By taking inspiration from the backflow transformation for correlated systems, we introduce a tensor network Ansatz which extends the well-established matrix product state representation of a quantum many-body wave function. This structure provides enough resources to ensure that states in dimensions larger than or equal to one obey an area law for entanglement. It can be efficiently manipulated to address the ground-state search problem by means of an optimization scheme which mixes tensor-network and variational Monte Carlo algorithms. We benchmark the Ansatz against spin models both in one and two dimensions, demonstrating high accuracy and precision. We finally employ our approach to study the challenging S = 1/2 two-dimensional (2D) J(1) -J(2) model, that it is with the state-of-the-art methods in 2D.

Matrix product states with backflow correlations / Lami, Guglielmo; Carleo, Giuseppe; Collura, Mario. - In: PHYSICAL REVIEW. B. - ISSN 2469-9950. - 106:8(2022), pp. 1-6. [10.1103/physrevb.106.l081111]

Matrix product states with backflow correlations

Guglielmo Lami;Mario Collura
2022-01-01

Abstract

By taking inspiration from the backflow transformation for correlated systems, we introduce a tensor network Ansatz which extends the well-established matrix product state representation of a quantum many-body wave function. This structure provides enough resources to ensure that states in dimensions larger than or equal to one obey an area law for entanglement. It can be efficiently manipulated to address the ground-state search problem by means of an optimization scheme which mixes tensor-network and variational Monte Carlo algorithms. We benchmark the Ansatz against spin models both in one and two dimensions, demonstrating high accuracy and precision. We finally employ our approach to study the challenging S = 1/2 two-dimensional (2D) J(1) -J(2) model, that it is with the state-of-the-art methods in 2D.
2022
106
8
1
6
L081111
https://arxiv.org/abs/2201.00810
Lami, Guglielmo; Carleo, Giuseppe; Collura, Mario
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11767/136054
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