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Metadynamics is an established sampling method aimed at reconstructing the free-energy surface relative to a set of appropriately chosen collective variables. In standard metadynamics the free-energy surface is filled by the addition of…

Statistical Mechanics · Physics 2012-07-11 Davide Branduardi , Giovanni Bussi , 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

We present a unique derivation of metadynamics. The starting point for the derivation is an on-the-fly reweighting scheme but through an approximation we recover the standard metadynamics and the well-tempered metadynamics in a general form…

Statistical Mechanics · Physics 2011-11-10 Bradley M. Dickson

We propose a formulation of adaptive computation of free energy differences, in the ABF or nonequilibrium metadynamics spirit, using conditional distributions of samples of configurations which evolve in time. This allows to present a truly…

Statistical Mechanics · Physics 2015-06-25 Tony Lelievre , Mathias Rousset , Gabriel Stoltz

The computational study of conformational transitions in RNA and proteins with atomistic molecular dynamics often requires suitable enhanced sampling techniques. We here introduce a novel method where concurrent metadynamics are integrated…

Computational Physics · Physics 2015-09-01 Alejandro Gil-Ley , Giovanni Bussi

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

We present an efficient method for the calculation of free energy landscapes. Our approach involves a history dependent bias potential which is evaluated on a grid. The corresponding free energy landscape is constructed via a histogram…

Computational Physics · Physics 2011-03-03 Jens Smiatek , Andreas Heuer

We propose an adiabatic reweighting algorithm for computing the free energy along an external parameter from adaptive molecular dynamics simulations. The adaptive bias is estimated using Bayes identity and information from all the sampled…

Statistical Mechanics · Physics 2014-04-08 Lingling Cao , Gabriel Stoltz , Tony Lelièvre , Mihai-Cosmin Marinica , Manuel Athènes

Existing adaptive bias techniques, which seek to estimate free energies and physical properties from molecular simulations, are limited by their reliance on fixed kernels or basis sets which hinder their ability to efficiently conform to…

Statistical Mechanics · Physics 2018-04-04 Hythem Sidky , Jonathan K. Whitmer

We propose a proof of convergence of an adaptive method used in molecular dynamics to compute free energy profiles. Mathematically, it amounts to studying the long-time behavior of a stochastic process which satisfies a non-linear…

Analysis of PDEs · Mathematics 2007-06-13 Tony Lelievre , Felix Otto , Mathias Rousset , Gabriel Stoltz

A new approach for efficiently exploring the configuration space and computing the free energy of large atomic and molecular systems is proposed, motivated by an analogy with reinforcement learning. There are two major components in this…

Chemical Physics · Physics 2018-04-18 Linfeng Zhang , Han Wang , Weinan E

The present paper proposes an adaptive biasing potential for the computation of free energy landscapes. It is motivated by statistical learning arguments and unifies the tasks of biasing the molecular dynamics to escape free energy wells…

Mathematical Physics · Physics 2018-03-05 I. Bilionis , P. S. Koutsourelakis

We present a simulation protocol that allows for efficient sampling of the degrees of freedom of a solute in explicit solvent. The protocol involves using a non-equilibrium umbrella sampling method, in this case the recently developed…

Chemical Physics · Physics 2010-03-16 Volodymyr Babin , Celeste Sagui

Estimating the free energy in molecular simulation requires, implicitly or explicitly, counting how many times the system is observed in a finite region. If the simulation is biased by an external potential, the weight of the configurations…

Chemical Physics · Physics 2021-12-22 Matteo Carli , Alessandro Laio

We present convergence results for an adaptive algorithm to compute free energies, namely the adaptive biasing force (ABF) method. The free energy is the effective potential associated to a so-called reaction coordinate (RC). Computing free…

Analysis of PDEs · Mathematics 2010-05-20 Tony Lelievre , Kimiya Minoukadeh

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

We develop an efficient sampling and free energy calculation technique within the adaptive biasing potential (ABP) framework. By mollifying the density of states we obtain an approximate free energy and an adaptive bias potential that is…

Statistical Mechanics · Physics 2010-01-29 Bradley M. Dickson , Frederic Legoll , Tony Lelievre , Gabriel Stoltz , Paul Fleurat-Lessard

We present a differentiable formalism for learning free energies that is capable of capturing arbitrarily complex model dependencies on coarse-grained coordinates and finite-temperature response to variation of general system parameters.…

Computational Physics · Physics 2024-05-31 Blake R. Duschatko , Xiang Fu , Cameron Owen , Yu Xie , Albert Musaelian , Tommi Jaakkola , Boris Kozinsky

A simple, efficient, and accurate method is proposed to map multi-dimensional free energy landscapes. The method combines the temperature-accelerated molecular dynamics (TAMD) proposed in [Maragliano & Vanden-Eijnden, Chem. Phys. Lett. 426,…

Computational Physics · Physics 2009-11-13 Luca Maragliano , Eric Vanden-Eijnden
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