Time dependent variational principle for tree Tensor Networks

Daniel Bauernfeind, Markus Aichhorn

Research output: Contribution to journalArticleResearchpeer-review

Abstract

We present a generalization of the Time Dependent Variational Principle (TDVP) to any finite sized loop-free tensor network. The major advantage of TDVP is that it can be employed as long as a representation of the Hamiltonian in the same tensor network structure that encodes the state is available. Often, such a representation can be found also for long-range terms in the Hamiltonian. As an application we use TDVP for the Fork Tensor Product States tensor network for multi-orbital Anderson impurity models. We demonstrate that TDVP allows to account for off-diagonal hybridizations in the bath which are relevant when spin-orbit coupling effects are important, or when distortions of the crystal lattice are present.
Original languageEnglish
Article number024
Number of pages21
JournalSciPost Physics
Volume8
Issue number2
DOIs
Publication statusPublished - 7 Feb 2020

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Fields of Expertise

  • Advanced Materials Science

Treatment code (Nähere Zuordnung)

  • Basic - Fundamental (Grundlagenforschung)
  • Theoretical

Cooperations

  • NAWI Graz

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