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We extend the weighted ensemble (WE) path sampling method to perform rigorous statistical sampling for systems at steady state. The straightforward steady-state implementation of WE is directly practical for simple landscapes, but not when…

Biological Physics · Physics 2015-05-14 Divesh Bhatt , Bin W. Zhang , Daniel M. Zuckerman

We apply the "weighted ensemble" (WE) simulation strategy, previously employed in the context of molecular dynamics simulations, to a series of systems-biology models that range in complexity from one-dimensional to a system with 354…

Molecular Networks · Quantitative Biology 2015-03-11 Rory M. Donovan , Andrew J. Sedgewick , James R. Faeder , Daniel M. Zuckerman

Equilibrium formally can be represented as an ensemble of uncoupled systems undergoing unbiased dynamics in which detailed balance is maintained. Many non-equilibrium processes can be described by suitable subsets of the equilibrium…

We introduce an extension to the Weighted Ensemble (WE) path sampling method to restrict sampling to a one dimensional path through a high dimensional phase space. Our method, which is based on the finite-temperature string method, permits…

Statistical Mechanics · Physics 2013-01-25 Joshua L. Adelman , Michael Grabe

We give a mathematical framework for weighted ensemble (WE) sampling, a binning and resampling technique for efficiently computing probabilities in molecular dynamics. We prove that WE sampling is unbiased in a very general setting that…

Numerical Analysis · Mathematics 2018-10-17 David Aristoff

We present an algorithm for finding the probabilities of rare events in nonequilibrium processes. The algorithm consists of evolving the system with a modified dynamics for which the required event occurs more frequently. By keeping track…

Statistical Mechanics · Physics 2011-04-07 Anupam Kundu , Sanjib Sabhapandit , Abhishek Dhar

We propose parameter optimization techniques for weighted ensemble sampling of Markov chains in the steady-state regime. Weighted ensemble consists of replicas of a Markov chain, each carrying a weight, that are periodically resampled…

Numerical Analysis · Mathematics 2022-04-22 David Aristoff , Daniel M. Zuckerman

Based on multiple simulation trajectories, which started from dispersively selected initial conformations, the weighted ensemble dynamics method is designed to robustly and systematically explore the hierarchical structure of complex…

Statistical Mechanics · Physics 2015-05-14 Linchen Gong , Xin Zhou

The weighted ensemble (WE) simulation strategy provides unbiased sampling of non-equilibrium processes, such as molecular folding or binding, but the extraction of rate constants relies on characterizing steady state behavior.…

Statistical Mechanics · Physics 2020-10-02 Jeremy Copperman , Daniel Zuckerman

An issue for molecular dynamics simulations is that events of interest often involve timescales that are much longer than the simulation time step, which is set by the fastest timescales of the model. Because of this timescale separation,…

Statistical Mechanics · Physics 2024-08-15 John Strahan , Chatipat Lorpaiboon , Jonathan Weare , Aaron R. Dinner

To directly simulate rare events using atomistic molecular dynamics is a significant challenge in computational biophysics. Well-established enhanced-sampling techniques do exist to obtain the thermodynamic functions for such systems. But…

Statistical Mechanics · Physics 2020-07-21 Dhiman Ray , Ioan Andricioaei

The weighted ensemble (WE) method, an enhanced sampling approach based on periodically replicating and pruning trajectories in a set of parallel simulations, has grown increasingly popular for computational biochemistry problems, due in…

Computational Physics · Physics 2023-06-23 D. Aristoff , J. Copperman , G. Simpson , R. J. Webber , D. M. Zuckerman

With the traditional equilibrium molecular simulations, it is usually difficult to efficiently visit the whole conformational space in complex systems, which are separated into some metastable conformational regions by high free energy…

Soft Condensed Matter · Physics 2019-08-17 Cheng Yang , Biao Wan , Shun Xu , Yanting Wang , Xin Zhou

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…

We introduce Ensemble Rejection Sampling, a scheme for exact simulation from the posterior distribution of the latent states of a class of non-linear non-Gaussian state-space models. Ensemble Rejection Sampling relies on a proposal for the…

Computation · Statistics 2020-01-28 George Deligiannidis , Arnaud Doucet , Sylvain Rubenthaler

We present a method for computing parameter sensitivities and response coefficients in Brownian dynamics simulations. The method involves tracking auxiliary variables (Malliavin weights) in addition to the usual particle positions, in an…

Statistical Mechanics · Physics 2012-07-20 Patrick B. Warren , Rosalind J. Allen

The "weighted ensemble" method, introduced by Huber and Kim, [G. A. Huber and S. Kim, Biophys. J. 70, 97 (1996)], is one of a handful of rigorous approaches to path sampling of rare events. Expanding earlier discussions, we show that the…

Computational Physics · Physics 2009-12-21 Bin W. Zhang , Daniel M. Zuckerman , David Jasnow

Estimating rare event kinetics from molecular dynamics simulations is a non-trivial task despite the great advances in enhanced sampling methods. Weighted Ensemble (WE) simulation, a special class of enhanced sampling techniques, offers a…

Soft Condensed Matter · Physics 2025-01-16 Sudipta Mitra , Ranjit Biswas , Suman Chakrabarty

When studying high-dimensional dynamical systems such as macromolecules, quantum systems and polymers, a prime concern is the identification of the most probable states and their stationary probabilities or free energies. Often, these…

Data Analysis, Statistics and Probability · Physics 2013-01-01 Hao Wu , Frank Noé

This paper develops the first class of algorithms that enable unbiased estimation of steady-state expectations for multidimensional reflected Brownian motion. In order to explain our ideas, we first consider the case of compound Poisson…

Probability · Mathematics 2015-10-27 Jose Blanchet , Xinyun Chen
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