Using the Quantum Approximate Optimization Algorithm (QAOA) to Solve Binary-Variable Optimization Problems

from Software Engineering Institute (SEI) Podcast Series · host Dr. Jason Larkin, Daniel Justice

In this podcast from the Carnegie Mellon University Software Engineering Institute, 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.

Episode metadata supplied by the publisher feed · Published Aug 18, 2022

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Using the Quantum Approximate Optimization Algorithm (QAOA) to Solve Binary-Variable Optimization Problems

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