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research article

Gauge Equivariant Neural Networks for Quantum Lattice Gauge Theories

Luo, Di
•
Carleo, Giuseppe  
•
Clark, Bryan K.
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December 30, 2021
Physical Review Letters

Gauge symmetries play a key role in physics appearing in areas such as quantum field theories of the fundamental particles and emergent degrees of freedom in quantum materials. Motivated by the desire to efficiently simulate many-body quantum systems with exact local gauge invariance, gauge equivariant neural-network quantum states are introduced, which exactly satisfy the local Hilbert space constraints necessary for the description of quantum lattice gauge theory with Z(d) gauge group and non-Abelian Kitaev DoG thorn models on different geometries. Focusing on the special case of Z(2) gauge group on a periodically identified square lattice, the equivariant architecture is analytically shown to contain the loop-gas solution as a special case. Gauge equivariant neural-network quantum states are used in combination with variational quantum Monte Carlo to obtain compact descriptions of the ground state wave function for the Z(2) theory away from the exactly solvable limit, and to demonstrate the confining or deconfining phase transition of the Wilson loop order parameter.

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Type
research article
DOI
10.1103/PhysRevLett.127.276402
Web of Science ID

WOS:000754293200008

Author(s)
Luo, Di
Carleo, Giuseppe  
Clark, Bryan K.
Stokes, James
Date Issued

2021-12-30

Publisher

AMER PHYSICAL SOC

Published in
Physical Review Letters
Volume

127

Issue

27

Article Number

276402

Subjects

Physics, Multidisciplinary

•

Physics

•

formulation

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
CQSL  
Available on Infoscience
February 28, 2022
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/185849
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