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| Hauptseite > Publikationsdatenbank > Comparison of Factoring Algorithms on the D-Wave Quantum Annealer |
| Hauptseite > Publikationsdatenbank > Comparison of Factoring Algorithms on the D-Wave Quantum Annealer |
| Bachelor Thesis | FZJ-2024-05254 |
2024
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Please use a persistent id in citations: doi:10.34734/FZJ-2024-05254
Abstract: The goal of this work is to implement and assess different approaches for solving the factoring problem on quantum annealers. We identify three promising approaches that use custom and heuristic embedding and experimentally test their performance on the Advantage quantum annealer by D-Wave Systems Inc. To reduce terms of higher order than quadratic, we formulate an approach that takes into account the coefficient of the term to be reduced, and we show experimentally that it produces valid models for smaller problem sizes. We evaluate the impact of using individual per-qubit offsets and find that this feature can significantly improve the success frequencies for some problem sizes. For others, applying offsets can lead to a decrease in success frequencies.We find that all three examined factoring approaches exhibit a scaling with problem size that is qualitatively similar to random drawing. Generally, all methods fail to find solutions for larger problem sizes. On average, the success frequencies are only $10-100$ times higher than randomly drawing each bit of $p$ and $q$. However, the approach with custom embedding is able to find ground states even for larger problem sizes, indicating a problem formulation that is well suited for the quantum annealer.
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