期刊
PHYSICAL REVIEW B
卷 95, 期 3, 页码 -出版社
AMER PHYSICAL SOC
DOI: 10.1103/PhysRevB.95.035129
关键词
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资金
- ExQM graduate school
- Nanosystems Initiative Munich
- Australian Research Council (ARC) Centre of Excellence for Engineered Quantum Systems [CE110001013]
- ARC Future Fellowships scheme [FT140100625]
- Australian Research Council [FT140100625] Funding Source: Australian Research Council
Matrix product operators (MPOs) are at the heart of the second-generation density matrix renormalization group (DMRG) algorithm formulated in matrix product state language. We first summarize the widely known facts on MPO arithmetic and representations of single-site operators. Second, we introduce three compression methods (rescaled SVD, deparallelization, and delinearization) for MPOs and show that it is possible to construct efficient representations of arbitrary operators using MPO arithmetic and compression. As examples, we construct powers of a short-ranged spin-chain Hamiltonian, a complicated Hamiltonian of a two-dimensional system and, as proof of principle, the long-range four-body Hamiltonian from quantum chemistry.
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