semvec/pypi-packages huggingface dataset:
qmp-kit 0.0.56
Quantum Manybody Problem
Requires Python: >=3.12
Keywords: quantum, manybody, quantum-chemistry, quantum-simulation, molecular-simulation, algorithms, simulation, wave-function, ground-state, ansatz, torch, pytorch

# Quantum Many-Body Problem Kit (qmp-kit)

The quantum many-body problem kit (`qmp-kit`) is a powerful tool designed to solve quantum-many-body problems especially for strongly correlated systems. This project includes our work on [Hamiltonian-Guided Autoregressive Selected-Configuration Interaction Achieves Chemical Accuracy in Strongly Correlated Systems](https://pubs.acs.org/doi/10.1021/acs.jctc.5c01415).

## About The Project

This repository hosts a [Python][python-url] package named `qmp-kit`, dedicated to solving the quantum-many-body problem.
It implements a suite of algorithms and interfaces with various model descriptors, such as the [OpenFermion][openfermion-url] format and FCIDUMP.
Additionally, `qmp` can efficiently utilize accelerators such as GPU(s) to enhance its performance.
The package's main entry point is a command line interface (CLI) application, also named `qmp`.

## Getting Started

To run this application locally, you need GPU(s) with [CUDA][cuda-url] support and a properly installed GPU driver (typically included with the CUDA Toolkit installation).

### Local Installation

To install locally, users first needs to install the [CUDA toolkit][cuda-url].

The `qmp` requires Python >= 3.12.
After setting up a compatible Python environment such as using [Anaconda][anaconda-url], [Miniconda][miniconda-url], [venv][venv-url] or [pyenv][pyenv-url], users can install [our prebuilt package][our-pypi-url] using:
```
pip install qmp-kit
```
If users face network issues, consider setting up a mirror with the `-i` option.

Users can then invoke the `qmp` script.

Please note that if the CUDA toolkit version is too old, users must install a compatible PyTorch version before running `pip install qmp-kit`.
For example, use `pip install torch --index-url https://download.pytorch.org/whl/cu118` for CUDA 11.8 (see [PyTorch’s guide][pytorch-install-url] for details).
This older CUDA-compatible PyTorch must be installed first, otherwise, users will need to uninstall all existing PyTorch/CUDA-related python packages before reinstalling the correct version.

## Contributing

Contributions are welcome! Please see [CONTRIBUTING.md](CONTRIBUTING.md) for detailed guidelines.

## License

This project is distributed under the GPLv3 License. See [LICENSE.md](LICENSE.md) for more information.

[python-url]: https://www.python.org/
[openfermion-url]: https://quantumai.google/openfermion
[cuda-url]: https://docs.nvidia.com/cuda/
[anaconda-url]: https://www.anaconda.com/
[miniconda-url]: https://docs.anaconda.com/miniconda/
[venv-url]: https://docs.python.org/3/library/venv.html
[pyenv-url]: https://github.com/pyenv/pyenv
[our-pypi-url]: https://pypi.org/project/qmp-kit/
[pytorch-install-url]: https://pytorch.org/get-started/locally/
[models-url]: https://huggingface.co/datasets/USTC-KnowledgeComputingLab/qmp-models
[naqs-url]: https://github.com/tomdbar/naqs-for-quantum-chemistry