Coder Social home page Coder Social logo

deepqmc's Introduction

DeepQMC

checks coverage python pypi commits since last commit license code style doi

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 a flexible neural network wave function ansatz, that can be configured to obtain a broad range of molecular neural network wave functions. Config files for the instantiation of variants of PauliNet, FermiNet, DeepErwin and PsiFormer can be found under src/deepqmc/conf/ansatz.

Installation

Install and update to the latest release using Pip:

pip install -U deepqmc

To install DeepQMC from a local Git repository run:

git clone https://github.com/deepqmc/deepqmc
cd deepqmc
pip install -e .[dev]

If Pip complains about setup.py not being found, please update to the latest Pip version.

The above installation will result in the CPU version of JAX. However, running DeepQMC on the GPU is highly recomended. To enable GPU support make sure to upgrade JAX to match the CUDA and cuDNN versions of your system. For most users this can be achieved with:

# CUDA 12 installation
pip install --upgrade "jax[cuda12_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

# CUDA 11 installation
pip install --upgrade "jax[cuda11_pip]" -f https://storage.googleapis.com/jax-releases/jax_cuda_releases.html

If issues arise during the JAX installation visit the JAX Install Guide.

Documentation and exemplary usage

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

An introduction to the methodology and exemplary experiments can be found in the associated software paper.

Citation

If you use DeepQMC for your work, please cite our implementation paper:

@article{10.1063/5.0157512,
    author = {Schätzle, Z. and Szabó, P. B. and Mezera, M. and Hermann, J. and Noé, F.},
    title = "{DeepQMC: An open-source software suite for variational optimization of deep-learning molecular wave functions}",
    journal = {The Journal of Chemical Physics},
    volume = {159},
    number = {9},
    pages = {094108},
    year = {2023},
    month = {09},
    issn = {0021-9606},
    doi = {10.1063/5.0157512},
    url = {https://doi.org/10.1063/5.0157512},
}

The repository can be cited as:

@software{deepqmc,
	author = {Jan Hermann and
		  Zeno Schätzle and
		  Peter Bernát Szabó and
		  Matěj Mezera and
		  {DeepQMC Contributers}},
	title = {{DeepQMC}},
	year = {2023},
	publisher = {Zenodo},
	copyright = {MIT},
	url = {https://github.com/deepqmc/deepqmc},
	doi = {10.5281/zenodo.7503172},
}

deepqmc's People

Contributors

jhrmnn avatar szbernat avatar zenoone avatar mmezic avatar ae-foster avatar kmaziarz avatar sauceda avatar mmjb avatar penify-dev[bot] avatar

Watchers

Robert Bongart (MSc MSc MA) avatar

Recommend Projects

  • React photo React

    A declarative, efficient, and flexible JavaScript library for building user interfaces.

  • Vue.js photo Vue.js

    🖖 Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.

  • Typescript photo Typescript

    TypeScript is a superset of JavaScript that compiles to clean JavaScript output.

  • TensorFlow photo TensorFlow

    An Open Source Machine Learning Framework for Everyone

  • Django photo Django

    The Web framework for perfectionists with deadlines.

  • D3 photo D3

    Bring data to life with SVG, Canvas and HTML. 📊📈🎉

Recommend Topics

  • javascript

    JavaScript (JS) is a lightweight interpreted programming language with first-class functions.

  • web

    Some thing interesting about web. New door for the world.

  • server

    A server is a program made to process requests and deliver data to clients.

  • Machine learning

    Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.

  • Game

    Some thing interesting about game, make everyone happy.

Recommend Org

  • Facebook photo Facebook

    We are working to build community through open source technology. NB: members must have two-factor auth.

  • Microsoft photo Microsoft

    Open source projects and samples from Microsoft.

  • Google photo Google

    Google ❤️ Open Source for everyone.

  • D3 photo D3

    Data-Driven Documents codes.