Time dependent variational principle for tree Tensor Networks
Daniel Bauernfeind, Markus Aichhorn
SciPost Phys. 8, 024 (2020) · published 7 February 2020
- doi: 10.21468/SciPostPhys.8.2.024
- Submissions/Reports
-
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.
Cited by 35
![Crossref Cited-by](https://scipost.org/static/scipost/images/citedby.gif)
Authors / Affiliation: mappings to Contributors and Organizations
See all Organizations.- Austrian Science Fund (FWF) (through Organization: Fonds zur Förderung der wissenschaftlichen Forschung / FWF Austrian Science Fund [FWF])