ipie stands for Intelligent Python-based Imaginary-time Evolution with a focus on simplicity and speed.
ipie inherits a lot of QMC features from pauxy.
Our first release paper is out at https://arxiv.org/abs/2209.04015
ipie currently supports:
- estimation of the ground state energy of ab-initio systems using phaseless AFQMC with support for CPUs and GPUs.
- simple data analysis.
- other legacy functionalities available in pauxy such as the ground state and finite-temperature energies and properties (via backpropagation) of the ab initio, UEG, Hubbard, and Hubbard-Holstein models.
Clone the repository
$ git clone https://github.com/linusjoonho/ipie.git
and run the following in the top-level ipie directory
$ pip install -r requirements.txt $ python setup.py build_ext --inplace $ python setup.py install
You may also need to set your PYTHONPATH appropriately.
- python (>= 3.6)
- numpy
- scipy
- h5py
- mpi4py
- cython
- pandas
Minimum versions are listed in the requirements.txt. To run the tests you will need pytest. To perform error analysis you will also need pyblock.
ipie contains unit tests and some longer driver tests that can be run using pytest by running:
$ pytest -v
in the base of the repo. Some longer parallel tests are also run through the CI. See .github/workflows/ci2.yml for more details.
Documentation and tutorials are available at readthedocs.