deepqmc 1.0.1

Deep-learning quantum Monte Carlo for electrons in real space

DeepQMC

DeepQMC implements variational quantum Monte Carlo for electrons in molecules, using deep neural networks as trial wave functions. The package is based on JAX and Haiku. Besides the core functionality, it contains an implementation of the PauliNet ansatz.

Installing

Install and update using Pip:

pip install -U deepqmc -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

To install DeepQMC from a local Git repository run:

git clone https://github.com/deepqmc/deepqmc
cd deepqmc
pip install -e .[dev] -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

Documentation and exemplary usage

For further information about the DeepQMC package and tutorials covering the basic usage visit the documentation.