Recommended by

Indexed by

Iterative unbiasing of quasi-equilibrium sampling

Federico Giberti1*, Bingqing Cheng2*, Gareth Tribello3*, Michele Ceriotti1*

1 Laboratory of Computational Science and Modeling, Institute of Materials, École Polytechnique Fédérale de Lausanne (EPFL), CH-1951 Sion, Valais, Switzerland

2 Trinity College, University of Cambridge, Cambridge CB2 1TQ, United Kingdom

3 Atomistic Simulation Centre, School of Mathematics and Physics, Queen's University Belfast, Belfast, BT14 7EN, United Kingdom

* Corresponding authors emails: federico.giberti@epfl.ch, bc509@cam.ac.uk, g.tribello@qub.ac.uk, michele.ceriotti@epfl.ch
DOI10.24435/materialscloud:2020.0044/v1 [version v1]

Publication date: Apr 27, 2020

How to cite this record

Federico Giberti, Bingqing Cheng, Gareth Tribello, Michele Ceriotti, Iterative unbiasing of quasi-equilibrium sampling, Materials Cloud Archive 2020.0044/v1 (2020), doi: 10.24435/materialscloud:2020.0044/v1.


This repository contains the PLUMED-2 input files required to generate the data used in the ITRE publications. ITRE is a method to reweight Molecular Dynamics trajectory biased with a history-dependent potential (such as Metadynamics), and calculate unbiased thermodynamic observables. Since it uses the trajectory itself as a proxy of a grid, its scaling does not depend on the dimensionality of the space explored. In addition, thanks to its formulation, it is less affected by out-of-equilibrium points that characterize the early stages of a biased calculation and are usually discarded. Thanks to this feature, it can be used to increase the statistics when evaluating a thermodynamic observable from biased calculation.

Materials Cloud sections using this data

No Explore or Discover sections associated with this archive record.


File name Size Description
13.0 MiB The .zip file contains the input files necessary to perform the calculation and the postprocessing described in the paper. There are further discussion in README.md files present in the subdirectory of the .zip file.


Files and data are licensed under the terms of the following license: Creative Commons Attribution 4.0 International.
Metadata, except for email addresses, are licensed under the Creative Commons Attribution Share-Alike 4.0 International license.


Enhanced Sampling Molecular Dynamics Statistical Mechanics EPFL ERC SNSF

Version history:

2020.0044/v1 (version v1) [This version] Apr 27, 2020 DOI10.24435/materialscloud:2020.0044/v1