The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
An efficient matrix product operator representation of the quantum chemical Hamiltonian
Open accessAbstract
We describe how to efficiently construct the quantum chemical Hamiltonian operator in matrix product form. We present its implementation as a density matrix renormalization group (DMRG) algorithm for quantum chemical applications. Existing implementations of DMRG for quantum chemistry are based on the traditional formulation of the method, which was developed from the point of view of Hilbert space decimation and attained higher performance compared to straightforward implementations of matrix product based DMRG. The latter variationally optimizes a class of ansatz states known as matrix product states, where operators are correspondingly represented as matrix product operators (MPOs). The MPO construction scheme presented here eliminates the previous performance disadvantages while retaining the additional flexibility provided by a matrix product approach, for example, the specification of expectation values becomes an input parameter. In this way, MPOs for different symmetries — abelian and non-abelian — and different relativistic and non-relativistic models may be solved by an otherwise unmodified program.
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Cites
Density matrix formulation for quantum renormalization groups
White, S. R. (1992) · Physical Review Letters · doi:10.1103/physrevlett.69.2863 · Cited by 7,702
The density-matrix renormalization group in the age of matrix product states
Schollwöck, U. (2011) · Annals of Physics · doi:10.1016/j.aop.2010.09.012 · Cited by 4,818
Entanglement in Quantum Critical Phenomena
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�ber das Paulische �quivalenzverbot
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The Density Matrix Renormalization Group in Quantum Chemistry
Chan, G. K.-L., & Sharma, S. (2011) · Annual Review of Physical Chemistry · doi:10.1146/annurev-physchem-032210-103338 · Cited by 822
Ab initio quantum chemistry using the density matrix renormalization group
White, S. R., & Martin, R. L. (1999) · The Journal of Chemical Physics · doi:10.1063/1.478295 · Cited by 558
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Cited by
Modern quantum chemistry with [Open]Molcas
Aquilante, F., Autschbach, J., Baiardi, A., Battaglia, S., Borin, V. A., Chibotaru, L. F., Conti, I., De Vico, L., Delcey, M., Fdez. Galván, I., et al. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0004835 · Cited by 499
Self-citationSeritan, S., Bannwarth, C., Fales, B. S., Hohenstein, E. G., Isborn, C. M., Kokkila‐Schumacher, S. I. L., Li, X., Liu, F., Luehr, N., Snyder, J. W., et al. (2021) · WIREs Computational Molecular Science · doi:10.1002/wcms.1494 · Cited by 312
Baiardi, A., & Reiher, M. (2020) · The Journal of Chemical Physics · doi:10.1063/1.5129672 · Cited by 306
Self-citationFreitag, L., Knecht, S., Angeli, C., & Reiher, M. (2017) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.6b00778 · Cited by 119
Self-citationT3NS: Three-Legged Tree Tensor Network States
Gunst, K., Verstraete, F., Wouters, S., Legeza, O., & Van Neck, D. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00098 · Cited by 64
“23,24 Equivalently for QC-TTNS, the QC-4 The predicted scaling of CPU time, memory usage, and disk usage are given in Table 1 and compared with DMRG.”
Method
Metadata
- Authors
- Keller, S., Dolfi, M., Troyer, M., & Reiher, M.
- Venue
- The Journal of Chemical Physics
- Publisher
- AIP Publishing
- Published
- 2015-12-28
- Volume
- 143
- Issue
- 24
- Pages
- 244118-244118
- ISSN
- 0021-9606 (ISSN-L)
- 1089-7690
- OpenAlex
- W1828807789
- Cited by
- 182
- References
- 7
- FWCI
- 7.64
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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