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Related papers: Deformations of Boltzmann Distributions

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Boltzmann generators approach the sampling problem in many-body physics by combining a normalizing flow and a statistical reweighting method to generate samples in thermodynamic equilibrium. The equilibrium distribution is usually defined…

Statistical Mechanics · Physics 2022-09-07 Manuel Dibak , Leon Klein , Andreas Krämer , Frank Noé

We consider a stochastic process in which independent identically distributed random matrices are multiplied and where the Lyapunov exponent of the product is positive. We continue multiplying the random matrices as long as the norm,…

Statistical Mechanics · Physics 2018-03-14 Michael Wilkinson , John Grant

We present a lattice-based numerical method to describe the non equilibrium behavior of a simple fluid under non-uniform spatial conditions. The evolution equation for the one-particle phase-space distribution function is derived starting…

Statistical Mechanics · Physics 2009-11-13 S. Melchionna , U. Marini Bettolo Marconi

The one-dimensional nonlinear equations for the blood flow motion in distensible vessels are considered using the kinetic approach. It is shown that the Lattice Boltzmann (LB) model for non-ideal gas is asymptotically equivalent to the…

Computational Physics · Physics 2020-02-26 Oleg Ilyin

A linear Boltzmann equation is derived in the Boltzmann-Grad scaling for the deterministic dynamics of many interacting particles with random initial data. We study a Rayleigh gas where a tagged particle is undergoing hard-sphere collisions…

Analysis of PDEs · Mathematics 2017-11-29 Karsten Matthies , George Stone , Florian Theil

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

We suggest a new Hamiltonian lattice approach, using a regularisation motivated by deep inelastic scattering. We discuss the relation between distribution functions and the $F_1$ structure function. We have tested this method by computing…

High Energy Physics - Lattice · Physics 2009-10-28 Helmut Kroger , Norbert Scheu

Motivated by a recent random pipe dream model, we study a family of probability distributions on \(S_n\) arising from Bott--Samelson varieties over finite fields. More precisely, for a word \(R\), we consider the Bott--Samelson map…

Combinatorics · Mathematics 2026-05-26 Jingqi Li , Haorun Yin , Wenbin Yu , Shixuan Zeng

We suggest a Hamiltonian formulation on a momentum lattice using a physically motivated regularization using the Breit-frame which links the maximal parton number to the lattice size. This scheme restricts parton momenta to positive values…

High Energy Physics - Lattice · Physics 2014-11-17 Helmut Kroger , Norbert Scheu

Scalable sampling of molecular states in thermodynamic equilibrium is a long-standing challenge in statistical physics. Boltzmann generators tackle this problem by pairing normalizing flows with importance sampling to obtain uncorrelated…

Machine Learning · Computer Science 2026-01-21 Charlie B. Tan , Avishek Joey Bose , Chen Lin , Leon Klein , Michael M. Bronstein , Alexander Tong

Multiplicative random processes in (not necessaryly equilibrium or steady state) stochastic systems with many degrees of freedom lead to Boltzmann distributions when the dynamics is expressed in terms of the logarithm of the normalized…

adap-org · Physics 2009-10-28 M. Levy , S. Solomon

We define and study the $T\bar{T}$ deformation of a random matrix model, showing a consistent definition requires the inclusion of both the perturbative and non-perturbative solutions to the flow equation. The deformed model is well defined…

High Energy Physics - Theory · Physics 2021-07-02 Felipe Rosso

A numerical experiment of ideal stochastic motion of a particle subject to conservative forces and Gaussian noise reveals that the path probability depends exponentially on action. This distribution implies a fundamental principle…

Statistical Mechanics · Physics 2020-10-16 Qiuping A. Wang , Aziz El Kaabouchi

We study the family of network models derived by requiring the expected properties of a graph ensemble to match a given set of measurements of a real-world network, while maximizing the entropy of the ensemble. Models of this type play the…

Statistical Mechanics · Physics 2009-11-10 Juyong Park , M. E. J. Newman

We introduce a training objective for continuous normalizing flows that can be used in the absence of samples but in the presence of an energy function. Our method relies on either a prescribed or a learnt interpolation $f_t$ of energy…

Machine Learning · Statistics 2023-05-31 Bálint Máté , François Fleuret

The classical Boltzmann equation is an integro-differential equation which describes the time evolution of rarefied gas in terms of a molecular distribution function. For some kinetic problems where it is necessary to add in the Boltzmann…

Algorithms based on normalizing flows are emerging as promising machine learning approaches to sampling complicated probability distributions in a way that can be made asymptotically exact. In the context of lattice field theory,…

The lattice Boltzmann method can be used to simulate flow through porous media with full geometrical resolution. With such a direct numerical simulation, it becomes possible to study fundamental effects which are difficult to assess either…

Computational Engineering, Finance, and Science · Computer Science 2015-08-13 Ehsan Fattahia , Christian Waluga , Barbara Wohlmuth , Ulrich Rüde , Michael Manhart , Rainer Helmig

We study the one component $\Phi^4$ model for four different lattice actions in the Gaussian limit and for the Ising model in the broken phase. Emphasis is put on the euclidean invariance properties of the boson propagator. A measure of the…

High Energy Physics - Lattice · Physics 2010-11-19 C. B. Lang , U. Winkler

The Boltzmann distribution of a protein provides a roadmap to all of its functional states. Normalizing flows are a promising tool for modeling this distribution, but current methods are intractable for typical pharmacological targets; they…

Machine Learning · Computer Science 2024-01-10 Joseph C. Kim , David Bloore , Karan Kapoor , Jun Feng , Ming-Hong Hao , Mengdi Wang