Using the Quantum Approximate Optimization Algorithm (QAOA) to Solve Binary-Variable Optimization Problems
• Podcast
Jason Larkin and Daniel Justice, researchers in the SEI’s AI Division, discuss a paper outlining their efforts to simulate the performance of Quantum Approximate Optimization Algorithm (QAOA) for the Max-Cut problem.
Publisher
Software Engineering Institute
Topic or Tag
Listen
Watch
Abstract
Jason Larkin and Daniel Justice, researchers in the SEI’s AI Division, discuss a paper outlining their efforts to simulate the performance of Quantum Approximate Optimization Algorithm (QAOA) for the Max-Cut problem and compare it with some of the best classical alternatives, for exact, approximate, and heuristic solutions.
