deepqmc 0.1.1

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 written in PyTorch as trial wave functions. Besides the core functionality, it contains implementations of the following ansatzes:

• PauliNet: https://arxiv.org/abs/1909.08423

Installing

Install and update using Pip.

pip install -U deepqmc[wf,train]

A simple example

from deepqmc import Molecule, evaluate, train
from deepqmc.wf import PauliNet

mol = Molecule.from_name('LiH')
net = PauliNet.from_hf(mol).cuda()
train(net)
evaluate(net)

Links

• Documentation: https://deepqmc.github.io