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Metadynamics: A Unified Framework for Accelerating Rare Events and Sampling Thermodynamics and Kinetics

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Handbook of Materials Modeling

Abstract

Metadynamics is an enhanced sampling algorithm in which the normal evolution of the system is biased by a history-dependent potential constructed as a sum of Gaussians centered along the trajectory followed by a suitably chosen set of collective variables. The sum of Gaussians forces the system to escape from local free energy minima and is used to iteratively build an estimator of the free energy. This original idea has been developed and improved over the years in several variants, which nowadays allow addressing in a unified framework some of the most important tasks of molecular simulations: computing the free energy as a function of the collective variables, accelerating rare events, and estimating unbiased kinetic rate constants. This chapter provides a survey of the many formulations of metadynamics with an emphasis on the underlying theoretical concepts and some hints on the appropriate manner of using this approach for solving complicated real-world problems.

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Authors and Affiliations

  1. SISSA, Trieste, Italy

    Giovanni Bussi & Alessandro Laio

  2. International Centre for Theoretical Physics (ICTP), Trieste, Italy

    Alessandro Laio

  3. Department of Chemistry and Biochemistry and Institute for Physical Science and Technology, University of Maryland, College Park, MD, USA

    Pratyush Tiwary

Authors
  1. Giovanni Bussi
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  2. Alessandro Laio
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  3. Pratyush Tiwary
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Correspondence to Alessandro Laio .

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Editors and Affiliations

  1. Institute of Physics, Swiss Federal Institute of Technology – Lausanne, Lausanne, Switzerland

    Wanda Andreoni

  2. Department of Nuclear Science and Engineering, Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA

    Sidney Yip

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Bussi, G., Laio, A., Tiwary, P. (2020). Metadynamics: A Unified Framework for Accelerating Rare Events and Sampling Thermodynamics and Kinetics. In: Andreoni, W., Yip, S. (eds) Handbook of Materials Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-44677-6_49

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