Quantum algorithms can be used to solve classically hard optimization problem such as the MaxCut problem. In our paper, we adopt a recently developed implementation (ITE-BE) of imaginary time evolution using exact block encoding to solve for the MaxCut problem. We also manage to integrate the ITE-BE approach with quantum approximate optimization algorithm (QAOA). The source code of these quantum solver for the MaxCut problem is in the imaginary_time_optimization.
Since the original comprehensive data is large, in the data folder we only include the python code to solve for MaxCut problem of unweight 3-regular graphs (u3R) and bipartite graphs rather than uploading real data files.
If you have any questions or suggestions, please contact via email daweiz@usc.edu or create an Github issue in this repository.