English
Related papers

Related papers: Direct Boltzmann inversion method from particle co…

200 papers

Interactions between particles in quantum many-body systems play a crucial role in determining the electric, magnetic, optical, and thermal properties of the system. The recent progress in the laser-pulse technique has enabled the…

Strongly Correlated Electrons · Physics 2021-09-07 Nguyen Thanh Phuc , Pham Quang Trung

We consider a classical system of point particles interacting by means of a short range potential. We prove that, in the low--density (Boltzmann--Grad) limit, the system behaves, for short times, as predicted by the associated Boltzmann…

Mathematical Physics · Physics 2016-11-28 Mario Pulvirenti , Chiara Saffirio , Sergio Simonella

A unified framework to derive discrete time-marching schemes for coupling of immersed solid and elastic objects to the lattice Boltzmann method is presented. Based on operator splitting for the discrete Boltzmann equation, second-order…

Computational Physics · Physics 2017-01-04 Ulf D. Schiller

Studying evolutionary correlations in alignments of homologous sequences by means of an inverse Potts model has proven useful to obtain residue-residue contact energies and to predict contacts in proteins. The quality of the results depend…

Biomolecules · Quantitative Biology 2019-09-04 G. Franco , M. Cagiada , G. Bussi , G. Tiana

This work explores the capability of simulating complex fluid flows by directly solving the Boltzmann equation. Due to the high-dimensionality of the governing equation, the substantial computational cost of solving the Boltzmann equation…

Fluid Dynamics · Physics 2023-12-05 Tarik Dzanic , Luigi Martinelli

The immersed boundary lattice Boltzmann method (IB-LBM) has been widely used in the simulation of fluid-solid interaction and particulate flow problems, since proposed in 2004. However, it is usually a non-trivial task to retain the…

Computational Physics · Physics 2018-03-28 Shi Tao , Qing He , Baiman Chen , Simin Huang

A non-perturbative method is introduced to measure the particle-particle interaction strengths and in-situ confinement for a vertically aligned dust particle pair in a complex plasma. The intrinsic thermal motion of each particle is…

Plasma Physics · Physics 2018-10-17 Ke Qiao , Zhiyue Ding , Jie Kong , Mudi Chen , Lorin S. Matthews , Truell W. Hyde

We introduce a novel mesoscopic computational model based on a multiphase-multicomponent lattice Boltzmann method for the simulation of self-phoretic particles in the presence of liquid-liquid interfaces. Our model features fully resolved…

Soft Condensed Matter · Physics 2022-06-22 Lucas Palacios , Andrea Scagliarini , Ignacio Pagonabarraga

A sufficient condition for entanglement in two-mode continuous systems is constructed based on interference visibility and the uncertainty of the total particle number. The observables to be measured (particle numbers and particle number…

Quantum Physics · Physics 2007-05-23 Geza Toth , Christoph Simon , Juan Ignacio Cirac

We present a method for the evaluation of the interaction potential of an equilibrium classical system starting from the (partial) knowledge of its structure factor. The procedure is divided into two phases both of which are based on the…

Statistical Mechanics · Physics 2012-06-22 Marco D'Alessandro

A Boltzmann machine is a stochastic neural network that has been extensively used in the layers of deep architectures for modern machine learning applications. In this paper, we develop a Boltzmann machine that is capable of modelling…

Statistical Mechanics · Physics 2016-10-18 Giacomo Torlai , Roger G. Melko

One emerging approach for the fabrication of complex architectures on the nanoscale is to utilize particles customized to intrinsically self-assemble into a desired structure. Inverse methods of statistical mechanics have proven…

Materials Science · Physics 2017-09-08 R. B. Jadrich , B. A. Lindquist , T. M. Truskett

The pseudopotential model within the Lattice Boltzmann Method (LBM) framework has emerged as a prominent approach in computational fluid dynamics due to its dual strengths in physical intuitiveness and computational tractability. However,…

Fluid Dynamics · Physics 2025-09-03 Yizhong Chen , Zhibin Wang

Our interest goes to the behavior of a tracer particle, accelerated by a constant and uniform external field, when the energy injected by the field is redistributed through collision to a bath of unaccelerated particles. A non equilibrium…

Soft Condensed Matter · Physics 2013-08-16 Matthieu Barbier , Emmanuel Trizac

Interacting-Particle Reaction Dynamics (iPRD) simulates the spatiotemporal evolution of particles that experience interaction forces and can react with one another. The combination of interaction forces and reactions enable a wide range of…

Chemical Physics · Physics 2018-07-20 Christoph Fröhner , Frank Noé

We investigate and provide optimal sets of reaction coordinates for mixed pairs of molecules displaying polar, uniaxial, or spherical symmetry in two and three dimensions. These coordinates are non-redundant, i.e., they implicitly involve…

Statistical Mechanics · Physics 2017-05-01 Thomas Heinemann , Sabine H. L. Klapp

In [C. Mouhot and L. Pareschi, "Fast algorithms for computing the Boltzmann collision operator," Math. Comp., to appear; C. Mouhot and L. Pareschi, C. R. Math. Acad. Sci. Paris, 339 (2004), pp. 71-76], fast deterministic algorithms based on…

Analysis of PDEs · Mathematics 2016-08-16 Francis Filbet , Clément Mouhot , Lorenzo Pareschi

The pseudopotential multiphase lattice Boltzmann (LB) model is a very popular model in the LB community for simulating multiphase flows. When the multiphase modeling involves a solid boundary, a numerical scheme is required to simulate the…

Computational Physics · Physics 2019-11-27 Q. Li , Y. Yu , Kai H. Luo

We propose a novel approach in the study of transport phenomena in dense systems or systems with long range interactions where multiple particle interactions must be taken into consideration. Within Boltzmann's kinetic formalism, we study…

Classical Physics · Physics 2015-06-26 Travis J. Sherman , Johann Rafelski

We review Boltzmann machines and energy-based models. A Boltzmann machine defines a probability distribution over binary-valued patterns. One can learn parameters of a Boltzmann machine via gradient based approaches in a way that log…

Neural and Evolutionary Computing · Computer Science 2019-01-21 Takayuki Osogami