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The bold diagrammatic Monte Carlo (BDMC) method performs an unbiased sampling of Feynman's diagrammatic series using skeleton diagrams. For lattice models the efficiency of BDMC can be dramatically improved by incorporating dynamic…

Statistical Mechanics · Physics 2015-05-20 L. Pollet , N. V. Prokof'ev , B. V. Svistunov

We propose a mean-field (MF) approximation for the recurrence relation governing the dynamics of $m$ species of particles on a square lattice, and we simultaneously perform Monte Carlo (MC) simulations under identical initial conditions to…

Statistical Mechanics · Physics 2025-06-23 Eduardo Velasco Stock , Roberto da Silva , Sebastian Gonçalves

We analyze diffusion of particles on a two dimensional square lattice. Each lattice site contains an arbitrary number of particles. Interactions affect particles only in the same site, and are macroscopically represented by the excess…

Statistical Mechanics · Physics 2022-08-17 Matías A. Di Muro , Miguel Hoyuelos

The role of turbulent effects for dynamos in the Sun and stars continues to be debated. Mean-field (MF) theory provides a broadly used framework to connect these effects to fundamental magnetohydrodynamics. While inaccessible…

Solar and Stellar Astrophysics · Physics 2021-10-06 Jörn Warnecke , Matthias Rheinhardt , Mariangela Viviani , Frederick Gent , Simo Tuomisto , Maarit J. Käpylä

We study in detail a one-dimensional lattice model of a continuum, conserved field (mass) that is transferred deterministically between neighbouring random sites. The model falls in a wider class of lattice models capturing the joint effect…

Statistical Mechanics · Physics 2023-11-01 Stefano Lepri , Paolo Politi , Arkady Pikovsky

We extend the statistical field-theoretical framework of rough surface contact mechanics to characterize the interfacial gap between an elastic half-space and a randomly rough surface incorporating exponential repulsion. Building upon a…

Soft Condensed Matter · Physics 2026-03-10 Yunong Zhou , Hengxu Song , Zhichao Zhang , Yang Xu

We propose a novel learning framework using neural mean-field (NMF) dynamics for inference and estimation problems on heterogeneous diffusion networks. Our new framework leverages the Mori-Zwanzig formalism to obtain an exact evolution…

Machine Learning · Computer Science 2021-06-07 Shushan He , Hongyuan Zha , Xiaojing Ye

We propose a novel learning framework based on neural mean-field dynamics for inference and estimation problems of diffusion on networks. Our new framework is derived from the Mori-Zwanzig formalism to obtain an exact evolution of the node…

Machine Learning · Computer Science 2021-01-20 Shushan He , Hongyuan Zha , Xiaojing Ye

The Kinetic Monte Carlo (KMC) method has become an important tool for examination of phenomena like surface diffusion and thin film growth because of its ability to carry out simulations for time scales that are relevant to experiments. But…

Materials Science · Physics 2007-05-23 Talat S. Rahman , Abdelkader Kara , Altaf Karim , Oleg Trushin

Dynamical mean-field theory (DMFT) is one of the most widely used theoretical methods for electronic structure calculations, providing self-consistent solutions even in low-temperature regimes, which are exact in the limit of infinite…

Strongly Correlated Electrons · Physics 2023-09-06 Johan Carlström

Can a diffusion model produce its own "mental average" of a concept-one that is as sharp and realistic as a typical sample? We introduce Diffusion Mental Averages (DMA), a model-centric answer to this question. While prior methods aim to…

Computer Vision and Pattern Recognition · Computer Science 2026-04-01 Phonphrm Thawatdamrongkit , Sukit Seripanitkarn , Supasorn Suwajanakorn

The dynamical mean-field theory (DMFT) is a widely applicable approximation scheme for the investigation of correlated quantum many-particle systems on a lattice, e.g., electrons in solids and cold atoms in optical lattices. In particular,…

Strongly Correlated Electrons · Physics 2015-05-30 D. Vollhardt , K. Byczuk , M. Kollar

We investigate the theoretical properties of general diffusion (interpolation) paths and their Langevin Monte Carlo implementation, referred to as diffusion annealed Langevin Monte Carlo (DALMC), under weak conditions on the data…

Machine Learning · Statistics 2025-02-14 Paula Cordero-Encinar , O. Deniz Akyildiz , Andrew B. Duncan

Diffusion is an ubiquitous phenomenon. It is a widespread belief that as long as the area under a current autocorrelation function converges in time, the corresponding spatiotemporal density dynamics should be diffusive. This may be viewed…

Statistical Mechanics · Physics 2025-07-04 Scott D. Linz , Jiaozi Wang , Robin Steinigeweg , Jochen Gemmer

In this work, we aimed to replicate and extend the results presented in the DiffFluid paper[1]. The DiffFluid model showed that diffusion models combined with Transformers are capable of predicting fluid dynamics. It uses a denoising…

Fluid Dynamics · Physics 2025-07-14 Yannick Gachnang , Vismay Churiwala

We present a novel hybrid computational method to simulate accurately dendritic solidification in the low undercooling limit where the dendrite tip radius is one or more orders of magnitude smaller than the characteristic spatial scale of…

Materials Science · Physics 2009-10-31 Mathis Plapp , Alain Karma

The diffusion of a particle in a crowded environment typically proceeds through three regimes: for very short times the particle diffuses freely until it collides with an obstacle for the first time, while for very long times diffusion the…

Biological Physics · Physics 2019-10-09 Nguiya P. Neo , Gary W. Slater

Behavior of the mixture of particles and dimers moving with different jump rates at reconstructed surfaces is described. Collective diffusion coefficient is calculated by the variational approach. Anisotropy of the collective particle…

Statistical Mechanics · Physics 2014-05-12 Marcin Mińkowski , Magdalena A. Załuska Kotur

We develop a new fast-diffusion approximation for the kinetics of deposition of extended objects on a linear substrate, accompanied by diffusional relaxation. This new approximation plays the role of the mean-field theory for such processes…

Condensed Matter · Physics 2010-10-12 Vladimir Privman , Mustansir Barma

Using previous experimental data of diffusion in metallic alloys, we obtain real values for an interpolation parameter introduced in a mean-field theory for diffusion with interaction. Values of order 1 were found as expected, finding…

Chemical Physics · Physics 2020-01-29 Marisel Di Pietro Martínez , Miguel Hoyuelos
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