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• W2913725972 abstract "Tensor-network states (TNS) are a promising but numerically challenging tool for simulating two-dimensional (2D) quantum many-body problems. We introduce an isometric restriction of the TNS ansatz that allows for highly efficient contraction of the network. We consider two concrete applications using this ansatz. First, we show that a matrix-product state representation of a 2D quantum state can be iteratively transformed into an isometric 2D TNS. Second, we introduce a 2D version of the time-evolving block decimation algorithm for approximating of the ground state of a Hamiltonian as an isometric TNS-which we demonstrate for the 2D transverse field Ising model." @default.
• W2913725972 created "2019-02-21" @default.
• W2913725972 creator A5003385467 @default.
• W2913725972 creator A5049927722 @default.
• W2913725972 date "2020-01-24" @default.
• W2913725972 modified "2023-10-03" @default.
• W2913725972 title "Isometric Tensor Network States in Two Dimensions" @default.
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• W2913725972 doi "https://doi.org/10.1103/physrevlett.124.037201" @default.
• W2913725972 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/32031848" @default.
• W2913725972 hasPublicationYear "2020" @default.
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