Metadata-Version: 2.4
Name: qugrad
Version: 1.0.1
Summary: A Python package for quantum optimal control.
Project-URL: Homepage, https://github.com/Christopher-K-Long/QuGrad
Project-URL: Documentation, https://QuGrad.readthedocs.io/
Project-URL: Issues, https://github.com/Christopher-K-Long/QuGrad/issues
Project-URL: Changelog, https://github.com/Christopher-K-Long/QuGrad/blob/main/ChangeLog.md
Author-email: "Christopher_K._Long" <ckl45@cam.ac.uk>
Maintainer-email: "Christopher_K._Long" <ckl45@cam.ac.uk>
License-Expression: Apache-2.0
License-File: LICENSE
Keywords: control,optimal,quantum
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.9
Requires-Dist: numpy
Requires-Dist: py-ste
Requires-Dist: tensorflow
Description-Content-Type: text/markdown

# QuGrad
A Python package for quantum optimal control.

[![Unit Tests](https://github.com/Christopher-K-Long/QuGrad/actions/workflows/test-python-package.yml/badge.svg)](https://github.com/Christopher-K-Long/QuGrad/actions/workflows/test-python-package.yml)

## Installation

The python package can be installed with pip as follows:
```bash
pip install qugrad
```

If on Linux and using a conda environment you may encounter an error
```
version `GLIBCXX_...' not found
```
to fix this you also need to execute:
```bash
conda install -c conda-forge libstdcxx-ng
```

### Requirements

Requires:
- [PySTE](https://PySTE.readthedocs.io)
- [TensorFlow](https://www.tensorflow.org)
- [NumPy](https://numpy.org)

#### Additional requirements for testing

- [toml](https://github.com/uiri/toml)
- [PyYAML](https://pyyaml.org/)

## Documentation

Documentation including worked examples can be found at: [https://QuGrad.readthedocs.io](https://QuGrad.readthedocs.io)

## Source Code

Source code can be found at: [https://github.com/Christopher-K-Long/QuGrad](https://github.com/Christopher-K-Long/QuGrad)

## Version and Changes

The current version is [`1.0.1`](ChangeLog.md#release-101). Please see the [Change Log](ChangeLog.md) for more details. QuGrad uses [semantic versioning](https://semver.org/).