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Webinar #74: Temperature and pressure control using first-order stochastic algorithms 

Abstract

Molecular dynamics (MD) simulations are commonly conducted under constant temperature and/or pressure conditions to closely emulate experimental settings. The corresponding algorithms (i.e., thermostats and barostats) are hence designed to enable the transfer of thermal energy or of mechanical work from an external bath. Over the past decades, various algorithms have been proposed, extending Hamilton's equations through first or second-order, stochastic or deterministic approaches, or combining MD with Monte Carlo methods. In this presentation I will focus on first-order stochastic algorithms for temperature [1] and pressure [2,3] control. Specifically, I will show that these algorithms usually strike a good balance between the possibility of customizing relaxation properties and the ease of choosing control parameters. I will show how the formal connection with Monte Carlo allows to develop robust integrators for which violation of detailed balance can be numerically quantified during production simulations. Practical examples using the GROMACS code will be discussed.

[1] Bussi, Donadio, and Parrinello, J. Chem. Phys. 126, 014101 (2007)

[2] Bernetti and Bussi, J. Chem. Phys. 153, 114107 (2020)

[3] Del Tatto, Raiteri, Bernetti, and Bussi, Appl. Sci. 12, 1139 (2022)

Presenter 

Giovianni Bussi - International School for Advanced Studies (SISSA)

More about the presenter on the Presenters tab.

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