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Related papers: Resetting Metadynamics

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We present a method for enhanced sampling of molecular dynamics simulations using stochastic resetting. Various phenomena, ranging from crystal nucleation to protein folding, occur on timescales that are unreachable in standard simulations.…

Chemical Physics · Physics 2023-02-09 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

Molecular dynamics simulations are widely used across chemistry, physics, and biology, providing quantitative insight into complex processes with atomic detail. However, their limited timescale of a few microseconds is a significant…

Chemical Physics · Physics 2025-04-10 Ofir Blumer , Barak Hirshberg

We present a procedure for enhanced sampling of molecular dynamics simulations through informed stochastic resetting. Many phenomena, such as protein folding and crystal nucleation, occur over time scales that are inaccessible in standard…

Metadynamics is an enhanced sampling method of great popularity, based on the on-the-fly construction of a bias potential that is function of a selected number of collective variables. We propose here a change in perspective that shifts the…

Computational Physics · Physics 2020-03-24 Michele Invernizzi , Michele Parrinello

Many enhanced sampling techniques rely on the identification of a number of collective variables that describe all the slow modes of the system. By constructing a bias potential in this reduced space one is then able to sample efficiently…

Computational Physics · Physics 2019-03-05 Michele Invernizzi , Michele Parrinello

In this paper we combine two powerful computational techniques, well-tempered metadynamics and time lagged independent component analysis. The aim is to develop a new tool for studying rare events and exploring complex free energy…

Statistical Mechanics · Physics 2017-12-08 James McCarty , Michele Parrinello

Stochastic resetting, the procedure of stopping and re-initializing random processes, has recently emerged as a powerful tool for accelerating processes ranging from queuing systems to molecular simulations. However, its usefulness is…

Statistical Mechanics · Physics 2025-03-18 Tommer D. Keidar , Ofir Blumer , Barak Hirshberg , Shlomi Reuveni

Metadynamics is a commonly used and successful enhanced sampling method. By the introduction of a history dependent bias which depends on a restricted number of collective variables(CVs) it can explore complex free energy surfaces…

Statistical Mechanics · Physics 2013-12-06 Pratyush Tiwary , Michele Parrinello

Infrequent Metadynamics is a popular method to obtain the rates of long timescale processes from accelerated simulations. The inference procedure is based on rescaling the first-passage times of Metadynamics trajectories using a…

Chemical Physics · Physics 2025-03-04 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

Stochastic resetting, where a dynamical process is intermittently returned to a fixed reference state, has emerged as a powerful mechanism for optimizing first-passage properties. Existing theory largely treats static, non-learning…

Machine Learning · Computer Science 2026-03-18 Jello Zhou , Vudtiwat Ngampruetikorn , David J. Schwab

Stochastic resetting is a powerful strategy known to accelerate the first-passage time statistics of stochastic processes. While its effects on Markovian systems are well understood, a general framework for non-Markovian dynamics is still…

Statistical Mechanics · Physics 2025-09-16 Debasish Saha , Rati Sharma

We review a selection of methods for performing enhanced sampling in molecular dynamics simulations. We consider methods based on collective variable biasing and on tempering, and offer both historical and contemporary perspectives. In…

Statistical Mechanics · Physics 2014-01-03 Cameron Abrams , Giovanni Bussi

The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predictions of kinetics are particularly difficult because rates, in…

Chemical Physics · Physics 2018-06-13 Yong Wang , Omar Valsson , Pratyush Tiwary , Michele Parrinello , Kresten Lindorff-Larsen

A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias…

Computational Physics · Physics 2010-10-15 Gareth A. Tribello , Michele Ceriotti , Michele Parrinello

We present an inference scheme of long timescale, non-exponential kinetics from Molecular Dynamics simulations accelerated by stochastic resetting. Standard simulations provide valuable insight into chemical processes but are limited to…

Chemical Physics · Physics 2024-10-15 Ofir Blumer , Shlomi Reuveni , Barak Hirshberg

A popular way to accelerate the sampling of rare events in molecular dynamics simulations is to introduce a potential that increases the fluctuations of selected collective variables. For this strategy to be successful, it is critical to…

Computational Physics · Physics 2021-01-19 Luigi Bonati

Many recently introduced enhanced sampling techniques are based on biasing coarse descriptors (collective variables) of a molecular system on the fly. Sometimes the calculation of such collective variables is expensive and becomes a…

Computational Physics · Physics 2015-09-01 Marco Jacopo Ferrarotti , Sandro Bottaro , Andrea Pérez-Villa , Giovanni Bussi

Atomistic modelling of phase transitions, chemical reactions, or other rare events that involve overcoming high free energy barriers usually entails prohibitively long simulation times. Introducing a bias potential as a function of an…

Computational Physics · Physics 2019-11-06 Federico Giberti , Bingqing Cheng , Gareth Aneurin Tribello , Michele Ceriotti

Molecular dynamics simulates the~movements of atoms. Due to its high cost, many methods have been developed to "push the~simulation forward". One of them, metadynamics, can hasten the~molecular dynamics with the~help of variables describing…

Computational Engineering, Finance, and Science · Computer Science 2018-01-09 Jana Pazúriková , Jaroslav Oľha , Aleš Křenek , Vojtěch Spiwok

Molecular dynamics simulations have become essential in many areas of atomistic modelling from drug discovery to materials science. They provide critical atomic-level insights into key dynamical events experiments cannot easily capture.…

Biological Physics · Physics 2024-06-14 Tiejun Wei , Balint Dudas , Edina Rosta
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