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
To perform DMET calculations, leverage MPI parallelism, and to use ebcc solvers, optional dependencies must be installed. See the documentation for details.
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 papers should be cited in publications which make use of Vayesta:
Max Nusspickel, Basil Ibrahim and George H. Booth, arXiv:2210.14561 (2023).
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).