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dc.date.accessioned2020-01-24T12:58:32Z
dc.date.available2020-01-24T12:58:32Z
dc.date.created2020-01-20T14:10:18Z
dc.date.issued2019
dc.identifier.citationFaulstich, Fabian Maximilian Laestadius, Andre Legeza, Örs Schneider, Reinhold Kvaal, Simen . Analysis of the Tailored Coupled-Cluster Method in Quantum Chemistry. SIAM Journal on Numerical Analysis. 2019, 57(6), 2579-2607
dc.identifier.urihttp://hdl.handle.net/10852/72496
dc.description.abstractn quantum chemistry, one of the most important challenges is the static correlation problem when solving the electronic Schrödinger equation for molecules in the Born--Oppenheimer approximation. In this article, we analyze the tailored coupled-cluster method (TCC), one particular and promising method for treating molecular electronic-structure problems with static correlation. The TCC method combines the single-reference coupled-cluster (CC) approach with an approximate reference calculation in a subspace (complete active space (CAS)) of the considered Hilbert space that covers the static correlation. A one-particle spectral gap assumption is introduced, separating the CAS from the remaining Hilbert space. This replaces the nonexisting or nearly nonexisting gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital usually encountered in standard single-reference quantum chemistry. The analysis covers, in particular, CC methods tailored by tensor-network states (TNS-TCC methods). The problem is formulated in a nonlinear functional analysis framework, and, under certain conditions such as the aforementioned gap, local uniqueness and existence are proved using Zarantonello's lemma. From the Aubin--Nitsche-duality method, a quadratic error bound valid for TNS-TCC methods is derived, e.g., for linear-tensor-network TCC schemes using the density matrix renormalization group method. © 2019, Society for Industrial and Applied Mathematicsen_US
dc.languageEN
dc.titleAnalysis of the Tailored Coupled-Cluster Method in Quantum Chemistryen_US
dc.typeJournal articleen_US
dc.creator.authorFaulstich, Fabian Maximilian
dc.creator.authorLaestadius, Andre
dc.creator.authorLegeza, Örs
dc.creator.authorSchneider, Reinhold
dc.creator.authorKvaal, Simen
cristin.unitcode185,15,12,70
cristin.unitnameHylleraas-senteret
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode2
dc.identifier.cristin1777924
dc.identifier.bibliographiccitationinfo:ofi/fmt:kev:mtx:ctx&ctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.jtitle=SIAM Journal on Numerical Analysis&rft.volume=57&rft.spage=2579&rft.date=2019
dc.identifier.jtitleSIAM Journal on Numerical Analysis
dc.identifier.volume57
dc.identifier.issue6
dc.identifier.startpage2579
dc.identifier.endpage2607
dc.identifier.doihttp://dx.doi.org/10.1137/18M1171436
dc.identifier.urnURN:NBN:no-75597
dc.type.documentTidsskriftartikkelen_US
dc.type.peerreviewedPeer reviewed
dc.source.issn0036-1429
dc.identifier.fulltextFulltext https://www.duo.uio.no/bitstream/handle/10852/72496/1/Faulstich2019.pdf
dc.type.versionPublishedVersion


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