Quantum Amplitude Amplification and Estimation

Gilles Brassard, Peter Høyer, Michele Mosca, Alain Tapp · 2002 · AMS Contemporary Mathematics 305:53-74

| 编号 QAPP002 | 主题 应用 | 链接 arXiv:quant-ph/0005055 |

摘要

摘要保留原文(英文)

摘要取自 arXiv / 出版方元数据,未作翻译,以保证与原文一致。

Consider a Boolean function that partitions set between its good and bad elements, where is good if and bad otherwise. Consider also a quantum algorithm such that is a quantum superposition of the elements of , and let denote the probability that a good element is produced if is measured. If we repeat the process of running , measuring the output, and using to check the validity of the result, we shall expect to repeat times on the average before a solution is found. Amplitude amplification is a process that allows to find a good after an expected number of applications of and its inverse which is proportional to , assuming algorithm makes no measurements. This is a generalization of Grover’s searching algorithm in which was restricted to producing an equal superposition of all members of and we had a promise that a single existed such that . Our algorithm works whether or not the value of is known ahead of time. In case the value of is known, we can find a good after a number of applications of and its inverse which is proportional to even in the worst case. We show that this quadratic speedup can also be obtained for a large family of search problems for which good classical heuristics exist. Finally, as our main result, we combine ideas from Grover’s and Shor’s quantum algorithms to perform amplitude estimation, a process that allows to estimate the value of . We apply amplitude estimation to the problem of approximate counting, in which we wish to estimate the number of such that . We obtain optimal quantum algorithms in a variety of settings.

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