Trainability Barriers in Low-Depth QAOA Landscapes

Understand

The Quantum Alternating Operator Ansatz (QAOA) is a prominent variational quantum algorithm for solving combinatorial optimization problems.

• Its effectiveness depends on identifying input parameters that yield high-quality solutions.
• However, understanding the complexity of training QAOA remains an under-explored area.
• Previous results have given analytical performance guarantees for a small, fixed number of parameters.