solving a variety of problems in physics that are presently intractable. A number of such problems involves the physics of systems in or near thermal equilibrium. There are two main ways to…

Quantum Physics · Physics 2023-08-16 Carter Ball , Thomas D. Cohen

Generative diffusion models have achieved spectacular performance in many areas of machine learning and generative modeling. While the fundamental ideas behind these models come from non-equilibrium physics, variational inference and…

Machine Learning · Statistics 2024-06-21 Luca Ambrogioni

A low density binary mixture of granular gases is considered within the Boltzmann kinetic theory. One component, the intruders, is taken to be dilute with respect to the other, and thermal segregation of the two species is described for a…

Statistical Mechanics · Physics 2013-05-06 J. Javier Brey , Nagi Khalil , James W. Dufty

We consider stochastic thermodynamics as a theory of statistical inference for experimentally observed fluctuating time-series. To that end, we introduce a general framework for quantifying the knowledge about the dynamical state of the…

Statistical Mechanics · Physics 2015-05-19 Bernhard Altaner , Jürgen Vollmer

We develop a thermodynamic framework for modeling innovation adoption and abandonment dynamics using statistical mechanics. Starting from a mathematical model for an adoption distribution that fits empirically obtained date, we construct a…

Physics and Society · Physics 2026-04-21 Guilherme S. Y. Giardini , Carlo R. daCunha

We compute the entropy production engendered in the environment from a single Brownian particle which moves in a mean flow, and show that it corresponds in expectation to classical near-equilibrium entropy production in the surrounding…

Statistical Mechanics · Physics 2014-05-06 Yueheng Lan , Erik Aurell

We examine stochastic processes that are used to model nonequilibrium processes (e.g, pulling RNA or dragging colloids) and so deliberately violate detailed balance. We argue that by combining an information-theoretic measure of…

Statistical Mechanics · Physics 2009-11-13 R. A. Blythe

One considers the motion of a test particle in an homogeneous fluid in equilibrium at temperature $T$, undergoing dissipative collisions with the fluid particles. It is shown that the corresponding linear Boltzmann equation still posseses a…

Statistical Mechanics · Physics 2007-05-23 Ph. A. Martin , J. Piasecki

A stochastic deformation of a thermodynamic symplectic structure is studied. The stochastic deformation procedure is analogous to the deformation of an algebra of observables like deformation quantization, but for an imaginary deformation…

Statistical Mechanics · Physics 2009-01-08 P. O. Kazinski

We describe in detail a recently proposed lattice-Boltzmann model for simulating flows with multiple phases and components. In particular, the focus is on the modeling of one-component fluid systems which obey non-ideal gas equations of…

comp-gas · Physics 2009-10-22 Xiaowen Shan , Hudong Chen

The majority vote model is one of the simplest opinion systems yielding distinct phase transitions and has garnered significant interest in recent years. However, its original formulation is not, in general, thermodynamically consistent,…

Statistical Mechanics · Physics 2023-06-16 Felipe Hawthorne , Mário J. de Oliveira , Pedro E. Harunari , Carlos E. Fiore

We present a novel mechanism for thermalizing a system of particles in equilibrium and nonequilibrium situations, based on specifically modeling energy transfer at the boundaries via a microscopic collision process. We apply our method to…

chao-dyn · Physics 2007-05-23 K. Rateitschak , R. Klages , G. Nicolis

Analyzing and interpreting time-dependent stochastic data requires accurate and robust density estimation. In this paper we extend the concept of normalizing flows to so-called temporal Normalizing Flows (tNFs) to estimate time dependent…

Computational Physics · Physics 2019-12-20 Gert-Jan Both , Remy Kusters

Stochastic thermodynamics provides a framework for describing small systems like colloids or biomolecules driven out of equilibrium but still in contact with a heat bath. Both, a first-law like energy balance involving exchanged heat and…

Statistical Mechanics · Physics 2012-05-21 Udo Seifert

We quantitatively characterize the metastability in a multi-phase lattice Boltzmann model. The structure factor of density fluctuations is theoretically obtained and numerically verified to a high precision, for all simulated wave-vectors…

Statistical Mechanics · Physics 2022-12-20 Matteo Lulli , Luca Biferale , Giacomo Falcucci , Mauro Sbragaglia , Dong Yang , Xiaowen Shan

An unified thermodynamical framework based in the use of a generalized Massieu-Planck thermodynamic potential is proposed and a new formulation of Boltzmann-Gibbs Statistical Mechanics is established. Under this philosophy a generalization…

Mathematical Physics · Physics 2007-05-23 V. Garcia-Morales , J. Pellicer

Diffusion models have shown promising potential for advancing Boltzmann Generators. However, two critical challenges persist: (1) inherent errors in samples due to model imperfections, and (2) the requirement of hundreds of functional…

Machine Learning · Computer Science 2024-09-12 Fengzhe Zhang , Jiajun He , Laurence I. Midgley , Javier Antorán , José Miguel Hernández-Lobato