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A shortcut to the thermodynamic limit for quantum many-body calculations of metals.
Mihm, Tina N; Schäfer, Tobias; Ramadugu, Sai Kumar; Weiler, Laura; Grüneis, Andreas; Shepherd, James J.
Afiliação
  • Mihm TN; Department of Chemistry, University of Iowa, Iowa City, Iowa, USA.
  • Schäfer T; Institute for Theoretical Physics, TU Wien, Vienna, Austria.
  • Ramadugu SK; Department of Chemistry, University of Iowa, Iowa City, Iowa, USA.
  • Weiler L; Department of Chemistry, University of Iowa, Iowa City, Iowa, USA.
  • Grüneis A; Institute for Theoretical Physics, TU Wien, Vienna, Austria.
  • Shepherd JJ; Department of Chemistry, University of Iowa, Iowa City, Iowa, USA. james-shepherd@uiowa.edu.
Nat Comput Sci ; 1(12): 801-808, 2021 Dec.
Article em En | MEDLINE | ID: mdl-38217186
ABSTRACT
Computationally efficient and accurate quantum mechanical approximations to solve the many-electron Schrödinger equation are crucial for computational materials science. Methods such as coupled cluster theory show potential for widespread adoption if computational cost bottlenecks can be removed. For example, extremely dense k-point grids are required to model long-range electronic correlation effects, particularly for metals. Although these grids can be made more effective by averaging calculations over an offset (or twist angle), the resultant cost in time for coupled cluster theory is prohibitive. We show here that a single special twist angle can be found using the transition structure factor, which provides the same benefit as twist averaging with one or two orders of magnitude reduction in computational time. We demonstrate that this not only works for metal systems but also is applicable to a broader range of materials, including insulators and semiconductors.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Comput Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Nat Comput Sci Ano de publicação: 2021 Tipo de documento: Article País de afiliação: Estados Unidos