Quantum variational optimization: The role of entanglement and problem hardness
Pablo Díez-Valle, Diego Porras, Juan José García‐Ripoll · Physical Review A · 2021
The authors investigate the ability of variational quantum algorithms to solve a combinatorial optimization problem, and demonstrate an advantage when the entanglement structure in the algorithm is chosen to mimic the structure of the problem. Notably, they find that when a certain cost function is used the depth of variational circuits is only moderately relevant, which suggests that new classical methods using product states may outperform existing quantum architectures.