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adcc: A versatile toolkit for rapid development of algebraic-diagrammatic construction methods
Stockholm University, Faculty of Science, Department of Physics. Heidelberg University, Germany.
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Number of Authors: 52020 (English)In: Wiley Interdisciplinary Reviews. Computational Molecular Science, ISSN 1759-0876, E-ISSN 1759-0884, article id e1462Article in journal (Refereed) Epub ahead of print
Abstract [en]

ADC-connect (adcc) is a hybrid python/C++ module for performing excited state calculations based on the algebraic-diagrammatic construction scheme for the polarization propagator (ADC). Key design goal is to restrict adcc to this single purpose and facilitate connection to external packages, for example, for obtaining the Hartree-Fock references, plotting spectra, or modeling solvents. Interfaces to four self-consistent field codes have already been implemented, namely pyscf, psi4, molsturm, and veloxchem. The computational workflow, including the numerical solvers, is implemented in python, whereas the working equations and other expensive expressions are done in C++. This equips adcc with adequate speed, making it a flexible toolkit for both rapid development of ADC-based computational spectroscopy methods as well as unusual computational workflows. This is demonstrated by three examples. Presently, ADC methods up to third order in perturbation theory are available in adcc, including the respective core-valence separation and spin-flip variants. Both restricted or unrestricted Hartree-Fock references can be employed.

This article is categorized under: Software > Simulation Methods Electronic Structure Theory > Ab Initio Electronic Structure Methods Theoretical and Physical Chemistry > Spectroscopy Software > Quantum Chemistry

Place, publisher, year, edition, pages
2020. article id e1462
Keywords [en]
algebraic diagrammatic construction methods, computational spectroscopy, python
National Category
Chemical Sciences
Identifiers
URN: urn:nbn:se:su:diva-178618DOI: 10.1002/wcms.1462ISI: 000506205800001OAI: oai:DiVA.org:su-178618DiVA, id: diva2:1396109
Available from: 2020-02-25 Created: 2020-02-25 Last updated: 2020-02-25

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