QuEmb is a robust framework designed to implement the Bootstrap Embedding (BE) method, efficiently treating electron correlation in molecules, surfaces, and solids. This repository contains the Python implementation of the BE methods, including periodic bootstrap embedding. The code leverages PySCF library for quantum chemistry calculations and utlizes Python's multiprocessing module to enable parallel computations in high-performance computing environments.
QuEmb includes two libraries: molbe
and kbe
.
The molbe
library implements BE for molecules and supramolecular complexes,
while the kbe
library is designed to handle periodic systems such as surfaces and solids using periodic BE.
- Fragment-based quantum embedding: Utilizes flexible system partioning with overlapping regions to improve quantum embedding techniques.
- Periodic Bootstrap Embedding: Extends BE method to treat periodic systems (1D & 2D systems) using reciprocal space sums.
- High accuracy and efficiency: Capable of recovering ~99.9% of electron correlation energy.
- Parallel computing: Employ's Python multiprocessing module to perform parallel computations across multiple processors.
- Python 3.6 or higher
- PySCF library
- Numpy
- Scipy
- libDMET (required for periodic BE)
- Wannier90&& (to use Wannier functions)
&&Wannier90 code is interfaced via libDMET in QuEmb
-
Clone the repository:
git clone https://github.com/oimeitei/quemb.git cd quemb
-
Install QuEmb using one of the following approaches:
pip install .
or simply add
path/to/quemd
toPYTHONPATH
export PYTHONPATH=/path/to/quemb:$PYTHONPATH
For conda (or virtual environment) installations, after creating your environment, specify the path to mol-be source as a path file, as in:
echo path/to/quemb > $(python -c "from distutils.sysconfig import get_python_lib; print(get_python_lib())")/quemb.pth
# Molecular
from quemb.molbe import fragpart
from quemb.molbe import BE
# Periodic
#from quemb.kbe import fragpart
#from quemb.kbe import BE
# Perform pyscf HF/KHF calculations
# get mol: pyscf.gto.M or pyscf.pbc.gto.Cell
# get mf: pyscf.scf.RHF or pyscf.pbc.KRHF
# Define fragments
myFrag = fragpart(be_type='be2', mol=mol)
# Initialize BE
mybe = BE(mf, myFrag)
# Perform density matching in BE
mybe.optimize(solver='CCSD')
See documentation and quemb/example
for more details.
Comprehensive documentation for QuEmb is available at quemb/docs
. The documentation provides detailed infomation on installation, usage, API reference, and examples. To build the documentation locally, simply navigate to docs
and build using make html
or make latexpdf
.
Alternatively, you can view the latest documentation online here.
The methods implemented in this code are described in details in the following papers:
- OR Meitei, T Van Voorhis, Periodic bootstrap embedding, JCTC 19 3123 2023
- OR Meitei, T Van Voorhis, Electron correlation in 2D periodic systems, arXiv:2308.06185
- HZ Ye, HK Tran, T Van Voorhis, Bootstrap embedding for large molecular systems, JCTC 16 5035 2020