Large-Scale Simulation of Shor's Quantum Factoring Algorithm
Dennis Willsch, Madita Willsch, Fengping Jin, Hans De Raedt, Kristel, Michielsen

TL;DR
This paper demonstrates large-scale classical simulation of Shor's quantum factoring algorithm on GPU supercomputers, revealing high success probabilities, effective post-processing, and resilience to errors, enabling factoring of large semiprimes beyond current quantum hardware capabilities.
Contribution
It introduces a GPU-based supercomputing approach to simulate Shor's algorithm for large numbers, surpassing current quantum hardware limitations and analyzing error resilience.
Findings
Average success probability above 50% due to lucky cases
Post-processing can nearly guarantee success in a single run
Largest factored semiprime is 549755813701 (712321 * 771781)
Abstract
Shor's factoring algorithm is one of the most anticipated applications of quantum computing. However, the limited capabilities of today's quantum computers only permit a study of Shor's algorithm for very small numbers. Here we show how large GPU-based supercomputers can be used to assess the performance of Shor's algorithm for numbers that are out of reach for current and near-term quantum hardware. First, we study Shor's original factoring algorithm. While theoretical bounds suggest success probabilities of only 3-4 %, we find average success probabilities above 50 %, due to a high frequency of "lucky" cases, defined as successful factorizations despite unmet sufficient conditions. Second, we investigate a powerful post-processing procedure, by which the success probability can be brought arbitrarily close to one, with only a single run of Shor's quantum algorithm. Finally, we study…
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Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Quantum Information and Cryptography · Cryptography and Data Security
