Accurate sampling using Langevin dynamics.

By Giovanni Bussi, Michele Parrinello. 2007

366 citations recorded by the source corpus.

We show how to derive a simple integrator for the Langevin equation and illustrate how it is possible to check the accuracy of the obtained distribution on the fly, using the concept of effective energy introduced in a recent paper [J. Chem. Phys. 126, 014101 (2007)]. Our integrator leads to correct sampling also in the difficult high-friction limit. We also show how these ideas can be applied in practical simulations, using a Lennard-Jones crystal as a paradigmatic case.

Subfields: Atomic and Molecular Physics, and Optics, Materials Chemistry, Molecular Biology

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Atomic and Molecular Physics, and Optics

1. Tim Dockhorn
2. Karsten Kreis
3. Arash Vahdat
4. Charles Matthews
5. Gabriel Stoltz
6. B. Leimkuhler

In Materials Chemistry

1. Tim Dockhorn
2. Charles Matthews
3. Gabriel Stoltz
4. B. Leimkuhler
5. Karsten Kreis
6. Arash Vahdat

In Molecular Biology

1. Tim Dockhorn
2. Arash Vahdat
3. Karsten Kreis
4. Charles Matthews
5. Gabriel Stoltz
6. B. Leimkuhler

Citations in the corpus

• Recent Advances of Continual Learning in Computer Vision: An Overview (2021, neutral): “Hence, they proposed to use an energy-based model [193] together with Langevin dynamic sampling [194] as a regularizer to choose the shared parameters that satisfy the independent assumption of VCL.”
• The computation of averages from equilibrium and nonequilibrium Langevin molecular dynamics (2013, methodology): “…obtained by a splitting strategy, building on studies such as Talay (2002); Bou-Rabee & Owhadi (2010) and clarifying the sampling properties of recently proposed schemes Skeel & Izaguirre (2002); Melchionna (2007); Bussi & Parrinello (2007); Thalmann & Farago (2007); Leimkuhler & Matthews (2013a).”
• i-PI: A Python interface for ab initio path integral molecular dynamics simulations (2014, neutral): “[38, 18].”
• Score-Based Generative Modeling with Critically-Damped Langevin Diffusion (2021, methodology): “Using techniques from molecular dynamics (Bussi & Parrinello, 2007; Tuckerman, 2010; Leimkuhler & Matthews, 2013), we also derive a novel SDE integrator tailored to CLD’s reverse-time synthesis SDE.”