Quantum pathways for charged track finding in high-energy collisions
File(s)frai-07-1339785.pdf (1.71 MB)
Published version
Author(s)
Brown, Christopher
Spannowsky, Michael
Tapper, Alexander
Williams, Simon
Xiotidis, Ioannis
Type
Journal Article
Abstract
In high-energy particle collisions, charged track finding is a complex yet crucial endeavor. We propose a quantum algorithm, specifically quantum template matching, to enhance the accuracy and efficiency of track finding. Abstracting the Quantum Amplitude Amplification routine by introducing a data register, and utilizing a novel oracle construction, allows data to be parsed to the circuit and matched with a hit-pattern template, without prior knowledge of the input data. Furthermore, we address the challenges posed by missing hit data, demonstrating the ability of the quantum template matching algorithm to successfully identify charged-particle tracks from hit patterns with missing hits. Our findings therefore propose quantum methodologies tailored for real-world applications and underline the potential of quantum computing in collider physics.
Date Issued
2024-05-30
Date Acceptance
2024-05-07
Citation
Frontiers in Artificial Intelligence, 2024, 7
ISSN
2624-8212
Publisher
Frontiers Media S.A.
Journal / Book Title
Frontiers in Artificial Intelligence
Volume
7
Copyright Statement
© 2024 Brown, Spannowsky, Tapper, Williams
and Xiotidis. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms
and Xiotidis. This is an open-access article
distributed under the terms of the Creative
Commons Attribution License (CC BY). The
use, distribution or reproduction in other
forums is permitted, provided the original
author(s) and the copyright owner(s) are
credited and that the original publication in
this journal is cited, in accordance with
accepted academic practice. No use,
distribution or reproduction is permitted
which does not comply with these terms
License URL
Identifier
https://www.frontiersin.org/articles/10.3389/frai.2024.1339785/full
Publication Status
Published
Article Number
1339785
Date Publish Online
2024-05-30