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We present a free energy lattice Boltzmann model capable of simulating fluid systems with an arbitrary number of immiscible components in principle. Our method is strictly reduction consistent, ensuring that absent fluid components do not…

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

The Boltzmann kinetic theory for a model of a confined quasi-two dimensional granular mixture derived previously [Garz\'o, Brito and Soto, Phys. Fluids \textbf{33}, 023310 (2021)] is considered further to analyze two different problems.…

Soft Condensed Matter · Physics 2024-03-07 Vicente Garzó , Ricardo Brito , Rodrigo Soto

Multicanonical ensemble sampling simulations have been performed to calculate the phase diagram of a Lennard-Jones fluid embedded in a fractal random matrix generated through diffusion limited cluster aggregation. The study of the system at…

Statistical Mechanics · Physics 2015-06-25 V. De Grandis , P. Gallo , M. Rovere

Exact mechanisms of thermal conductivity in liquids are not well understood, despite rich research history. A vibrational model of energy transfer in dense simple liquids with soft pairwise interactions seems adequate to partially fill this…

Soft Condensed Matter · Physics 2024-02-06 S. A. Khrapak , A. G. Khrapak

Sampling molecular conformations from the Boltzmann distribution is essential for computational chemistry, but iterative diffusion methods are prohibitively slow. Drifting Models offer one-step generation, yet their equilibrium matches the…

Chemical Physics · Physics 2026-03-09 Pipi Hu

The two-dimensional, periodic Lorentz gas, is the dynamical system corresponding with the free motion of a point particle in a planar system of fixed circular obstacles centered at the vertices of a square lattice in the Euclidian plane.…

Analysis of PDEs · Mathematics 2012-07-26 Emanuele Caglioti , François Golse

Many physical systems are described by probability distributions that evolve in both time and space. Modeling these systems is often challenging to due large state space and analytically intractable or computationally expensive dynamics. To…

Biological Physics · Physics 2019-07-03 Oliver K. Ernst , Tom Bartol , Terrence Sejnowski , Eric Mjolsness

In this paper, a central-moment-based lattice Boltzmann (CLB) method for incompressible thermal flows is proposed. In the method, the incompressible Navier-Stokes equations and the convection-diffusion equation for the temperature field are…

Computational Physics · Physics 2017-12-21 Linlin Fei , K. H. Luo , Chuandong Lin , Qing Li

Focusing on the grand-canonical extension of the ordinary restricted Boltzmann machine, we suggest an energy-based model for feature extraction that uses a layer of hidden units with varying size. By an appropriate choice of the chemical…

Disordered Systems and Neural Networks · Physics 2019-12-13 Orestis Loukas

Whenever invertible generative networks are needed for LHC physics, normalizing flows show excellent performance. In this work, we investigate their performance for fast calorimeter shower simulations with increasing phase space dimension.…

High Energy Physics - Phenomenology · Physics 2025-03-06 Florian Ernst , Luigi Favaro , Claudius Krause , Tilman Plehn , David Shih

We present a lattice-Boltzmann method that can simulate the coupled hydrodynamics and electrostatics equations of motion of a two-phase fluid as a means to model electrowetting phenomena. Our method has the advantage of modelling the…

Fluid Dynamics · Physics 2018-12-17 Élfego Ruiz-Gutiérrez , Rodrigo Ledesma-Aguilar

The crucial problem for better understanding the nature of glass transition and related relaxation phenomena is to find proper interrelations between molecular dynamics and thermodynamics of viscous systems. To gain this aim the recently…

Soft Condensed Matter · Physics 2012-10-17 Andrzej Grzybowski , Kajetan Koperwas , Marian Paluch

We afford an experimentally feasible platform to study Boltzmann negative temperatures. Our proposal takes advantage of well-known techniques of engineering Hamiltonian to achieve steady states with highly controllable population inversion.…

Quantum Physics · Physics 2019-05-22 R. J. de Assis , C. J. Villas-Boas , N. G. de Almeida

A simple and efficient one-dimensional discrete Boltzmann method is developed for compressible flows with tunable specific heat ratios by incorporating extra degrees of freedom. To guarantee Galilean invariance in numerical simulations, a…

Fluid Dynamics · Physics 2026-03-03 Yaofeng Li , Chuandong Lin

Spurious velocities arising from the imperfect offset of the undesired term at the discrete level are frequently observed in numerical simulations of equilibrium multiphase flow systems using the lattice Boltzmann equation (LBE) method. To…

Fluid Dynamics · Physics 2023-11-21 Long Ju , Peiyao Liu , Bicheng Yan , Jin Bao , Shuyu Sun , Zhaoli Guo

The most rigorous physical description of non-equilibrium gas dynamics is rooted in the numerical solution of the Boltzmann equation. Yet, the large number of degrees of freedom and the wide range of both spatial and temporal scales render…

Computational Physics · Physics 2024-10-25 Anthony Chang , Narendra Singh , Marco Panesi

Lattice Boltzmann simulations are used to investigate spinodal decomposition in a two-dimensional binary fluid with equilibrium lamellar and droplet phases. We emphasise the importance of hydrodynamic flow to the phase separation kinetics.…

Soft Condensed Matter · Physics 2009-10-31 G. Gonnella , E. Orlandini , J. M. Yeomans

Traditional stochastic modeling of reactive systems limits the domain of applicability of the associated path thermodynamics to systems involving a single elementary reaction at the origin of each observed change in composition. An…

Statistical Mechanics · Physics 2023-01-18 F. Baras , A. L. Garcia , M. Malek Mansour

We consider the problem of sampling from an unknown distribution for which only a sufficiently large number of training samples are available. Such settings have recently drawn considerable interest in the context of generative modelling…

Machine Learning · Statistics 2024-10-24 Georg A. Gottwald , Fengyi Li , Youssef Marzouk , Sebastian Reich