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A novel principle is presented which allows for the proof of bounded weak solutions to a class of physically relevant, strongly coupled parabolic systems exhibiting a formal gradient-flow structure. The main feature of these systems is that…

Analysis of PDEs · Mathematics 2015-06-11 Ansgar Jüngel

We study lithium systems over a range of number of atoms, e.g., atomic anion, dimer, metallic cluster, and body-centered cubic crystal by the diffusion Monte Carlo method. The calculations include both core and valence electrons in order to…

Computational Physics · Physics 2015-07-29 Kevin Rasch , Lubos Mitas

Diffusion-based generative models have achieved promising results recently, but raise an array of open questions in terms of conceptual understanding, theoretical analysis, algorithm improvement and extensions to discrete, structured,…

Machine Learning · Computer Science 2022-09-01 Xingchao Liu , Lemeng Wu , Mao Ye , Qiang Liu

We offer a new proposal for the Monte Carlo treatment of many-fermion systems in continuous space. It is based upon Diffusion Monte Carlo with significant modifications: correlated pairs of random walkers that carry opposite signs;…

Condensed Matter · Physics 2009-10-31 M. H. Kalos , Francesco Pederiva

In this paper we introduce and discuss numerical schemes for the approximation of kinetic equations for flocking behavior with phase transitions that incorporate uncertain quantities. This class of schemes here considered make use of a…

Numerical Analysis · Mathematics 2019-10-31 Jose Antonio Carrillo , Mattia Zanella

We use Monte Carlo techniques to simulate an organized prediction competition between a group of a scientific experts acting under the influence of a ``self-governing'' prediction reward algorithm. Our aim is to illustrate the advantages of…

Social and Information Networks · Computer Science 2023-05-09 J. O. Gonzalez-Hernandez , Jonathan Marino , Ted Rogers , Brandon Velasco

We study the problem of multifidelity uncertainty propagation for computationally expensive models. In particular, we consider the general setting where the high-fidelity and low-fidelity models have a dissimilar parameterization both in…

We propose a novel sequential Monte Carlo (SMC) method for sampling from unnormalized target distributions based on a reverse denoising diffusion process. While recent diffusion-based samplers simulate the reverse diffusion using…

Computation · Statistics 2025-11-06 Luhuan Wu , Yi Han , Christian A. Naesseth , John P. Cunningham

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

Reflected diffusions in polyhedral domains are commonly used as approximate models for stochastic processing networks in heavy traffic. Stationary distributions of such models give useful information on the steady state performance of the…

Probability · Mathematics 2012-05-24 Amarjit Budhiraja , Jiang Chen , Sylvain Rubenthaler

Auto-bidding is widely used in advertising systems, serving a diverse range of advertisers. Generative bidding is increasingly gaining traction due to its strong planning capabilities and generalizability. Unlike traditional reinforcement…

Machine Learning · Computer Science 2025-08-26 Yunshan Peng , Wenzheng Shu , Jiahao Sun , Yanxiang Zeng , Jinan Pang , Wentao Bai , Yunke Bai , Xialong Liu , Peng Jiang

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

Kinetic equations model the position-velocity distribution of particles subject to transport and collision effects. Under a diffusive scaling, these combined effects converge to a diffusion equation for the position density in the limit of…

Numerical Analysis · Mathematics 2023-07-26 Emil Løvbak , Giovanni Samaey

We investigate via Monte Carlo numerical simulations and theoretical considerations the outflux of random walkers moving in an interval bounded by an interface exhibiting channels (pores, doors) which undergo an open/close cycle according…

Mathematical Physics · Physics 2014-01-16 Daniele Andreucci , Dario Bellaveglia , Emilio N. M. Cirillo , Silvia Marconi

We study the numerical solution of nonlinear partially observed optimal stopping problems. The system state is taken to be a multi-dimensional diffusion and drives the drift of the observation process, which is another multi-dimensional…

Optimization and Control · Mathematics 2010-01-20 Mike Ludkovski

An open source software package for simulating thermal neutron propagation in geometry is presented. In this system, neutron propagation can be treated by either the particle transport method or the ray-tracing method. Supported by an…

Computational Physics · Physics 2023-12-05 Zi-Yi Pan , Ni Yang , Ming Tang , Peixun Shen , Xiao-Xiao Cai

Min et al. (2009) presented two complementary techniques that use the diffusion approximation to allow efficient Monte-Carlo radiation transfer in very optically thick regions: a modified random walk and a partial diffusion approximation.…

Instrumentation and Methods for Astrophysics · Physics 2015-05-20 Thomas P. Robitaille

Neutron transport along guides is governed by the Liouville theorem and the technology involved has advanced in recent decades. Computer simulations have proven to be useful tools in the design and conception of neutron guide systems in…

We develop approximate estimation methods for exponential random graph models (ERGMs), whose likelihood is proportional to an intractable normalizing constant. The usual approach approximates this constant with Monte Carlo simulations,…

Methodology · Statistics 2023-01-11 Angelo Mele , Lingjiong Zhu

To conduct Bayesian inference with large data sets, it is often convenient or necessary to distribute the data across multiple machines. We consider a likelihood function expressed as a product of terms, each associated with a subset of the…

Computation · Statistics 2020-04-09 Lewis J. Rendell , Adam M. Johansen , Anthony Lee , Nick Whiteley
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