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Optimization schemes for unitary tensor-network circuit

Haghshenas, Reza (2020) Optimization schemes for unitary tensor-network circuit. . (Unpublished)

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We discuss the variational optimization of a unitary tensor-network circuit with different network structures. The ansatz is performed based on a generalization of well-developed multi-scale entanglement renormalization algorithm and also the conjugate-gradient method with an effective line search. We present the benchmarking calculations for different network structures by studying the Heisenberg model in a strongly disordered magnetic field and a tensor-network QR-decomposition.

Item Type:Report or Paper (Discussion Paper)
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URLURL TypeDescription Paper
Haghshenas, Reza0000-0002-5593-8915
Additional Information:This work was supported by the US National Science Foundation (NSF) via grant CHE-1665333. We have used library Uni10 to perform tensor-network ansatz. We thank F. Pollmann for the initial ideas of this work and also thank D. N. Sheng, A. Langari, A. T. Rezakhani and G. K. Chan for helpful discussions. We appreciate F. Pollmann and P. Helms for useful comments and reading the manuscript.
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Record Number:CaltechAUTHORS:20200928-121032434
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:105583
Deposited By: Tony Diaz
Deposited On:28 Sep 2020 19:46
Last Modified:28 Sep 2020 19:46

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