Read this in other languages: English, Spanish.
- About the Project
- Contributors
- Getting Started
- Usage
- Contributing
- License
- Contact
- Acknowledgements
- Credits
Development and testing project on the performance of Grover's algorithm compared to other search algorithms, this project was developed during the Qiskit Hackathon Bilbao 2019.
There is a brief explanation in this Elevator Pitch in PowerPoint or pdf.
Update: we won second place in our category :D
Thanks to the support staff that helped with the theoretical content and with Qiskit language:
 Oier Ajenjo |
 Carlos Lago |
 Alberto Miranda |
 Aitor Morais |
 Rafael Romón |
To get a local copy up and running follow these simple example steps:
- python3
- python3-dev
Download and install Python from this link
sudo apt install python3 python3-dev- Clone the repository
git clone https://github.com/oierajenjo/q-Grover-Algorithm- Install Python packages
pip install -r requirements.txtsudo pip3 install -r requirements.txt- You may need to configure additional settings in the settings.py file like db or localizations.
You can run an interactive Demo from the qGrover folder as a normal Django application.
Note: For more information, please refer to the Offical Documentation.
The performance graphs have been made with the tools in the algorithm_comparison folder.
To make a test, run the file comparisons.py.
Feel free to open pull requests with new features or bug fixes. Any contributions you make are greatly appreciated.
As the license states, you can fork and even redistribute this as long as it remains as a GPL project.
Distributed under the Apache License. See LICENSE for more information.
If you are not that tech savvy feel free to ask us any questions via email, just keep in mind we might not know the answer to your questions as we did this in a Hackathon and we are not experts in this area.
 Vic Pina |
 Ana Martín |
 Giancarlo Gatti |
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