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arxiv: 1512.07550 · v2 · submitted 2015-12-23 · 🪐 quant-ph · cs.DS

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Optimizing the Number of Gates in Quantum Search

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classification 🪐 quant-ph cs.DS
keywords gatessqrtnumberqueriesalgorithmotherconstantdatabase
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$ $In its usual form, Grover's quantum search algorithm uses $O(\sqrt{N})$ queries and $O(\sqrt{N} \log N)$ other elementary gates to find a solution in an $N$-bit database. Grover in 2002 showed how to reduce the number of other gates to $O(\sqrt{N}\log\log N)$ for the special case where the database has a unique solution, without significantly increasing the number of queries. We show how to reduce this further to $O(\sqrt{N}\log^{(r)} N)$ gates for any constant $r$, and sufficiently large $N$. This means that, on average, the gates between two queries barely touch more than a constant number of the $\log N$ qubits on which the algorithm acts. For a very large $N$ that is a power of 2, we can choose $r$ such that the algorithm uses essentially the minimal number $\frac{\pi}{4}\sqrt{N}$ of queries, and only $O(\sqrt{N}\log(\log^{\star} N))$ other gates.

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  1. Quantum Search without Global Diffusion

    quant-ph 2026-04 unverdicted novelty 7.0

    A recursive construction preserves O(sqrt(N)) quantum search complexity with local operations on tensor-decomposable partitions, eliminating the need for global diffusion via degeneracy in reflection angles.