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      Psi4 1.1: An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability

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          Abstract

          P si4 is an ab initio electronic structure program providing methods such as Hartree-Fock, density functional theory, configuration interaction, and coupled-cluster theory. The 1.1 release represents a major update meant to automate complex tasks, such as geometry optimization using complete-basis-set extrapolation or focal-point methods. Conversion of the top-level code to a Python module means that P si4 can now be used in complex workflows alongside other Python tools. Several new features have been added with the aid of libraries providing easy access to techniques such as density fitting, Cholesky decomposition, and Laplace denominators. The build system has been completely rewritten to simplify interoperability with independent, reusable software components for quantum chemistry. Finally, a wide range of new theoretical methods and analyses have been added to the code base, including functional-group and open-shell symmetry adapted perturbation theory (F-SAPT and O-SAPT), density-fitted coupled cluster with frozen natural orbitals [DF-FNO-CCSD(T)], orbital-optimized perturbation and coupled-cluster methods (e.g., OO-MP2 and OO-CCSD), density-fitted multiconfigurational self-consistent field (DF-MCSCF), density cumulant functional theory (DCT), algebraic-diagrammatic construction [ADC(2)] excited states, improvements to the geometry optimizer, and the “X2C” approach to relativistic corrections, among many other improvements.

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          Author and article information

          Journal
          101232704
          33038
          J Chem Theory Comput
          J Chem Theory Comput
          Journal of chemical theory and computation
          1549-9618
          1549-9626
          4 September 2020
          06 June 2017
          11 July 2017
          17 September 2020
          : 13
          : 7
          : 3185-3197
          Affiliations
          [1 ]Center for Computational Molecular Science and Technology, School of Chemistry and Biochemistry, School of Computational Science and Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States.
          [2 ]National Institutes of Health, National Heart, Lung and Blood Institute, Laboratory of Computational Biology, 5635 Fishers Lane, T-900 Suite, Rockville, Maryland 20852, United States.
          [3 ]Department of Chemistry and Biochemistry, Florida State University, Tallahassee, Florida 32306-4390, United States.
          [4 ]Department of Chemistry and Biochemistry, The City College of New York, New York, New York 10031, United States.
          [5 ]Department of Chemistry, Hacettepe University, Ankara 06800, Turkey.
          [6 ]Division of Chemistry and Chemical Engineering, California Institute of Technology, Pasadena, California 91125, United States.
          [7 ]Department of Chemistry, Centre for Theoretical and Computational Chemistry, UiT, The Arctic University of Norway, N-9037 Tromsø, Norway.
          [8 ]Department of Chemistry, Virginia Tech, Blacksburg, Virginia 24061, United States.
          [9 ]Department of Chemistry and Research Center for Smart Molecules, Rikkyo University, 3-34-1 Nishi-ikebukuro, Toshima-ku, Tokyo 171-8501, Japan.
          [10 ]Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States.
          [11 ]Center for Computational Quantum Chemistry, University of Georgia, Athens, Georgia 30602, United States.
          [12 ]Department of Chemistry and Biochemistry, Auburn University, Auburn, Alabama 36849, United States.
          [13 ]Department of Chemistry, Bethel University, St. Paul, Minnesota 55112, United States.
          Article
          PMC7495355 PMC7495355 7495355 nihpa1625530
          10.1021/acs.jctc.7b00174
          7495355
          28489372
          12f437cf-eb3a-4cf0-9ed5-d98dda8c46e5
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