Maximum Cut

The 'Maximum Cut' is a benchmark problem in optimization that involves partitioning the vertices of a graph into two sets to maximize the number of edges between the sets, and it is used to evaluate the performance of quantum optimization algorithms.

Papers using Maximum Cut (4)

Quantum Optimization Algorithms2025Separating Ansatz Discovery from Deployment on Larger Problems: Reinforcement Learning for Modular Circuit Design2025Reinforcement Learning for Variational Quantum Circuits Design2024 · 1 citesSolving Combinatorial Optimization Problems with a Block Encoding Quantum Optimizer2024