Quantum Approximate Optimization Algorithm

This lecture covers the Quantum Approximate Optimization Algorithm (QAOA), discussing physically inspired unitary coupled cluster ansatz, hardware-efficient ansatz, variational quantum eigensolver (VQE), and the variational principle. It also explores the concept of parametrized circuits and the approximation of Hamiltonian. The lecture delves into the narrative of quantum adiabatic optimization and its relation to the ground state of Hamiltonian, emphasizing the variational principle and the equality conditions. The content progresses to the discussion of the traveling salesman problem and the shortest path, providing insights into NP-completeness and the optimal route finding. The lecture concludes with the exploration of classical algorithms and their application to optimization problems.