Optimization schemes for unitary tensor-network circuit

Abstract

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.

9 pages, 6 figures, sample source codes are available at https://github.com/rezah/unitary-tensor-network-operator

References in corpus (6)

• Matrix Product States, Projected Entangled Pair States, and variational renormalization group methods for quantum spin systems
• Many-body localization edge in the random-field Heisenberg chain
• Continuous Matrix Product States for Quantum Fields
• Real- and imaginary-time evolution with compressed quantum circuits
• Many-body localisation implies that eigenvectors are matrix-product states
• Symmetry fractionalization: Symmetry-protected topological phases of the bond-alternating spin-$1/2$ Heisenberg chain

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