Vayesta is a Python package for performing correlated wave function-based quantum embedding in ab initio molecules and solids, as well as lattice models.
To install, clone the repository
git clone [email protected]:BoothGroup/Vayesta.git
Install the package using pip from the top-level directory, which requires CMake
python -m pip install . --user
Examples of how to use Vayesta can be found in the vayesta/examples directory
and a quickstart guide can be found in the documentation.
M. Nusspickel, O. J. Backhouse, B. Ibrahim, A. Santana-Bonilla, C. J. C. Scott, G. H. Booth
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).