Lecture

Quantum Approximation: Optimization Algorithm

Description

This lecture covers the Quantum Approximate Optimization Algorithm (QAOA) and its application in quantum optimization. The instructor discusses the trade-off between quantum resources and success probability in factoring integers using a superconducting quantum processor. Various noise sources and error sources are empirically analyzed, revealing the impact of residual ZZ-coupling between qubits. The lecture also explores the optimal number of circuit layers to maximize success probability.

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