Simulating two- and three-dimensional frustrated quantum systems with string-bond states

Abstract

Simulating frustrated quantum magnets is among the most challenging tasks in computational physics. We apply String-Bond States, a recently introduced ansatz which combines Tensor Networks with Monte Carlo based methods, to the simulation of frustrated quantum systems in both two and three dimensions. We compare our results with existing results for unfrustrated and two-dimensional systems with open boundary conditions, and demonstrate that the method applies equally well to the simulation of frustrated systems with periodic boundaries in both two and three dimensions.

9 pages, 11 figures; v2: accepted version, Journal-Ref added

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• Exploring corner transfer matrices and corner tensors for the classical simulation of quantum lattice systems
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• The spin-1/2 square-lattice J_1-J_2 model: The spin-gap issue
• Gradient optimization of finite projected entangled pair states
• Renormalization group contraction of tensor networks in three dimensions
• Hybrid convolutional neural network and PEPS wave functions for quantum many-particle states
• From Tensor Network Quantum States to Tensorial Recurrent Neural Networks
• Ground-state properties of the spin-1/2 antiferromagnetic Heisenberg model on the triangular lattice: A variational study based on entangled-plaquette states
• Three-dimensional isometric tensor networks
• Condensed Matter Applications of Entanglement Theory
• Gradient optimization of fermionic projected entangled pair states on directed lattices
• Ground-state phase diagram of the spin-1/2 square-lattice J1-J2 model with plaquette structure
• Variational study of a mobile hole in a two dimensional quantum antiferromagnet using entangled-plaquette states
• Efficient neural-network based variational Monte Carlo scheme for direct optimization of excited energy states in frustrated quantum systems
• Monte Carlo simulations of two-dimensional fermion systems with string-bond states
• Replica exchange molecular dynamics optimization of tensor network states for quantum many-body systems
• TNSPackage: A Fortran2003 library designed for tensor network state methods
• Variational Neural and Tensor Network Approximations of Thermal States
• Hybrid between biologically and quantum-inspired many-body states