FCIQMC-Tailored Distinguishable Cluster Approach | Zendy

Eugenio Vitale | Zendy; Ali Alavi | Zendy; Daniel Kats | Zendy

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FCIQMC-Tailored Distinguishable Cluster Approach

Author(s) -

Eugenio Vitale,

Ali Alavi,

Daniel Kats

Publication year - 2020

Publication title -

journal of chemical theory and computation

Language(s) - Uncategorized

Resource type - Journals

SCImago Journal Rank - 2.001

H-Index - 185

eISSN - 1549-9626

pISSN - 1549-9618

DOI - 10.1021/acs.jctc.0c00470

Subject(s) - computer science , cluster (spacecraft) , coupled cluster , solver , convergence (economics) , set (abstract data type) , basis (linear algebra) , algorithm , atomic orbital , data mining , theoretical computer science , computational science , physics , mathematics , molecule , geometry , quantum mechanics , economics , programming language , economic growth , electron

The tailored approach is applied to the distinguishable cluster method together with a stochastic FCI solver (FCIQMC). It is demonstrated that the new method is more accurate than the corresponding tailored coupled cluster and the pure distinguishable cluster methods. An F12 correction for tailored methods and FCIQMC is introduced, which drastically improves the basis set convergence. A new black-box approach to define the active space using the natural orbitals from the distinguishable cluster is evaluated and found to be a convenient alternative to the usual CASSCF approach.

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