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  5. Comparison of many‐particle representations for selected‐CI I: A tree based approach

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Article
English
2021

Comparison of many‐particle representations for selected‐CI I: A tree based approach

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English
2021
Journal of Computational Chemistry
Vol 42 (14)
DOI: 10.1002/jcc.26518

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Frank Neese
Frank Neese

Max Planck

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Vijay Gopal Chilkuri
Frank Neese

Abstract

The full configuration interaction (FCI) method is only applicable to small molecules with few electrons in moderate size basis sets. One of the main alternatives to obtain approximate FCI energies for bigger molecules and larger basis sets is selected CI. However, due to: (a) the lack of a well‐defined structure in a selected CI Hamiltonian, (b) the potentially large number of electrons together with c) potentially large orbital spaces, a computationally and memory efficient algorithm is difficult to construct. In the present series of papers, we describe our attempts to address these issues by exploring tree‐based approaches. At the same time, we devote special attention to the issue of obtaining eigenfunctions of the total spin squared operator since this is of particular importance in tackling magnetic properties of complex open shell systems. Dedicated algorithms are designed to tackle the CI problem in terms of determinant, configuration (CFG) and configuration state function many‐particle bases by effective use of the tree representation. In this paper we describe the underlying logic of our algorithm design and discuss the advantages and disadvantages of the different many particle bases. We demonstrate by the use of small examples how the use of the tree simplifies many key algorithms required for the design of an efficient selected CI program. Our selected CI algorithm, called the iterative configuration expansion, is presented in the penultimate part. Finally, we discuss the limitations and scaling characteristics of the present approach.

How to cite this publication

Vijay Gopal Chilkuri, Frank Neese (2021). Comparison of many‐particle representations for selected‐CI I: A tree based approach. Journal of Computational Chemistry, 42(14), pp. 982-1005, DOI: 10.1002/jcc.26518.

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Publication Details

Type

Article

Year

2021

Authors

2

Datasets

0

Total Files

0

Language

English

Journal

Journal of Computational Chemistry

DOI

10.1002/jcc.26518

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