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Quantum Approximate Counting with Nonadaptive Grover Iterations

  • DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
  • Schloss Dagstuhl – Leibniz Center for Informatics
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Abstract

Approximate Counting refers to the problem where we are given query access to a function f : [N] → {0,1}, and we wish to estimate K = #{x : f(x) = 1} to within a factor of 1+ε (with high probability), while minimizing the number of queries. In the quantum setting, Approximate Counting can be done with O(min (√{N/ε}, √{N/K} / ε) queries. It has recently been shown that this can be achieved by a simple algorithm that only uses "Grover iterations"; however the algorithm performs these iterations adaptively. Motivated by concerns of computational simplicity, we consider algorithms that use Grover iterations with limited adaptivity. We show that algorithms using only nonadaptive Grover iterations can achieve O(√{N/ε}) query complexity, which is tight.

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Publication details

DOI
10.4230/lipics.stacs.2021.59
OpenAlex
W3137615165
Document type
article
Language
EN
Source
DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)
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