Skip to content
/ qudra Public
forked from qBraid/NYUAD-2022

Leveraging quantum advantage to optimize distributed grids for energy security and sustainability.

License

Notifications You must be signed in to change notification settings

qcenergy/qudra

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

56 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

qudra | قُدرة

Quantum Energy Management

License

Motivation

qudra: power, capacity, ability

Leveraging quantum advantage to optimize distributed grids for energy security and sustainability.

Please check out these slides for more information.

Installation

Conda users, please make sure to conda install pip before running any pip installation if you want to install qudra into your conda environment.

qudra is published on PyPI. So, to install, simply run:

pip install qudra

If you also want to download the dependencies needed to run optional tutorials, please use pip install qudra[dev] or pip install 'qudra[dev]' (for zsh users).

To check if the installation was successful, run:

>>> import qudra

Building from source

To build qudra from source, pip install using:

git clone https://github.com/qcenergy/qudra.git
cd qudra
pip install --upgrade .

If you also want to download the dependencies needed to run optional tutorials, please use pip install --upgrade .[dev] or pip install --upgrade '.[dev]' (for zsh users).

Installation for Devs

If you intend to contribute to this project, please install qudra in editable mode as follows:

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

python3 -m venv venv . venv/bin/activate Please use pip install -e '.[dev]' if you are a zsh user.

Building documentation locally

Set yourself up to use the [dev] dependencies. Then, from the command line run:

mkdocs build

Then, when you're ready to deploy, run:

mkdocs gh-deploy

Acknowledgements

Core Devs: Asil Qraini, Fouad Afiouni, Gargi Chandrakar, Nurgazy Seidaliev, Sahar Ben Rached, Salem Al Haddad, Sarthak Prasad Malla

Mentors: Akash Kant, Shantanu Jha

This project was created at the 2022 NYUAD Hackathon for Social Good in the Arab World: Focusing on Quantum Computing (QC).

About

Leveraging quantum advantage to optimize distributed grids for energy security and sustainability.

Topics

Resources

License

Stars

Watchers

Forks

Packages

No packages published

Languages

  • Jupyter Notebook 58.8%
  • Python 41.2%