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Symmetry-protected tensor networks
Symmetry-protected tensor networks
The simulation and numerical study of large, strongly correlated quantum systems containing Fermions or using real-time evolution in finite dimensions is still an essentially unsolved problem, primarily due to the exponential growth of the Hilbert state space with system size and the occurrence of the so-called sign problem in Monte Carlo studies. In this area, the use of tensor-network methods, for one-dimensional systems chief among them the density matrix renormalisation group (DMRG) and matrix-product states (MPS), has grown in importance in recent years. This thesis first recapitulates the use of non-abelian symmetries such as SU(2)-Spin in arbitrary tensor networks with an extensive review of the published literature including detailed algorithms and implementation hints. Implementing such symmetries can lead to a considerably more efficient representation of states in the tensor network. This part is intended to be suitable as an implementation-oriented introduction to tensor networks in general and the implementation of non-abelian symmetries in particular. Second, it introduces a series of technical improvements for the MPS methods. These improvements include a faster convergence scheme for MPS-DMRG, a systematic approach to the construction of matrix-product operators and an improved Krylov time evolution method as well as the combination of several well-known techniques into a single tensor network toolkit, SYTEN. The effectiveness of these improvements is demonstrated in numerical examples. Third, the toolkit is applied to the study of two models of current research interest: A one-dimensional spin chain in a staggered external magnetic field is studied and confinement of the elementary spinon excitations, as predicted by analytical arguments, found numerically using real-time evolution and evaluation of the dynamical structure factor. Additionally, the Hubbard model in two dimensions is studied extensively at various system sizes, geometries, interaction strengths U and filling factors n using up to 30'000 SU(2)-Spin-symmetric states equivalent to approx. 100'000 states in other MPS-DMRG implementations. Hints of a possible phase coexistence in the region 0.85 < n < 0.95 are found at intermediate interaction strengths U = 4 and U = 6 as well as a consistently striped ground state in the region n ≈ 0.875.
tensor networks, density matrix renormalization group, non-abelian symmetries, matrix-product states
Hubig, Claudius
2017
Englisch
Universitätsbibliothek der Ludwig-Maximilians-Universität München
Hubig, Claudius (2017): Symmetry-protected tensor networks. Dissertation, LMU München: Fakultät für Physik
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Abstract

The simulation and numerical study of large, strongly correlated quantum systems containing Fermions or using real-time evolution in finite dimensions is still an essentially unsolved problem, primarily due to the exponential growth of the Hilbert state space with system size and the occurrence of the so-called sign problem in Monte Carlo studies. In this area, the use of tensor-network methods, for one-dimensional systems chief among them the density matrix renormalisation group (DMRG) and matrix-product states (MPS), has grown in importance in recent years. This thesis first recapitulates the use of non-abelian symmetries such as SU(2)-Spin in arbitrary tensor networks with an extensive review of the published literature including detailed algorithms and implementation hints. Implementing such symmetries can lead to a considerably more efficient representation of states in the tensor network. This part is intended to be suitable as an implementation-oriented introduction to tensor networks in general and the implementation of non-abelian symmetries in particular. Second, it introduces a series of technical improvements for the MPS methods. These improvements include a faster convergence scheme for MPS-DMRG, a systematic approach to the construction of matrix-product operators and an improved Krylov time evolution method as well as the combination of several well-known techniques into a single tensor network toolkit, SYTEN. The effectiveness of these improvements is demonstrated in numerical examples. Third, the toolkit is applied to the study of two models of current research interest: A one-dimensional spin chain in a staggered external magnetic field is studied and confinement of the elementary spinon excitations, as predicted by analytical arguments, found numerically using real-time evolution and evaluation of the dynamical structure factor. Additionally, the Hubbard model in two dimensions is studied extensively at various system sizes, geometries, interaction strengths U and filling factors n using up to 30'000 SU(2)-Spin-symmetric states equivalent to approx. 100'000 states in other MPS-DMRG implementations. Hints of a possible phase coexistence in the region 0.85 < n < 0.95 are found at intermediate interaction strengths U = 4 and U = 6 as well as a consistently striped ground state in the region n ≈ 0.875.