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Spectral functions with the density matrix renormalization group: Krylov-space approach for correction vectors.
Nocera, A; Alvarez, G.
Afiliação
  • Nocera A; Computer Science and Mathematics Division and Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
  • Alvarez G; Computer Science and Mathematics Division and Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, USA.
Phys Rev E ; 94(5-1): 053308, 2016 Nov.
Article em En | MEDLINE | ID: mdl-27967202
Frequency-dependent correlations, such as the spectral function and the dynamical structure factor, help illustrate condensed matter experiments. Within the density matrix renormalization group (DMRG) framework, an accurate method for calculating spectral functions directly in frequency is the correction-vector method. The correction vector can be computed by solving a linear equation or by minimizing a functional. This paper proposes an alternative to calculate the correction vector: to use the Krylov-space approach. This paper then studies the accuracy and performance of the Krylov-space approach, when applied to the Heisenberg, the t-J, and the Hubbard models. The cases studied indicate that the Krylov-space approach can be more accurate and efficient than the conjugate gradient, and that the error of the former integrates best when a Krylov-space decomposition is also used for ground state DMRG.
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Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Phys Rev E Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos
Buscar no Google
Base de dados: MEDLINE Tipo de estudo: Prognostic_studies Idioma: En Revista: Phys Rev E Ano de publicação: 2016 Tipo de documento: Article País de afiliação: Estados Unidos