Number of the records: 1  

Density Matrix Renormalization Group with Dynamical Correlation via Adiabatic Connection

  1. 1.
    0548171 - ÚFCH JH 2022 RIV US eng J - Journal Article
    Beran, Pavel - Matoušek, Mikuláš - Hapka, M. - Pernal, K. - Veis, Libor
    Density Matrix Renormalization Group with Dynamical Correlation via Adiabatic Connection.
    Journal of Chemical Theory and Computation. Roč. 17, č. 12 (2021), s. 7575-7585. ISSN 1549-9618. E-ISSN 1549-9626
    R&D Projects: GA ČR(CZ) GJ18-18940Y
    Grant - others:Ga MŠk(CZ) LM2015070
    Institutional support: RVO:61388955
    Keywords : density matrix renormalization group (DMRG) method * wave function * chemical calculation
    OECD category: Physical chemistry
    Impact factor: 6.578, year: 2021
    Method of publishing: Limited access

    The quantum chemical version of the density matrix renormalization group (DMRG) method has established itself as one of the methods of choice for calculations of strongly correlated molecular systems. Despite its great ability to capture strong electronic correlation in large active spaces, it is not suitable for computations of dynamical electron correlation. In this work, we present a new approach to the electronic structure problem of strongly correlated molecules, in which DMRG is responsible for a proper description of the strong correlation, whereas dynamical correlation is computed via the recently developed adiabatic connection (AC) technique which requires only up to two-body active space reduced density matrices. We report the encouraging results of this approach on typical candidates for DMRG computations, namely, n-acenes (n = 2 → 7), Fe(II)–porphyrin, and the Fe3S4 cluster.
    Permanent Link: http://hdl.handle.net/11104/0324280

     
    FileDownloadSizeCommentaryVersionAccess
    0548171.pdf11.1 MBPublisher’s postprintrequire
    0548171preprint.pdf01 MBAuthor´s preprintopen-access
     
Number of the records: 1  

  This site uses cookies to make them easier to browse. Learn more about how we use cookies.