Quantum algorithms for jet clustering
Name
PhysRevD.101.094015.pdf
Description
Published version
Size
848.19 KB
Format
Adobe PDF
Checksum (MD5)
fc8c6a39479bffb99cbaba59a64ecd93
Author(s)
Wei, Annie Y.
Naik, Preksha
Harrow, Aram W.
Thaler, Jesse
Date Issued
May 2020
Journal
Physical Review D
Publisher
American Physical Society (APS)
Citation
Wei, Annie Y. et al. “Quantum algorithms for jet clustering.” Physical Review D, 101, 9 (May 2020): 094015 © 2020 The Author(s)
Version
Final published version
Abstract
Identifying jets formed in high-energy particle collisions requires solving optimization problems over potentially large numbers of final-state particles. In this work, we consider the possibility of using quantum computers to speed up jet clustering algorithms. Focusing on the case of electron-positron collisions, we consider a well-known event shape called thrust whose optimum corresponds to the most jetlike separating plane among a set of particles, thereby defining two hemisphere jets. We show how to formulate thrust both as a quantum annealing problem and as a Grover search problem. A key component of our analysis is the consideration of realistic models for interfacing classical data with a quantum algorithm. With a sequential computing model, we show how to speed up the well-known O(N3) classical algorithm to an O(N2) quantum algorithm, including the O(N) overhead of loading classical data from N final-state particles. Along the way, we also identify a way to speed up the classical algorithm to O(N2logN) using a sorting strategy inspired by the siscone jet algorithm, which has no natural quantum counterpart. With a parallel computing model, we achieve O(NlogN) scaling in both the classical and quantum cases. Finally, we consider the generalization of these quantum methods to other jet algorithms more closely related to those used for proton-proton collisions at the Large Hadron Collider.
MIT Department
Massachusetts Institute of Technology. Center for Theoretical Physics
Massachusetts Institute of Technology. Department of Physics
Terms of Use
Creative Commons Attribution 4.0 International license
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1103/PHYSREVD.101.094015
