This repository provides examples of data-driven quantum chemistry (DDQC) methods from the "Data-Driven acceleration of coupled-cluster and perturbation theory methods" book chapter in Quantum Chemistry in the Age of Machine Learning.

• DDCCSD=0.1
• DDCASPT2=0.1

1. Install conda using Miniconda
2. You will need a valid install of Psi4 and Psi4NumPy to run the DDCCSD tutorials. Link for installation information Psi4NumPy
3. Clone repository

git clone https://github.com/ChemRacer/DDQC_Demo.git

4. Install conda environment named ddqc_demo

cd DDQC_Demo/conda-envs
conda env create -f ddqc_demo.yml

5. Link conda environment to jupyter kernel

conda activate ddqc_demo
ipython kernel install --user --name=ddqc_demo
conda deactivate

To run the DDCCSD tutorial:

cd DDQC_Demo/DDCCSD/
jupyter notebook DDCCSD_model.ipynb

To run the DDCASPT2 tutorial:

cd DDQC_Demo/DDCASPT2/
jupyter notebook gen_pair.ipynb