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Advances in intelligent systems and computing

Quantum Computer Search Algorithms: Can We Outperform the Classical Search Algorithms?

Avery M. Leider, Sadida Siddiqui, Daniel A. Sabol, Charles C. Tappert

Published Oct 12, 2019• 5 citations
Publisher
DOI
10.1007/978-3-030-32520-6_34

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A groundbreaking advancement in computing theory, quantum search algorithms leverage quantum mechanics to outperform their classical counterparts in solving search issues. With a focus on their theoretical underpinnings, practical applications, and performance in a variety of computational contexts, this systematic review carefully investigates the evolution, progress, and current state of quantum search algorithms. We present a thorough analysis of significant algorithms, such as Grover’s search algorithm, together with recent developments in quantum optimization and quantum-enhanced search techniques. We also go over the challenges with quantum error correction, scalability, and hardware constraints that prevent the broad application of quantum search techniques.
We investigate the problem of quantum searching on a noisy quantum computer. Taking a fault-ignorant approach, we analyze quantum algorithms that solve the task for various different noise strengths, which are possibly unknown beforehand. We prove lower bounds on the runtime of such algorithms and thereby find that the quadratic speedup is necessarily lost (in our noise models). However, for low but constant noise levels the algorithms we provide (based on Groverʼs algorithm) still outperform the best noiseless classical search algorithm.