A Method to Compute QAOA Fixed Angles
Andrey Yu. Chernyavskiy, B. I. Bantysh · Russian Microelectronics · 2023
Abstract QAOA (Quantum Approximate Optimization Algorithms) is one of the most promising algorithms of Noisy Intermediate Scale Quantum (NISQ) era. The standard approach to QAOA involves the use of a hybrid quantum-classical optimization, although this approach was not considered as the main one in the original paper on QAOA. Recently, a new approach has emerged based on the hypothesis that optimal circuit parameters (angles) are close for a wide class of problems. However, the search for fixed angles itself remains a challenge with different approaches. We propose one specific method based on the use of a fixed training set and the special metric associated with increasing the probability of a correct answer. We carry out the analysis of the proposed method performance on the unweighted Max-Cut problems and random weighted QUBO (Quadratic Unconstrained Binary Optimization) problems of the special type.