Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/105839
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dc.contributor.authorHaar, T.-
dc.contributor.authorKamleh, W.-
dc.contributor.authorZanotti, J.-
dc.contributor.authorNakamura, Y.-
dc.date.issued2017-
dc.identifier.citationComputer Physics Communications, 2017; 215:113-127-
dc.identifier.issn0010-4655-
dc.identifier.issn1879-2944-
dc.identifier.urihttp://hdl.handle.net/2440/105839-
dc.description.abstractAbstract not available-
dc.description.statementofresponsibilityTaylor Haar, Waseem Kamleh, James Zanotti, Yoshifumi Nakamura-
dc.language.isoen-
dc.publisherElsevier-
dc.rights© 2017 Elsevier B.V. All rights reserved.-
dc.subjectHybrid Monte Carlo algorithm; multiple time scale integration-
dc.titleApplying polynomial filtering to mass preconditioned Hybrid Monte Carlo-
dc.typeJournal article-
dc.identifier.doi10.1016/j.cpc.2017.02.020-
dc.relation.granthttp://purl.org/au-research/grants/arc/FT100100005-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP120104627-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP140103067-
dc.relation.granthttp://purl.org/au-research/grants/arc/DP150103164-
pubs.publication-statusPublished-
dc.identifier.orcidKamleh, W. [0000-0002-6177-5366]-
dc.identifier.orcidZanotti, J. [0000-0002-3936-1597]-
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