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Conjecture II.3.6 of Spohn in [Spohn '91] and Lecture 7 of Jensen-Yau in [Jensen-Yau '99] ask for a general derivation of universal fluctuations of hydrodynamic limits in large-scale stochastic interacting particle systems. However, the…

Probability · Mathematics 2023-03-21 Kevin Yang

In this paper, we construct a type of interacting particle systems to approximate a class of stochastic different equations whose coefficients depend on the conditional probability distributions of the processes given partial observations.…

Probability · Mathematics 2024-03-27 Kai Du , Yunzhang Li , Yuyang Ye

We introduce a family of implicit probabilistic integrators for initial value problems (IVPs), taking as a starting point the multistep Adams-Moulton method. The implicit construction allows for dynamic feedback from the forthcoming…

Methodology · Statistics 2019-04-19 Onur Teymur , Han Cheng Lie , Tim Sullivan , Ben Calderhead

The direct numerical simulation of particulate systems offers a unique approach to study the dynamics of fluid-solid suspensions by fully resolving the submerged particles and without introducing empirical models. For the lattice Boltzmann…

Computational Engineering, Finance, and Science · Computer Science 2017-06-06 Christoph Rettinger , Ulrich Rüde

Solids facing a plasma are a common situation in many astrophysical systems and laboratory setups. Moreover, many plasma technology applications rely on the control of the plasma-surface interaction. However, presently often a fundamental…

Plasma Physics · Physics 2019-12-20 M Bonitz , A Filinov , J W Abraham , K Balzer , H Kählert , E Pehlke , FX Bronold , M Pamperin , M M Becker , D Loffhagen , H Fehske

Integration against a probability distribution given its unnormalized density is a central task in Bayesian inference and other fields. We introduce new methods for approximating such expectations with a small set of weighted samples --…

Machine Learning · Statistics 2026-05-15 Ayoub Belhadji , Daniel Sharp , Youssef M. Marzouk

Computational modeling and simulation of fluid-structure interactions constitute a fundamental cornerstone for advancing aerospace engineering endeavors. This paper addresses the notion and implementation of the immersed boundary method for…

Computational Physics · Physics 2025-12-24 Longqing Ge , Qingdong Cai , Yonghao Zhang , Tianbai Xiao

Using a new Bayesian method for solving inverse quantum problems, potentials of quantum systems are reconstructed from coordinate measurements in non-stationary states. The approach is based on two basic inputs: 1. a likelihood model,…

Quantum Physics · Physics 2007-05-23 J. C. Lemm

The ab-initio computational treatment of electrochemical systems requires an appropriate treatment of the solid/liquid interfaces. A fully quantum mechanical treatment of the interface is computationally demanding due to the large number of…

We introduce the inverse Kalman filter, which enables exact matrix-vector multiplication between a covariance matrix from a dynamic linear model and any real-valued vector with linear computational cost. We integrate the inverse Kalman…

Methodology · Statistics 2026-01-27 Xinyi Fang , Mengyang Gu

In nuclear fusion and fission, fluctuation and dissipation arise due to the coupling of collective degrees of freedom with internal excitations. Close to the barrier, both quantum, statistical and non-Markovian effects are expected to be…

Nuclear Theory · Physics 2010-04-06 G. Hupin , D. Lacroix

Interaction is so ubiquitous that imaging a world free from it is a difficult fantasy exercise. At the same time, in understanding any complex physical system, our ability of accounting for the mutual interaction of its constituents is…

Quantum Physics · Physics 2015-01-19 Roberto D'Agosta

We calculate the admittance of a two-dimensional quantum point contact (QPC) using a Boltzman-like kinetic equation derived for a partial Wigner distribution function in an effective potential. We show that this approach leads to the known…

Condensed Matter · Physics 2008-02-03 I. E. Aronov , G. P. Berman , D. K. Campbell , S. V. Dudiy

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

Background: An accurate way to incorporate long range Coulomb interaction alongside short-range nuclear interaction has been a challenge for theoretical physicists. Purpose: In this paper, we propose a methodology based on the reference…

Nuclear Theory · Physics 2023-08-23 O. S. K. S. Sastri , Arushi Sharma , Ayushi Awasthi

Boltzmann machines are physics informed generative models with wide applications in machine learning. They can learn the probability distribution from an input dataset and generate new samples accordingly. Applying them back to physics, the…

Computational Physics · Physics 2017-11-20 Lei Wang

Many non-coding RNAs are known to play a role in the cell directly linked to their structure. Structure prediction based on the sole sequence is however a challenging task. On the other hand, thanks to the low cost of sequencing…

Quantitative Methods · Quantitative Biology 2020-05-05 Francesca Cuturello , Guido Tiana , Giovanni Bussi

We review a recently devised Monte Carlo simulation method for the direct study of quasi-stationary properties of stochastic processes with an absorbing state. The method is used to determine the static correlation function and the…

Statistical Mechanics · Physics 2009-11-10 Ronald Dickman , Marcelo Martins de Oliveira

Computing equilibrium states in condensed-matter many-body systems, such as solvated proteins, is a long-standing challenge. Lacking methods for generating statistically independent equilibrium samples in "one shot", vast computational…

Machine Learning · Statistics 2019-07-15 Frank Noé , Simon Olsson , Jonas Köhler , Hao Wu

Any physical theory aims to establish the relationship between physical systems in terms of the interaction between these systems. However, any known approach in the literature to infer this interaction is dependent on the particular…

Quantum Physics · Physics 2024-10-01 Shubhayan Sarkar
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