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Vayesta

Vayesta is a Python package for performing correlated wave function-based quantum embedding in ab initio molecules and solids, as well as lattice models.

Installation

To install, clone the repository

git clone git@github.com:BoothGroup/Vayesta.git

Install the package using pip from the top-level directory, which requires CMake

python -m pip install . --user

Quickstart

Examples of how to use Vayesta can be found in the vayesta/examples directory and a quickstart guide can be found in the documentation.

Authors

M. Nusspickel, O. J. Backhouse, B. Ibrahim, A. Santana-Bonilla, C. J. C. Scott, G. H. Booth

Citing Vayesta

The following paper should be cited in publications which make use of Vayesta:

Max Nusspickel and George H. Booth, Phys. Rev. X 12, 011046 (2022).

Publication which utilize Extended Density-matrix Embedding Theory (EDMET) should also cite:

Charles J. C. Scott and George H. Booth, Phys. Rev. B 104, 245114 (2021).