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Optimizing the Number of Gates in Quantum Search

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 Publication date 2015
and research's language is English




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$ $In its usual form, Grovers 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 $O(sqrt{N}loglog N)$ 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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