<?xml version='1.0' encoding='utf-8'?> <oai_dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:oai_dc="http://www.openarchives.org/OAI/2.0/oai_dc/" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"> <dc:creator>Giberti, Federico</dc:creator> <dc:creator>Tribello, Gareth</dc:creator> <dc:creator>Ceriotti, Michele</dc:creator> <dc:date>2021-05-08</dc:date> <dc:description>This repository contains the scripts that were used to run the calculations that present a new biasing technique, the Adaptive Topography of Landscape for Accelerated Sampling (ATLAS). The techinque is implemented in plumed-2.0 and the input file are included in the repository, as well as a few scripts to postprocess the calculations and reproduce the plots presented in the paper</dc:description> <dc:identifier>https://archive.materialscloud.org/record/2021.72</dc:identifier> <dc:identifier>doi:10.24435/materialscloud:py-h3</dc:identifier> <dc:identifier>mcid:2021.72</dc:identifier> <dc:identifier>oai:materialscloud.org:849</dc:identifier> <dc:language>en</dc:language> <dc:publisher>Materials Cloud</dc:publisher> <dc:rights>info:eu-repo/semantics/openAccess</dc:rights> <dc:rights>Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode</dc:rights> <dc:subject>enhanced sampling</dc:subject> <dc:subject>molecular dynamics</dc:subject> <dc:subject>machine learning</dc:subject> <dc:subject>SNSF</dc:subject> <dc:subject>EPFL</dc:subject> <dc:subject>ERC</dc:subject> <dc:title>Global free-energy landscapes as a smoothly joined collection of local maps</dc:title> <dc:type>Dataset</dc:type> </oai_dc:dc>