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Constructing Tensor Network Influence Functionals for General Quantum Dynamics

Ye, Erika and Chan, Garnet Kin-Lic (2021) Constructing Tensor Network Influence Functionals for General Quantum Dynamics. . (Submitted) https://resolver.caltech.edu/CaltechAUTHORS:20210316-101643523

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Abstract

We describe an iterative formalism to compute influence functionals that describe the general quantum dynamics of a subsystem beyond the assumption of linear coupling to a quadratic bath. We use a space-time tensor network representation of the influence functional and investigate its approximability in terms of the bond dimensions and time-like entanglement in the tensor network description. We study two numerical models, the spin-boson model and a model of interacting hard-core bosons in a 1D harmonic trap. We find that the influence functional and the intermediates involved in its construction can be efficiently approximated by low bond dimension tensor networks in certain dynamical regimes, which allows the quantum dynamics to be accurately computed for longer times than with direct time evolution methods. However, as one iteratively integrates out the bath, the correlations in the influence functional can first increase before decreasing, indicating that the final compressibility of the influence functional is achieved via non-trivial cancellation.


Item Type:Report or Paper (Discussion Paper)
Related URLs:
URLURL TypeDescription
http://arxiv.org/abs/2101.05466arXivDiscussion Paper
ORCID:
AuthorORCID
Chan, Garnet Kin-Lic0000-0001-8009-6038
Additional Information:Attribution 4.0 International (CC BY 4.0). GKC was supported by the Center for Molecular Magnetic Quantum Materials, an Energy Frontier Research Center funded by the U.S. Department of Energy, Office of Science, Basic Energy Sciences under Award No. DESC0019330. EY was primarily supported by the Google PhD fellowship program with supplemental salary support from the Center for Molecular Magnetic Quantum Materials.
Funders:
Funding AgencyGrant Number
Department of Energy (DOE)DE-SC0019330
Google PhD FellowshipUNSPECIFIED
Record Number:CaltechAUTHORS:20210316-101643523
Persistent URL:https://resolver.caltech.edu/CaltechAUTHORS:20210316-101643523
Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:108450
Collection:CaltechAUTHORS
Deposited By: Tony Diaz
Deposited On:19 Mar 2021 00:42
Last Modified:19 Mar 2021 00:42

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