What is maxcut?

The goal of the maxcut problem is to find the single cut through a graph that maximizes the number of edges cut. The more edges cut, the better.



More specifically, the above is describing the unweighted maxcut problem. In a weighted maxcut problem, each edge has a "weight" assigned to it. The goal changes from maximizing the number of edges cut, to maximizing the sum of the weights of the edges cut.



The Quantum Maxcut Finder uses quantum machine learning, or more specifically, QAOA (the quantum approximate optimization algorithm), to find the line of maximum cut given a weighted or unweighted graph.

Read part 2 to learn how you can calculate the maxcut of any graph using a quantum webapp.