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dc.contributor.authorScott, Charles J. C.
dc.contributor.authorDi Remigio, Roberto
dc.contributor.authorCrawford, T. Daniel
dc.contributor.authorThom, Alex J. W.
dc.date.accessioned2019-03-11T14:55:56Z
dc.date.available2019-03-11T14:55:56Z
dc.date.issued2019-02-09
dc.description.abstractWe propose a modified coupled cluster Monte Carlo algorithm that stochastically samples connected terms within the truncated Baker–Campbell–Hausdorff expansion of the similarity-transformed Hamiltonian by construction of coupled cluster diagrams on the fly. Our new approach—diagCCMC—allows propagation to be performed using only the connected components of the similarity-transformed Hamiltonian, greatly reducing the memory cost associated with the stochastic solution of the coupled cluster equations. We show that for perfectly local, noninteracting systems diagCCMC is able to represent the coupled cluster wavefunction with a memory cost that scales linearly with system size. The favorable memory cost is observed with the only assumption of fixed stochastic granularity and is valid for arbitrary levels of coupled cluster theory. Significant reduction in memory cost is also shown to smoothly appear with dissociation of a finite chain of helium atoms. This approach is also shown not to break down in the presence of strong correlation through the example of a stretched nitrogen molecule. Our novel methodology moves the theoretical basis of coupled cluster Monte Carlo closer to deterministic approaches.en_US
dc.description.sponsorshipThe Royal Society ARCHER Leadership Project Grant The U.S. National Science Foundationen_US
dc.descriptionPosted with permission from Scott, C.J.C., Di Remigio, R., Crawford, T.D. & Thom, A.J.W. (2019). Diagrammatic Coupled Cluster Monte Carlo. <i>The Journal of Physical Chemistry Letters, 10</i>925-935. <a href=https://doi.org/10.1021/acs.jpclett.9b00067> https://doi.org/10.1021/acs.jpclett.9b00067</a>. Copyright 2019 American Chemical Society.en_US
dc.identifier.citationScott, C.J.C., Di Remigio, R., Crawford, T.D. & Thom, A.J.W. (2019). Diagrammatic Coupled Cluster Monte Carlo. <i>The Journal of Physical Chemistry Letters, 10</i>, 925-935. https://doi.org/10.1021/acs.jpclett.9b00067en_US
dc.identifier.cristinIDFRIDAID 1677480
dc.identifier.doi10.1021/acs.jpclett.9b00067
dc.identifier.issn1948-7185
dc.identifier.urihttps://hdl.handle.net/10037/14944
dc.language.isoengen_US
dc.publisherAmerican Chemical Societyen_US
dc.relation.journalThe Journal of Physical Chemistry Letters
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/SFF/262695/Norway/Hylleraas Centre for Quantum Molecular Sciences/CAGE/en_US
dc.relation.projectIDinfo:eu-repo/grantAgreement/RCN/FRINATEK/261873/Norway/Stochastic Methods for Molecular Chiroptical Properties//en_US
dc.rights.accessRightsopenAccessen_US
dc.subjectVDP::Mathematics and natural science: 400::Chemistry: 440en_US
dc.subjectVDP::Matematikk og Naturvitenskap: 400::Kjemi: 440en_US
dc.titleDiagrammatic Coupled Cluster Monte Carloen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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