QAOA

QAOA (Quantum Approximate Optimization Algorithm) is a hybrid quantum-classical algorithm introduced by Farhi, Goldstone, and Gutmann (2014) for solving combinatorial optimization problems like Max-Cut, traveling salesman, and graph partitioning. QAOA uses a parameterized circuit with p layers, alternating between a "problem unitary" (encoding the cost function) and a "mixer unitary" (exploring the solution space). A classical optimizer tunes the 2p parameters (γ, β) to maximize the expected solution quality. At p→∞, QAOA converges to the exact optimal solution. For practical NISQ devices, p=1 or p=2 layers are common. QAOA is considered one of the most promising near-term quantum algorithms. HLQuantum includes a built-in QAOA implementation.