Recent developments in the PySCF program package.

@article{Sun2020RecentDI,
  title={Recent developments in the PySCF program package.},
  author={Qiming Sun and Xing Zhang and Samragni Banerjee and Peng Bao and Marc Barbry and Nick S Blunt and Nikolay A. Bogdanov and George H. Booth and Jia Chen and Zhi-Hao Cui and Janus Juul Eriksen and Yang Gao and Sheng Guo and Jan Hermann and Matthew R. Hermes and Kevin J Koh and Peter Koval and Susi Lehtola and Zhendong Li and Junzi Liu and Narbe Mardirossian and James D. McClain and Mario Motta and Bastien Mussard and Hung Q. Pham and Artem Pulkin and Wirawan Purwanto and Paul J. Robinson and Enrico Ronca and Elvira R. Sayfutyarova and Maximilian Scheurer and Henry F. Schurkus and James E. T. Smith and Chong Sun and Shi-Ning Sun and Shiv Upadhyay and Lucas K. Wagner and Xiao Wang and Alec F. White and James Daniel Whitfield and Mark J. Williamson and Sebastian Wouters and J. Yang and Jason M. Yu and Tianyu Zhu and Timothy C. Berkelbach and Sandeep Sharma and Alexander Yu. Sokolov and Garnet Kin-Lic Chan},
  journal={The Journal of chemical physics},
  year={2020},
  volume={153 2},
  pages={
          024109
        }
}
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… 

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References

SHOWING 1-10 OF 163 REFERENCES

VeloxChem: A Python‐driven density‐functional theory program for spectroscopy simulations in high‐performance computing environments

An open‐source program named VeloxChem has been developed for the calculation of electronic real and complex linear response functions at the levels of Hartree–Fock and Kohn–Sham density functional

adcc: A versatile toolkit for rapid development of algebraic‐diagrammatic construction methods

TLDR
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.

Third-order algebraic diagrammatic construction theory for electron attachment and ionization energies: Conventional and Green's function implementation.

TLDR
The results demonstrate that EA-/IP-ADC(n) (n = 2, 3) methods are efficient and accurate alternatives to widely used electronic structure methods for simulations of electron attachment and ionization properties.

Generalized Many-Body Expanded Full Configuration Interaction Theory.

TLDR
It is argued that generalized MBE-FCI theory possesses an immense potential to yield near-exact correlation energies for molecular systems of unprecedented size, composition, and complexity in the years to come.

Periodic Electronic Structure Calculations With Density Matrix Embedding Theory.

TLDR
This work develops a periodic version of density matrix embedding theory, DMET, with which it is possible to perform electronic structure calculations on periodic systems, and compute the band structure of solid-state materials, and expects that periodic DMET can be a promising first principle method for strongly correlated materials.

Efficient Implementation of Ab Initio Quantum Embedding in Periodic Systems: Density Matrix Embedding Theory.

TLDR
The formulation of ab initio DMET is demonstrated in the computation of ground-state properties such as the total energy, equation of state, magnetic moment and correlation functions.

Efficient Formulation of Ab Initio Quantum Embedding in Periodic Systems: Dynamical Mean-Field Theory.

TLDR
This work presents an efficient ab initio dynamical mean-field theory (DMFT) implementation for quantitative simulations in solids and produces accurate spectral functions compared to both benchmark periodic coupled-cluster computations and experimental spectra.

CPPE: An Open-Source C++ and Python Library for Polarizable Embedding.

We present a modular open-source library for polarizable embedding (PE) named CPPE. The library is implemented in C++, and it additionally provides a Python interface for rapid prototyping and

Wannier90 as a community code: new features and applications.

  • G. PizziV. Vitale J. Yates
  • Computer Science
    Journal of physics. Condensed matter : an Institute of Physics journal
  • 2019
TLDR
New features, capabilities, and code development model of Wannier90 aim to further sustain and expand the community uptake and range of applicability, that nowadays spans complex and accurate dielectric, electronic, magnetic, optical, topological and transport properties of materials.

Atoms in Molecules From Alchemical Perturbation Density Functional Theory.

TLDR
The results suggest that APDFT based AIMs enable meaningful, interesting, and counter-intuitive interpretations of chemical bonding and electron densities, as well as comparison to atomic energy estimates resulting from DFT trained neural network models and atomic basis set overlap within CCSD.
...