Notice: This is research code that will not necessarily be maintained to support further releases of Forest and other Rigetti Software. We welcome bug reports and PRs but make no guarantee about fixes or responses.

It is easiest to install QuantumFlow's requirements using conda.

git clone https://github.com/rigetti/quantumflow.git
cd quantumflow
conda install -c conda-forge --file requirements.txt
pip install -e .

You can also install with pip. However some of the requirements are tricky to install (notably tensorflow & cvxpy), and (probably) not everything in QuantumFlow will work correctly.

git clone https://github.com/rigetti/quantumflow.git
cd quantumflow
pip install -r requirements.txt
pip install -e .

Train the QAOA algorithm, with back-propagation gradient descent, to perform MAXCUT on a randomly chosen 6 node graph.

./examples/qaoa_maxcut.py --verbose --steps 5 --nodes 6 random