On quantum factoring using noisy intermediate scale quantum computers

Understand

We study the performance and resource usage of the variational quantum factoring (VQF) algorithm for different instance sizes and optimization algorithms.

• Our simulations show better chance of finding the ground state when using VQE rather than QAOA for optimization.
• In gradient-based optimization we find that the time required for quantum circuit gradient estimation is a significant problem if VQF is to become competitive with classical factoring algorithms.
• Further, we compare entangled and non-entangled circuits in VQE optimization and fail to see significant evidence in favour of including entanglement in the VQE circuit.