Topic
PySCF
About: PySCF is a research topic. Over the lifetime, 15 publications have been published within this topic receiving 865 citations.
Papers
TL;DR: The capabilities and design philosophy of the current version of the PySCF package are document, which is as efficient as the best existing C or Fortran‐based quantum chemistry programs.
Abstract: Python-based simulations of chemistry framework (PySCF) is a general-purpose electronic structure platform designed from the ground up to emphasize code simplicity, so as to facilitate new method development and enable flexible computational workflows. The package provides a wide range of tools to support simulations of finite-size systems, extended systems with periodic boundary conditions, low-dimensional periodic systems, and custom Hamiltonians, using mean-field and post-mean-field methods with standard Gaussian basis functions. To ensure ease of extensibility, PySCF uses the Python language to implement almost all of its features, while computationally critical paths are implemented with heavily optimized C routines. Using this combined Python/C implementation, the package is as efficient as the best existing C or Fortran-based quantum chemistry programs. In this paper, we document the capabilities and design philosophy of the current version of the PySCF package. WIREs Comput Mol Sci 2018, 8:e1340. doi: 10.1002/wcms.1340
This article is categorized under:
Structure and Mechanism > Computational Materials Science
Electronic Structure Theory > Ab Initio Electronic Structure Methods
Software > Quantum Chemistry
1,592 citations
California Institute of Technology1, Ohio State University2, Chinese Academy of Sciences3, University of Cambridge4, Max Planck Society5, King's College London6, University of Florida7, University of Bristol8, Google9, Free University of Berlin10, University of Minnesota11, University of Notre Dame12, University of Helsinki13, Beijing Normal University14, Johns Hopkins University15, Amgen16, IBM17, University of Colorado Boulder18, Delft University of Technology19, Old Dominion University20, Columbia University21, Yale University22, Interdisciplinary Center for Scientific Computing23, University of Pittsburgh24, University of Illinois at Urbana–Champaign25, Dartmouth College26, University of Hong Kong27, University of California, Irvine28
TL;DR: PySCF as mentioned in this paper is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows.
Abstract: PySCF is a Python-based general-purpose electronic structure platform that supports first-principles simulations of molecules and solids as well as accelerates the development of new methodology and complex computational workflows. This paper explains the design and philosophy behind PySCF that enables it to meet these twin objectives. With several case studies, we show how users can easily implement their own methods using PySCF as a development environment. We then summarize the capabilities of PySCF for molecular and solid-state simulations. Finally, we describe the growing ecosystem of projects that use PySCF across the domains of quantum chemistry, materials science, machine learning, and quantum information science.
797 citations
TL;DR: ADCconnect as discussed by the authors is a hybrid python/C++ module for performing excited state calculations based on the algebraic-diagrammatic construction scheme for the polarisation propagator (ADC).
Abstract: ADC-connect (adcc) is a hybrid python/C++ module for performing excited state calculations based on the algebraic-diagrammatic construction scheme for the polarisation propagator (ADC). Key design goal is to restrict adcc to this single purpose and facilitate connection to external packages, e.g., for obtaining the Hartree-Fock references, plotting spectra, or modelling 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, are 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.
37 citations
TL;DR: ADC‐connect is a hybrid python/C++ module for performing excited state calculations based on the algebraic‐diagrammatic construction scheme for the polarization propagator (ADC) to facilitate connection to external packages, for example, for obtaining the Hartree–Fock references, plotting spectra, or modeling solvents.
Abstract: ADC-connect (adcc) is a hybrid python/C++ module for performing excited state calculations based on the algebraic-diagrammatic construction scheme for the polarisation propagator (ADC). Key design goal is to restrict adcc to this single purpose and facilitate connection to external packages, e.g., for obtaining the Hartree-Fock references, plotting spectra, or modelling 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, are 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.
37 citations
TL;DR: A coupled cluster framework for coupled systems of electrons and harmonic phonons is described and neutral and charged excitations are accessed via the equation-of-motion version of the theory.
Abstract: We describe a coupled cluster framework for coupled systems of electrons and harmonic phonons. Neutral and charged excitations are accessed via the equation-of-motion version of the theory. Benchmarks on the Hubbard–Holstein model allow us to assess the strengths and weaknesses of different coupled cluster approximations, which generally perform well for weak to moderate coupling. Finally, we report progress toward an implementation for ab initio calculations on solids and present some preliminary results on finite-size models of diamond with a linear electron–phonon coupling. We also report the implementation of electron–phonon coupling matrix elements from crystalline Gaussian type orbitals within the PySCF program package.
34 citations
Related Topics (5)
Performance Metrics
| Year | Papers |
|---|---|
| 2021 | 2 |
| 2020 | 7 |
| 2019 | 4 |
| 2018 | 2 |