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Frequency response functions (FRFs) are important for assessing the behavior of stochastic linear dynamic systems. For large systems, their evaluations are time-consuming even for a single simulation. In such cases, uncertainty…

Computation · Statistics 2017-03-23 V. Yaghoubi , S. Marelli , B. Sudret , T. Abrahamsson

We show that the common local Monte Carlo rules used to simulate the motion of driven flux lines in disordered media cannot capture the interplay between elasticity and disorder which lies at the heart of these systems. We therefore discuss…

Disordered Systems and Neural Networks · Physics 2009-11-07 Alberto Rosso , Werner Krauth

An efficient Monte Carlo simulation method for bosonic reaction-diffusion systems which are mainly used in the renormalization group (RG) study is proposed. Using this method, one dimensional bosonic single species annihilation model is…

Statistical Mechanics · Physics 2007-05-23 Su-Chan Park

We develop diffusion-based samplers for target distributions known up to a normalising constant. To this end, we rely on the well-known diffusion path that smoothly interpolates between a simple base distribution and the target, popularised…

Although histogram methods have been extremely effective for analyzing data from Monte Carlo simulations, they do have certain limitations, including the range over which they are valid and the difficulties of combining data from…

Statistical Mechanics · Physics 2015-06-25 Robert H. Swendsen , Jian-Sheng Wang , Shing-Te Li , Brian Diggs , Christopher Genovese , Joseph B. Kadane

The stochastic simulation algorithm (SSA) and the corresponding Monte Carlo (MC) method are among the most common approaches for studying stochastic processes. They rely on knowledge of interevent probability density functions (PDFs) and on…

Computation · Statistics 2024-02-12 S. Rusconi , E. Akhmatskaya , D. Sokolovski , N. Ballard , J. C. de la Cal

We propose a computationally efficient random walk on a convex body which rapidly mixes and closely tracks a time-varying log-concave distribution. We develop general theoretical guarantees on the required number of steps; this number can…

Machine Learning · Statistics 2013-09-25 Hariharan Narayanan , Alexander Rakhlin

This article reviews the basic computational techniques for carrying out multi-scale simulations using statistical methods, with the focus on simulations of epitaxial growth. First, the statistical-physics background behind Monte Carlo…

Materials Science · Physics 2009-04-17 Peter Kratzer

We investigate both ensemble and time-averaged mean-squared displacements of particles in a polydisperse granular system in a homogeneous cooling state. The system contains an arbitrary number of species of different sizes and masses. The…

Soft Condensed Matter · Physics 2024-09-20 Anna S. Bodrova , Alexander I. Osinsky

In recent years efficient algorithms have been developed for the numerical computation of relativistic single-particle path integrals in quantum field theory. Here, we adapt this "worldline Monte Carlo" approach to the standard problem of…

The Monte Carlo method is a powerful tool for performing radiative equilibrium calculations, even in complex geometries. The main drawback of the standard Monte Carlo radiative equilibrium methods is that they require iteration, which makes…

In the present paper we consider the initial data, external force, viscosity coefficients, and heat conductivity coefficient as random data for the compressible Navier--Stokes--Fourier system. The Monte Carlo method, which is frequently…

Numerical Analysis · Mathematics 2023-04-04 Maria Lukacova -- Medvidova , Bangwei She , Yuhuan Yuan

We propose a new Monte Carlo method for efficiently sampling trajectories with fixed initial and final conditions in a system with discrete degrees of freedom. The method can be applied to any stochastic process with local interactions,…

Statistical Mechanics · Physics 2012-03-30 Thierry Mora , Aleksandra M. Walczak , Francesco Zamponi

Suppose X is a multivariate diffusion process that is observed discretely in time. At each observation time, a transformation of the state of the process is observed with noise. The smoothing problem consists of recovering the path of the…

Computation · Statistics 2024-09-04 Marcin Mider , Moritz Schauer , Frank van der Meulen

We study memory based random walk models to understand diffusive motion in crowded heterogeneous environment. The models considered are non-Markovian as the current move of the random walk models is determined by randomly selecting a move…

Statistical Mechanics · Physics 2018-08-01 Sabeeha Hasnain , Upendra Harbola , Pradipta Bandyopadhyay

We present an ``equation-free'' multiscale approach to the simulation of unsteady diffusion in a random medium. The diffusivity of the medium is modeled as a random field with short correlation length, and the governing equations are cast…

Numerical Analysis · Mathematics 2007-05-23 Dongbin Xiu , Ioannis Kevrekidis

A free boundary diffusive logistic model finds application in many different fields from biological invasion to wildfire propagation. However, many of these processes show a random nature and contain uncertainties in the parameters. In this…

Numerical Analysis · Mathematics 2025-01-17 M. -C. Casabán , R. Company , V. N. Egorova , L. Jódar

Charge transport processes in disordered complex media are accompanied by anomalously slow relaxation for which usually a broad distribution of relaxation times is adopted. To account for those properties of the environment, a standard…

Statistical Mechanics · Physics 2009-11-10 Ewa Gudowska-Nowak , Kinga Bochenek , Agnieszka Jurlewicz , Karina Weron

By using the integral method in the muon propagation through water, we calculate the range fluctuation of high and ultra high energy muons. Many authors divide all radiative processes into two parts, namely, the continuous part and…

High Energy Astrophysical Phenomena · Physics 2015-03-17 Y. Okumura , N. Takahashi , A. Misaki

Closed-form stochastic filtering equations can be derived in a general setting where probability distributions are replaced by some specific outer measures. In this article, we study how the principles of the sequential Monte Carlo method…

Methodology · Statistics 2018-05-07 Jeremie Houssineau , Branko Ristic
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