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Bibliographic Details
Main Author: Rotello, Caleb
Format: Preprint
Published: 2024
Subjects:
Online Access:https://arxiv.org/abs/2412.00567
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author Rotello, Caleb
author_facet Rotello, Caleb
contents Quantum amplitude amplification and estimation have shown quadratic speedups to unstructured search and estimation tasks. We show that a coherent combination of these quantum algorithms also provides a quadratic speedup to calculating the expectation value of a random-exist quantified oracle. In this problem, Nature makes a decision randomly, i.e. chooses a bitstring according to some probability distribution, and a player has a chance to react by finding a complementary bitstring such that an black-box oracle evaluates to $1$ (or True). Our task is to approximate the probability that the player has a valid reaction to Nature's initial decision. We compare the quantum algorithm to the average-case performance of Monte-Carlo integration over brute-force search, which is, under reasonable assumptions, the best performing classical algorithm. We find the performance separation depends on some problem parameters, and show a regime where the canonical quadratic speedup exists.
format Preprint
id arxiv_https___arxiv_org_abs_2412_00567
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Quantum algorithm for approximating the expected value of a random-exist quantified oracle
Rotello, Caleb
Quantum Physics
Data Structures and Algorithms
Quantum amplitude amplification and estimation have shown quadratic speedups to unstructured search and estimation tasks. We show that a coherent combination of these quantum algorithms also provides a quadratic speedup to calculating the expectation value of a random-exist quantified oracle. In this problem, Nature makes a decision randomly, i.e. chooses a bitstring according to some probability distribution, and a player has a chance to react by finding a complementary bitstring such that an black-box oracle evaluates to $1$ (or True). Our task is to approximate the probability that the player has a valid reaction to Nature's initial decision. We compare the quantum algorithm to the average-case performance of Monte-Carlo integration over brute-force search, which is, under reasonable assumptions, the best performing classical algorithm. We find the performance separation depends on some problem parameters, and show a regime where the canonical quadratic speedup exists.
title Quantum algorithm for approximating the expected value of a random-exist quantified oracle
topic Quantum Physics
Data Structures and Algorithms
url https://arxiv.org/abs/2412.00567