Quantum divide and conquer

Fuente: arXiv
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Auteurs principaux: Childs, Andrew M., Kothari, Robin, Kovacs-Deak, Matt, Sundaram, Aarthi, Wang, Daochen
Format: Preprint
Publié: 2022
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author Childs, Andrew M.
Kothari, Robin
Kovacs-Deak, Matt
Sundaram, Aarthi
Wang, Daochen
author_facet Childs, Andrew M.
Kothari, Robin
Kovacs-Deak, Matt
Sundaram, Aarthi
Wang, Daochen
contents The divide-and-conquer framework, used extensively in classical algorithm design, recursively breaks a problem of size $n$ into smaller subproblems (say, $a$ copies of size $n/b$ each), along with some auxiliary work of cost $C^{\textrm{aux}}(n)$, to give a recurrence relation $$C(n) \leq a \, C(n/b) + C^{\textrm{aux}}(n)$$ for the classical complexity $C(n)$. We describe a quantum divide-and-conquer framework that, in certain cases, yields an analogous recurrence relation $$C_Q(n) \leq \sqrt{a} \, C_Q(n/b) + O(C^{\textrm{aux}}_Q(n))$$ that characterizes the quantum query complexity. We apply this framework to obtain near-optimal quantum query complexities for various string problems, such as (i) recognizing regular languages; (ii) decision versions of String Rotation and String Suffix; and natural parameterized versions of (iii) Longest Increasing Subsequence and (iv) Longest Common Subsequence.
format Preprint
id arxiv_https___arxiv_org_abs_2210_06419
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Quantum divide and conquer
Childs, Andrew M.
Kothari, Robin
Kovacs-Deak, Matt
Sundaram, Aarthi
Wang, Daochen
Quantum Physics
Data Structures and Algorithms
The divide-and-conquer framework, used extensively in classical algorithm design, recursively breaks a problem of size $n$ into smaller subproblems (say, $a$ copies of size $n/b$ each), along with some auxiliary work of cost $C^{\textrm{aux}}(n)$, to give a recurrence relation $$C(n) \leq a \, C(n/b) + C^{\textrm{aux}}(n)$$ for the classical complexity $C(n)$. We describe a quantum divide-and-conquer framework that, in certain cases, yields an analogous recurrence relation $$C_Q(n) \leq \sqrt{a} \, C_Q(n/b) + O(C^{\textrm{aux}}_Q(n))$$ that characterizes the quantum query complexity. We apply this framework to obtain near-optimal quantum query complexities for various string problems, such as (i) recognizing regular languages; (ii) decision versions of String Rotation and String Suffix; and natural parameterized versions of (iii) Longest Increasing Subsequence and (iv) Longest Common Subsequence.
title Quantum divide and conquer
topic Quantum Physics
Data Structures and Algorithms
url https://arxiv.org/abs/2210.06419