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The density matrix renormalization group in quantum chemistry.

Abstract

The density matrix renormalization group is a method that is useful for describing molecules that have strongly correlated electrons. Here we provide a pedagogical overview of the basic challenges of strong correlation, how the density matrix renormalization group works, a survey of its existing applications to molecular problems, and some thoughts on the future of the method.

Year: 2011 PMID： 21219144 DOI： 10.1146/annurev-physchem-032210-103338

Source DB: PubMed Journal: Annu Rev Phys Chem ISSN： 0066-426X Impact factor: 12.703

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Cited

25 in total

1. Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems.

Authors: Xiaoyao Ma; Randall W Hall; Frank Löffler; Karol Kowalski; Kiran Bhaskaran-Nair; Mark Jarrell; Juana Moreno
Journal: J Chem Phys Date: 2016-01-07 Impact factor: 3.488

2. Perspective: Quantum mechanical methods in biochemistry and biophysics.

Authors: Qiang Cui
Journal: J Chem Phys Date: 2016-10-14 Impact factor: 3.488

3. Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

Authors: Konstantinos D Vogiatzis; Mikhail V Polynski; Justin K Kirkland; Jacob Townsend; Ali Hashemi; Chong Liu; Evgeny A Pidko
Journal: Chem Rev Date: 2018-10-30 Impact factor: 60.622

Review 4. Mono- and binuclear non-heme iron chemistry from a theoretical perspective.

Authors: Tibor András Rokob; Jakub Chalupský; Daniel Bím; Prokopis C Andrikopoulos; Martin Srnec; Lubomír Rulíšek
Journal: J Biol Inorg Chem Date: 2016-05-26 Impact factor: 3.358

5. Electronic landscape of the P-cluster of nitrogenase as revealed through many-electron quantum wavefunction simulations.

Authors: Zhendong Li; Sheng Guo; Qiming Sun; Garnet Kin-Lic Chan
Journal: Nat Chem Date: 2019-09-30 Impact factor: 24.427

The density matrix renormalization group in quantum chemistry.

1. Sign Learning Kink-based (SiLK) Quantum Monte Carlo for molecular systems.

2. Perspective: Quantum mechanical methods in biochemistry and biophysics.

3. Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities.

Review 4. Mono- and binuclear non-heme iron chemistry from a theoretical perspective.

5. Electronic landscape of the P-cluster of nitrogenase as revealed through many-electron quantum wavefunction simulations.

6. QM/MM Analysis of Transition States and Transition State Analogues in Metalloenzymes.

7. Low-energy spectrum of iron-sulfur clusters directly from many-particle quantum mechanics.

8. Biomolecular QM/MM Simulations: What Are Some of the "Burning Issues"?

9. Accurate ab Initio Spin Densities.

10. FCIQMC-Tailored Distinguishable Cluster Approach: Open-Shell Systems.