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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

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

We provide an algorithm based on weighted-ensemble (WE) methods, to accurately sample systems at steady state. Applying our method to different one- and two-dimensional models, we succeed to calculate steady state probabilities of order…

Statistical Mechanics · Physics 2015-06-15 Justus A. Kromer , Lutz Schimansky-Geier , Raul Toral

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…

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 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

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

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

Finding and sampling multiple reaction channels for molecular transitions remains an important challenge in physical chemistry. Here we show that the weighted ensemble (WE) path sampling method can readily sample multiple channels. In a…

Biological Physics · Physics 2009-02-17 Bin W. Zhang , David Jasnow , Daniel M. 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

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

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

The weighted ensemble (WE) method stands out as a widely used segment-based sampling technique renowned for its rigorous treatment of kinetics. The WE framework typically involves initially mapping the configuration space onto a…

Computational Physics · Physics 2024-11-19 Dedi Wang , Pratyush Tiwary

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

Machine learning has emerged as a promising approach to path loss prediction, yet its effectiveness often degrades when measurement data are scarce. To address this limitation, we propose an ensemble-based machine learning framework that…

Signal Processing · Electrical Eng. & Systems 2026-05-26 Ahmed P. Mohamed , Byunghyun Lee , Yaguang Zhang , Christopher R. Anderson , David J. Love , James V. Krogmeier

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 presence of erratic or unstable paths in standard kinetic Monte Carlo simulations significantly undermines the accurate simulation and sampling of transition pathways. While typically reliable methods, such as the Gillespie algorithm,…

Statistical Mechanics · Physics 2024-12-03 Elad Korngut , Ohad Vilk , Michael Assaf

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

We introduce the well-tempered ensemble (WTE) which is the biased ensemble sampled by well-tempered metadynamics when the energy is used as collective variable. WTE can be designed so as to have approximately the same average energy as the…

Statistical Mechanics · Physics 2015-05-14 M. Bonomi , M. Parrinello

We propose a method for efficient simulations in extended ensembles, useful, e.g., for the study of problems with complex energy landscapes and for free energy calculations. The main difficulty in such simulations is the estimation of the a…

Statistical Mechanics · Physics 2012-05-29 Jack Lidmar
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