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arXiv · 2208.07085

On quantum factoring using noisy intermediate scale quantum computers

Vivian Phan·Arttu Pönni·Matti Raasakka·Ilkka Tittonen
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Abstract

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.

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Vivian Phan, Arttu Pönni, Matti Raasakka, Ilkka Tittonen. 2022-08-15. On quantum factoring using noisy intermediate scale quantum computers. https://arxiv.org/abs/2208.07085

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