Rethinking Metadynamics

Authors: Michele Invernizzi1*, Michele Parrinello2*

  1. Department of Physics, ETH Zurich c/o USI Campus, 6900 Lugano, Switzerland
  2. Department of Chemistry and Applied Biosciences, ETH Zurich c/o USI Campus, 6900 Lugano, Switzerland
  • Corresponding authors emails: michele.invernizzi@phys.chem.ethz.ch, michele.parrinello@phys.chem.ethz.ch

DOI10.24435/materialscloud:2019.0063/v1 (version v1, submitted on 22 October 2019)

How to cite this entry

Michele Invernizzi, Michele Parrinello, Rethinking Metadynamics, Materials Cloud Archive (2019), doi: 10.24435/materialscloud:2019.0063/v1.

Description

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. In order to improve its usability and convergence speed, we propose here a change in perspective that shifts the focus form the bias to the probability distribution reconstruction. The result is an enhanced sampling method that combine metadynamics and adaptive umbrella sampling approaches, taking the best from the two worlds. This new method has a straightforward reweighting scheme and allows for efficient importance sampling, avoiding uninteresting high free energy regions. Thanks to a compressed kernel density estimation it can handle a higher dimensional collective variable space, and does not require the prior knowledge of the boundaries of such space. The new method comes in two variants. The first aims at a quick convergence, avoiding oscillations and maximizing the quasi-static bias regime, while in the second the main focus is on a rapid exploration of the free energy landscape. We demonstrate the performance of the method in a number of representative examples.

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Files

File name Size Description
opes.zip
MD5MD5: 2ebe995066a46c5b029826699b023ce8
490.6 KiB all the input files and scripts to reproduce the results in the paper
README.txt
MD5MD5: 38305722d943191a44fa11245bb56863
299 Bytes basic information
figures.zip
MD5MD5: 38d00539729a7fcc0e248657137def2e
41.8 MiB all the data used to produce the figures in the paper

License

Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.

External references

Preprint

Keywords

enhanced sampling free energy umbrella sampling MARVEL/DD1

Version history

22 October 2019 [This version]