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We perform a thorough analysis on the choice of estimators for random series path integral methods. In particular, we show that both the thermodynamic (T-method) and the direct (H-method) energy estimators have finite variances and are…

Statistical Mechanics · Physics 2009-11-10 Cristian Predescu , Dubravko Sabo , J. D. Doll , David L. Freeman

The neural dynamics of the nematode C. elegans are experimentally low-dimensional and correspond to discrete behavioral states, where previous modeling work has found neural proxies for some of these states. Experimental results further…

Neurons and Cognition · Quantitative Biology 2015-09-04 James Kunert , Eli Shlizerman , Andrew Walker , J. Nathan Kutz

Metadynamics is a popular enhanced sampling scheme wherein by periodic application of a repulsive bias, one can surmount high free energy barriers and explore complex landscapes. Recently metadynamics was shown to be mathematically well…

Chemical Physics · Physics 2016-01-20 Pratyush Tiwary , James F. Dama , Michele Parrinello

Weighted ensemble (WE) is an enhanced path-sampling method that is conceptually simple, widely applicable, and statistically exact. In a WE simulation, an ensemble of trajectories is periodically pruned or replicated to enhance sampling of…

Particle tracking has several important applications for solute transport studies in aquifer systems. Travel time distribution at observation points, particle coordinates in time and streamlines are some practical results providing…

Distributed, Parallel, and Cluster Computing · Computer Science 2023-02-28 Rodrigo Pérez-Illanes , Daniel Fernàndez-Garcia

The probability distribution describing the state of a Stochastic Reaction Network evolves according to the Chemical Master Equation (CME). It is common to estimated its solution using Monte Carlo methods such as the Stochastic Simulation…

Quantitative Methods · Quantitative Biology 2015-06-18 Benjamin Hepp , Ankit Gupta , Mustafa Khammash

We developed a multiscale approach (MultiSCAAL) that integrates the potential of mean force (PMF) obtained from all-atomistic molecular dynamics simulations with a knowledge-based energy function for coarse-grained molecular simulations in…

Biological Physics · Physics 2010-05-10 Antonios Samiotakis , Dirar Homouz , Margaret S. Cheung

Metastability is a common obstacle to performing long molecular dynamics simulations. Many numerical methods have been proposed to overcome it. One method is parallel replica dynamics, which relies on the rapid convergence of the underlying…

Numerical Analysis · Mathematics 2015-05-20 Andrew Binder , Tony Lelièvre , Gideon Simpson

We propose a rigorous construction of a 1D path collective variable to sample structural phase transformations in condensed matter. The path collective variable is defined in a space spanned by global collective variables that serve as…

Materials Science · Physics 2022-12-09 Jutta Rogal , Elia Schneider , Mark E. Tuckerman

Multiparticle collision dynamics (MPCD) is a relatively new algorithm of fluid flow simulations that has been applied mostly to flows around simple objects. One might ask how it behaves in more complex flows. Therefore, we extend MPCD to…

Computational Physics · Physics 2016-10-31 Maciej Matyka

The universal mathematical form of machine-learning potentials (MLPs) shifts the core of development of interatomic potentials to collecting proper training data. Ideally, the training set should encompass diverse local atomic environments…

Computational Physics · Physics 2021-08-17 Dongsun Yoo , Jisu Jung , Wonseok Jeong , Seungwu Han

Typical biomolecular systems such as cellular membranes, DNA, and protein complexes are highly charged. Thus, efficient and accurate treatment of electrostatic interactions is of great importance in computational modelling of such systems.…

Soft Condensed Matter · Physics 2007-05-23 Michael Patra , Marja T. Hyvonen , Emma Falck , Mohsen Sabouri-Ghomi , Ilpo Vattulainen , Mikko Karttunen

We present a one-way shooting algorithm for transition path sampling that accepts every proposed trajectory, yet samples the correct transition path ensemble for systems with overdamped stochastic dynamics. The method is based on two key…

Computational Physics · Physics 2026-03-10 Magdalena Häupl , Sebastian Falkner , Peter G. Bolhuis , Christoph Dellago , Alessandro Coretti

Accurate prediction of cancer progression remains a challenge due to the high heterogeneity of molecular omics data across patients. While biologically informed models have improved the interpretability of these predictions, a persistent…

Machine Learning · Computer Science 2026-04-21 Koushik Howlader , Md Tauhidul Islam , Wei Le

Stochastic models are often used to help understand the behavior of intracellular biochemical processes. The most common such models are continuous time Markov chains (CTMCs). Parametric sensitivities, which are derivatives of expectations…

Numerical Analysis · Mathematics 2014-11-19 Elizabeth Skubak Wolf , David F. Anderson

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths --- the rare trajectories that transit between the folded and unfolded ensembles --- using only thermodynamic information, such as a…

Biomolecules · Quantitative Biology 2018-08-09 William M. Jacobs , Eugene I. Shakhnovich

Large molecular dynamics simulations (millions of atoms, tens of microseconds, thousands of processors) hit the strong scalability wall: simulation on twice as many processors does not take half the time. Inspired by large N-body space…

Numerical Analysis · Computer Science 2013-10-21 Jana Pazúriková , Luděk Matyska

An exact approach to compute physical properties for general multi-electronic-state (MES) systems in thermal equilibrium is presented. The approach is extended from our recent progress on path integral molecular dynamics (PIMD) [J. Chem.…

Chemical Physics · Physics 2017-11-22 Xinzijian Liu , Jian Liu

The adoption of detailed mechanisms for chemical kinetics often poses two types of severe challenges: First, the number of degrees of freedom is large; and second, the dynamics is characterized by widely disparate time scales. As a result,…

Dynamical Systems · Mathematics 2025-10-01 Eliodoro Chiavazzo , C. William Gear , Carmeline J. Dsilva , Neta Rabin , Ioannis G. Kevrekidis

A method to generate reactive trajectories, namely equilibrium trajectories leaving a metastable state and ending in another one is proposed. The algorithm is based on simulating in parallel many copies of the system, and selecting the…

Statistical Mechanics · Physics 2015-05-19 Frédéric Cérou , Arnaud Guyader , Tony Lelièvre , David Pommier