The Divide-and-Conquer QAOA for Max Cut module takes a learner from the implementation of QAOA to solve a small max problem to an application of a divide-and-conquer QAOA algorithm to a large max cut problem using parallel computation. This visual introduction to QAOA and circuit cutting provides the learner the background to understand more advanced topics such as ADAPT-QAOA, Adaptive Circuit Knitting, and QAOA-GPT.
Prerequisites:
- Familiarity with Python with enough comfort to refer to Python package documentation, specifically NetworkX, as needed
- Completion of the Quick Start to Quantum Computing with CUDA-Q course or equivalent familiarity with variational quantum algorithms (e.g. VQE or QAOA).
The Jupyter notebooks in this folder are designed to run in an environment with CUDA-Q with Python. For instructions on how to install CUDA-Q on your machine, check out this guide.
Otherwise, explore our Learning Pathways page for additional cloud-based options to run these notebooks.