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arXiv · 1908.03090

Time Dependent Variational Principle for Tree Tensor Networks

Daniel Bauernfeind·Markus Aichhorn
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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.

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Daniel Bauernfeind, Markus Aichhorn. 2019-08-08. Time Dependent Variational Principle for Tree Tensor Networks. https://doi.org/10.21468/scipostphys.8.2.024

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