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dc.contributor.authorSpencer, James Sen
dc.contributor.authorNeufeld, Verenaen
dc.contributor.authorVigor, Will Aen
dc.contributor.authorFranklin, Ruth STen
dc.contributor.authorThom, Alex JWen
dc.date.accessioned2019-10-23T15:45:32Z
dc.date.available2019-10-23T15:45:32Z
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/298050
dc.descriptionThis contains the data for this publications and some scripts needed for analysis, plotting figures and creating some of the results. To follow where most of the results come from, please download HANDE QMC (https://github.com/hande-qmc/hande, 10.5281/zenodo.1158670). For more information, see the README files within the dataset.en
dc.description.sponsorshipThomas Young Centre, TYC-101. Cambridge Philosophical Society. EPSRC. CHESS. This work used the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk) and the UK Research Data Facility (http://www.archer.ac.uk/documentation/rdf-guide), grant e507. This work was performed using resources provided by the Cambridge Service for Data Driven Discovery (CSD3) operated by the University of Cambridge Research Computing Service (www.csd3.cam.ac.uk), provided by Dell EMC and Intel using Tier-2 funding from the Engineering and Physical Sciences Research Council (capital grant EP/P020259/1), and DiRAC funding from the Science and Technology Facilities Council (www.dirac.ac.uk).en
dc.formatExternal code possibly needed in addition to this provided data/scipts: - Download HANDE QMC (https://github.com/hande-qmc/hande, 10.5281/zenodo.1158670) if you want to reproduce QMC results. - Download code from https://github.com/abrandoned/murmur2 for excitor behaviour analysis. - Various python packages are needed as well.en
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rightsAttribution 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/en
dc.subjectCoupled cluster Monte Carloen
dc.subjectMonte Carloen
dc.subjectParallelizationen
dc.subjectElectronic Structureen
dc.titleResearch data and further information supporting "Large Scale Parallelization in Stochastic Coupled Cluster"en
dc.typeDataset
dc.identifier.doi10.17863/CAM.30359
rioxxterms.licenseref.urihttp://creativecommons.org/licenses/by/4.0/en
datacite.contributor.supervisorThom, Alex JW
dcterms.formatPython and other coding scripts, Jupyter notebook file, further text files.en
dc.contributor.orcidNeufeld, Verena [0000-0002-4204-746X]
rioxxterms.typeOtheren
pubs.funder-project-idRoyal Society (uf110161)
pubs.funder-project-idRoyal Society (UF160398)
pubs.funder-project-idEPSRC (1502865)
datacite.issupplementto.doi10.1063/1.5047420en
datacite.issupplementto.urlhttps://www.repository.cam.ac.uk/handle/1810/286737


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International