Performance of Quantum Approximate Optimization with Quantum Error Detection

Understand

Quantum algorithms must be scaled up to tackle real-world applications.

• Doing so requires overcoming the noise present on today's hardware.
• The quantum approximate optimization algorithm (QAOA) is a promising candidate for scaling up, due to its modest resource requirements and documented asymptotic speedup over state-of-the-art classical algorithms for some problems.
• However, achieving better-than-classical performance with QAOA is believed to require fault tolerance.