| Name | qosst-skr JSON |
| Version |
0.10.0
JSON |
| download |
| home_page | https://github.com/qosst |
| Summary | Secret Key Rate (SKR) submodule of QOSST, with the different methods to compute the Secret Key Rate. |
| upload_time | 2024-04-29 12:43:41 |
| maintainer | None |
| docs_url | None |
| author | Yoann Piétri |
| requires_python | <3.13,>=3.9 |
| license | GPLv3 |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# qosst-skr
<center>
</center>
This project is part of [QOSST](https://github.com/qosst/qosst).
## Features
`qosst-skr` is the project that holds the codes to compute the Secret Key Rate (SKR) in different cases. For now, the SKR can be computed in the following cases:
* Gaussian Trusted Heterodyne Asymptotic;
* Gaussian Trusted Homodyne Asymptotic;
* Gaussian Untrusted Homodyne Asymptotic.
## Installation
The module can be installed with the following command:
```console
pip install qosst-skr
```
It is also possible to install it directly from the github repository:
```console
pip install git+https://github.com/qosst/qosst-skr
```
It also possible to clone the repository before and install it with pip or poetry
```console
git clone https://github.com/qosst/qosst-skr
cd qosst-skr
poetry install
pip install .
```
## Documentation
The whole documentation can be found at https://qosst-skr.readthedocs.io/en/latest/
## Usage
`qosst-skr` can be used by importing the functions and using the `skr` static method from each class. The parameters depends on the considered case.
```python
from qosst_skr.gaussian_trusted_heterodyne_asymptotic import GaussianTrustedHeterodyneAsymptotic
k = GaussianTrustedHeterodyneAsymptotic(Va=5, eta=0.5, Vel=0.1, xi=0.01, T=0.5)
```
Refer to the documentation for more information.
## License
As for all submodules of QOSST, `qosst-skr` is shipped under the [Gnu General Public License v3](https://www.gnu.org/licenses/gpl-3.0.html).
## Contributing
Contribution are more than welcomed, either by reporting issues or proposing merge requests. Please check the contributing section of the [QOSST](https://github.com/qosst/qosst) project fore more information.
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