Learning topological defects formation with neural networks in a quantum phase transition

DOI10.1088/1572-9494/AD3227zbMATH Open1544.81006MaRDI QIDQ6579610

Han-Qing Shi, Hai-Qing Zhang

Publication date: 25 July 2024

Published in: Communications in Theoretical Physics (Search for Journal in Brave)

zbMATH Keywords

neural networksmachine learningKibble-Zurek mechanismtransverse-field quantum Ising model

Mathematics Subject Classification ID

Artificial neural networks and deep learning (68T07) Neural networks for/in biological studies, artificial life and related topics (92B20) Computational methods for problems pertaining to quantum theory (81-08) Many-body theory; quantum Hall effect (81V70)

Cites Work

• The density-matrix renormalization group in the age of matrix product states
• Topological defects as relics of spontaneous symmetry breaking from black hole physics
• Holographic topological defects in a ring: role of diverse boundary conditions
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Quantum Phase Transitions
• Neural-Network Quantum State of Transverse-Field Ising Model
• Topology of cosmic domains and strings
• Solving the quantum many-body problem with artificial neural networks

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