/DDQC_Demo

Primary LanguageJupyter NotebookGNU General Public License v3.0GPL-3.0

Data-Driven Quantum Chemistry Case Studies

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.

Code Versions

  • DDCCSD=0.1
  • DDCASPT2=0.1

Setup

  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
  1. Install conda environment named ddqc_demo
cd DDQC_Demo/conda-envs
conda env create -f ddqc_demo.yml
  1. Link conda environment to jupyter kernel
conda activate ddqc_demo
ipython kernel install --user --name=ddqc_demo
conda deactivate

Case Studies

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