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Making the Best of a Bad Situation: A Multiscale Approach to Free Energy Calculation
- Michele Invernizzi*Michele Invernizzi*E-mail: [email protected]Department of Physics, ETH Zurich c/o USI Campus, 6900 Lugano, SwitzerlandFacoltà di Informatica, Instituto di Scienze Computationali, and National Center for Computational Design and Discovery of Novel Materials MARVEL, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900 Lugano, SwitzerlandMore by Michele Invernizzi
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- Michele ParrinelloMichele ParrinelloDepartment of Chemistry and Applied Biosciences, ETH Zurich c/o USI Campus, 6900 Lugano, SwitzerlandFacoltà di Informatica, Instituto di Scienze Computationali, and National Center for Computational Design and Discovery of Novel Materials MARVEL, Università della Svizzera Italiana (USI), Via Giuseppe Buffi 13, CH-6900 Lugano, SwitzerlandMore by Michele Parrinello
Abstract
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 and reconstruct the free energy landscape. In methods such as metadynamics, the quality of these collective variables plays a key role in convergence efficiency. Unfortunately in many systems of interest it is not possible to identify an optimal collective variable, and one must deal with the nonideal situation of a system in which some slow modes are not accelerated. We propose a two-step approach in which, by taking into account the residual multiscale nature of the problem, one is able to significantly speed up convergence. To do so, we combine an exploratory metadynamics run with an optimization of the free energy difference between metastable states, based on the recently proposed variationally enhanced sampling method. This new method is well parallelizable and is especially suited for complex systems, because of its simplicity and clear underlying physical picture.
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This article is cited by 16 publications.
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- Michele Invernizzi, Michele Parrinello. Rethinking Metadynamics: From Bias Potentials to Probability Distributions. The Journal of Physical Chemistry Letters 2020, 11 (7) , 2731-2736. https://doi.org/10.1021/acs.jpclett.0c00497
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- Luigi Bonati, Yue-Yu Zhang, Michele Parrinello. Neural networks-based variationally enhanced sampling. Proceedings of the National Academy of Sciences 2019, 116 (36) , 17641-17647. https://doi.org/10.1073/pnas.1907975116