This repository contains fast CPU and GPU simulators for benchmarking the Quantum Approximate Optimization Algorithm, as well as scripts for generating matching quantum circuits for execution on hardware. See the examples folder for a demo of this package.
Creating a virtual environment is recommended before installing.
python -m venv qokit
source qokit/bin/activate
pip install -U pip
Install requires python>=3.9 and pip >= 23. It is recommended to update your pip using pip install --upgrade pip before install.
git clone https://github.com/jpmorganchase/QOKit.git
cd QOKit/
pip install -e .
Some optional parts of the package require additional dependencies.
- Using commercial IP solvers to solve optimizations problems:
pip install qokit[solvers] - GPU simulation:
pip install qokit[GPU] - Development:
pip install qokit[dev]
If compilation fails, try installing just the Python version using QOKIT_PYTHON_ONLY=1 pip install -e ..
Installation can be verified by running tests using pytest.
For MaxCut, the datasets in qokit/assets/maxcut_datasets must be inflated