Deep-learning quantum Monte Carlo for electrons in real space
Project description
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
Project details
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