qoolqit 0.3.3

A Python library for developing algorithms in the Rydberg Analog Model.

QoolQit is a Python library for algorithm development in the Rydberg Analog Model.

For more detailed information, check out the documentation.

Installation

QoolQit can be installed from PyPi with pip/pipx/uv as follows

pip install qoolqit

pipx install qoolqit

uv pip install qoolqit

Please, don't forget to create a virtual environment first.

Install from source

If you wish to install directly from the source, for example, if you are developing code for QoolQit, you can:

1. Clone the QoolQit GitHub repository

git clone https://github.com/pasqal-io/qoolqit.git

2. Setup an environment for developing. We recommend using Hatch. With Hatch installed, you can enter the qoolqit repository and run

hatch shell

This will automatically take you into an environment with the necessary dependencies. Alternatively, if you wish to use a different environment manager like conda or venv, you can instead enter the qoolqit repository from within the environment and run

pip install -e .

Using any pyproject-compatible Python manager

For usage within a project with a corresponding pyproject.toml file, you can add

  "qoolqit"

to the list of dependencies.

Getting in touch

• Pasqal Community Portal (forums, chat, tutorials, examples, code library).
• GitHub Repository (source code, issue tracker).
• Professional Support (if you need tech support, custom licenses, a variant of this library optimized for your workload, your own QPU, remote access to a QPU, ...)