# QuGrad
A Python package for quantum optimal control.
[](https://doi.org/10.5281/zenodo.17116721)
[](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) (== 1.*) ([doi:10.5281/zenodo.17116431](https://doi.org/10.5281/zenodo.17116431))
- [TensorFlow](https://www.tensorflow.org) (== 2.*)
- [NumPy](https://numpy.org) (>= 1.21, < 3)
#### 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 [`1.0.2`](ChangeLog.md#release-102). Please see the [Change Log](ChangeLog.md) for more details. QuGrad uses [semantic versioning](https://semver.org/).
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