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A computationally simple way to accommodate 'basins' of trapping sites in standard kinetic Monte Carlo simulations is presented. By assuming the system is effectively equilibrated in the basin, the residence time (time spent in the basin…

Statistical Mechanics · Physics 2008-02-12 Clinton DeW. Van Siclen

Sequential Monte Carlo methods, also known as particle methods, are a popular set of techniques for approximating high-dimensional probability distributions and their normalizing constants. These methods have found numerous applications in…

Computation · Statistics 2021-06-23 Jeremy Heng , Adrian N. Bishop , George Deligiannidis , Arnaud Doucet

We estimate the parameter of a stationary time series process by minimizing the integrated weighted mean squared error between the empirical and simulated characteristic function, when the true characteristic functions cannot be explicitly…

Statistics Theory · Mathematics 2021-02-03 Richard A. Davis , Thiago do Rêgo Sousa , Claudia Klüppelberg

We present a new method for simulating Markovian jump processes with time-dependent transitions rates, which avoids the transformation of random numbers by inverting time integrals over the rates. It relies on constructing a sequence of…

Statistical Mechanics · Physics 2015-05-20 Viktor Holubec , Petr Chvosta , Mario Einax , Philipp Maass

Recent developments in multiscale computation allow the solution of ``coarse equations'' for the expected macroscopic behavior of microscopically/stochastically evolving particle distributions without ever obtaining these coarse equations…

Computational Physics · Physics 2007-05-23 Ju Li , Panayotis G. Kevrekidis , C. William Gear , Ioannis G. Kevrekidis

We consider systems of stochastic differential equations with multiple scales and small noise and assume that the coefficients of the equations are ergodic and stationary random fields. Our goal is to construct provably-efficient importance…

Probability · Mathematics 2015-09-29 Konstantinos Spiliopoulos

Machine learning techniques not only offer efficient tools for modelling dynamical systems from data, but can also be employed as frontline investigative instruments for the underlying physics. Nontrivial information about the original…

Data Analysis, Statistics and Probability · Physics 2021-02-24 Francesco Borra , Marco Baldovin

We demonstrate how time-integration of stochastic differential equations (i.e. Brownian dynamics simulations) can be combined with continuum numerical bifurcation analysis techniques to analyze the dynamics of liquid crystalline polymers…

Condensed Matter · Physics 2009-11-07 C. I. Siettos , M. D. Graham , I. G. Kevrekidis

Switching dynamical systems are an expressive model class for the analysis of time-series data. As in many fields within the natural and engineering sciences, the systems under study typically evolve continuously in time, it is natural to…

Machine Learning · Computer Science 2022-05-19 Lukas Köhs , Bastian Alt , Heinz Koeppl

With the guidance offered by nonequilibrium statistical thermodynamics, simulation techniques are elevated from brute-force computer experiments to systematic tools for extracting complete, redundancy-free and consistent coarse grained…

Statistical Mechanics · Physics 2018-03-09 Hans Christian Öttinger

We show how the Equation-Free approach for multi-scale computations can be exploited to systematically study the dynamics of neural interactions on a random regular connected graph under a pairwise representation perspective. Using an…

Computational Engineering, Finance, and Science · Computer Science 2015-05-13 Konstantinos G. Spiliotis , Constantinos I. Siettos

This note is addressed to giving a short introduction to control theory of stochastic systems, governed by stochastic differential equations in both finite and infinite dimensions. We will mainly explain the new phenomenon and difficulties…

Optimization and Control · Mathematics 2016-12-09 Qi Lu , Xu Zhang

We propose a computer-assisted approach to studying the effective continuum behavior of spatially discrete evolution equations. The advantage of the approach is that the "coarse model" (the continuum, effective equation) need not be…

Computational Physics · Physics 2007-05-23 J. Moeller , O. Runborg , P. G. Kevrekidis , K. Lust , I. G. Kevrekidis

The stochastic-gauge representation is a method of mapping the equation of motion for the quantum mechanical density operator onto a set of equivalent stochastic differential equations. One of the stochastic variables is termed the…

Quantum Physics · Physics 2010-11-02 Mark R. Dowling , Matthew J. Davis , Peter D. Drummond , Joel F. Corney

Controlling complex dynamical systems has been a topic of considerable interest in academic circles in recent decades. While existing works have primarily focused on closed-loop control schemes with infinite-time durations, this paper…

Optimization and Control · Mathematics 2025-01-08 Xiaoxiao Peng , Shijie Zhou

A brief review of modeling and simulation methods for a study of polymers at interfaces is provided. When studying truly multiscale problems as provided by realistic polymer systems, coarse graining is practically unavoidable. In this…

Soft Condensed Matter · Physics 2009-10-19 Fathollah Varnik , Kurt Binder

These lecture notes introduce quantum spin systems and several computational methods for studying their ground-state and finite-temperature properties. Symmetry-breaking and critical phenomena are first discussed in the simpler setting of…

Strongly Correlated Electrons · Physics 2015-03-17 Anders W. Sandvik

Recently, global pulsar timing arrays have released results from searching for a nano-Hertz gravitational wave background signal. Although there has not been any definite evidence of the presence of such a signal in residuals of pulsar…

General Relativity and Quantum Cosmology · Physics 2022-10-12 A. Samajdar , G. Shaifullah , A. Sesana , J. Antoniadis , M. Burgay , D. J. Champion , S. Chen , M. Kramer , J. W. McKee , M. B. Mickaliger , E. Van der Wateren

Atomistic simulations provide valuable insights into the physical processes governing material behavior. However, their applicability is fundamentally constrained by the limited time scales accessible to brute-force simulations. This…

Computational Physics · Physics 2026-02-16 Michael Kim , Wei Cai

Monte Carlo sampling methods often suffer from long correlation times. Consequently, these methods must be run for many steps to generate an independent sample. In this paper a method is proposed to overcome this difficulty. The method…

Computation · Statistics 2007-09-13 Jonathan Weare