Abstract
Recently, the authors implemented the linear-scaling divide-and-conquer (DC) quantum chemical methodologies into the GAMESS-US package, which is available without charge. In this Chapter, we summarized recent developments in the DC methods, namely, the density-matrix-based DC self-consistent field (SCF) and the DC-based post-SCF electron correlation methods. Especially, the DC-based post-SCF calculation is considerably efficient, i.e., its computational time achieves near-linear scaling with respect to the system size [O(N 1)] and the required memory and scratch sizes are hardly dependent on the system size [O(N 0)]. Numerical assessments also revealed the reliability of the DC methods.
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Acknowledgments
We thank Prof. M. S. Gordon and Dr. M. W. Schmidt at Iowa State University for their support when implementing our method to GAMESS program. We are also grateful to many group members, especially Dr. T. Akama, for their contributions. Some of the present calculations were performed at the Research Center for Computational Science (RCCS), Okazaki Research Facilities, National Institutes of Natural Sciences (NINS). The studies were supported in part by a Grant-in-Aid for Scientific Research on Priority Areas “Molecular Theory for Real Systems” “KAKENHI 18066016,” the Next Generation Integrated Nanoscience Simulation Software Project, and the Global COE “Practical Chemical Wisdom” from the Ministry of Education, Culture, Sports, Science and Technology (MEXT), Japan. A project research grant for “Development of high-performance computational environment for quantum chemical calculation and its assessment” from the Research Institute for Science and Engineering (RISE) at Waseda University is gratefully acknowledged. One of the authors (MK) was indebted to the Research Fellowship for Young Scientists from Japan Society for the Promotion of Science (JSPS).
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Kobayashi, M., Nakai, H. (2011). Divide-and-Conquer Approaches to Quantum Chemistry: Theory and Implementation. In: Zalesny, R., Papadopoulos, M., Mezey, P., Leszczynski, J. (eds) Linear-Scaling Techniques in Computational Chemistry and Physics. Challenges and Advances in Computational Chemistry and Physics, vol 13. Springer, Dordrecht. https://doi.org/10.1007/978-90-481-2853-2_5
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