Search Menu
DOE PAGES title logo U.S. Department of Energy
Office of Scientific and Technical Information
Search Scholarly Publications

Title: Charged particle tracking with quantum annealing optimization

Abstract

Abstract At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.

Authors:
ORCiD logo; ; ; ; ; ;
Publication Date:
Research Org.:
Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States)
Sponsoring Org.:
USDOE Office of Science (SC), High Energy Physics (HEP)
OSTI Identifier:
1828631
Alternate Identifier(s):
OSTI ID: 1599326
Report Number(s):
FERMILAB-PUB-19-670-PPD; arXiv:1908.04475
Journal ID: ISSN 2524-4906; 27; PII: 54
Grant/Contract Number:  
AC02-07CH11359
Resource Type:
Published Article
Journal Name:
Quantum Machine Intelligence
Additional Journal Information:
Journal Name: Quantum Machine Intelligence Journal Volume: 3 Journal Issue: 2; Journal ID: ISSN 2524-4906
Publisher:
Springer Science + Business Media
Country of Publication:
Switzerland
Language:
English
Subject:
97 MATHEMATICS AND COMPUTING; Quantum annealing; High energy physics; Optimization; Pattern recognition; Adiabatic quantum computing

Citation Formats

Zlokapa, Alexander, Anand, Abhishek, Vlimant, Jean-Roch, Duarte, Javier M., Job, Joshua, Lidar, Daniel, and Spiropulu, Maria. Charged particle tracking with quantum annealing optimization. Switzerland: N. p., 2021. Web. doi:10.1007/s42484-021-00054-w.
Copy to clipboard
Zlokapa, Alexander, Anand, Abhishek, Vlimant, Jean-Roch, Duarte, Javier M., Job, Joshua, Lidar, Daniel, & Spiropulu, Maria. Charged particle tracking with quantum annealing optimization. Switzerland. https://doi.org/10.1007/s42484-021-00054-w
Copy to clipboard
Zlokapa, Alexander, Anand, Abhishek, Vlimant, Jean-Roch, Duarte, Javier M., Job, Joshua, Lidar, Daniel, and Spiropulu, Maria. Tue . "Charged particle tracking with quantum annealing optimization". Switzerland. https://doi.org/10.1007/s42484-021-00054-w.
Copy to clipboard
@article{osti_1828631,
title = {Charged particle tracking with quantum annealing optimization},
author = {Zlokapa, Alexander and Anand, Abhishek and Vlimant, Jean-Roch and Duarte, Javier M. and Job, Joshua and Lidar, Daniel and Spiropulu, Maria},
abstractNote = {Abstract At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for physics analysis will need to be upgraded to scale with track density. Quantum annealing has shown promise in its ability to solve combinatorial optimization problems amidst an ongoing effort to establish evidence of a quantum speedup. As a step towards exploiting such potential speedup, we investigate a track reconstruction approach by adapting the existing geometric Denby-Peterson (Hopfield) network method to the quantum annealing framework for HL-LHC conditions. We develop additional techniques to embed the problem onto existing and near-term quantum annealing hardware. Results using simulated annealing and quantum annealing with the D-Wave 2X system on the TrackML open dataset are presented, demonstrating the successful application of a quantum annealing algorithm to the track reconstruction challenge. We find that combinatorial optimization problems can effectively reconstruct tracks, suggesting possible applications for fast hardware-specific implementations at the HL-LHC while leaving open the possibility of a quantum speedup for tracking.},
doi = {10.1007/s42484-021-00054-w},
journal = {Quantum Machine Intelligence},
number = 2,
volume = 3,
place = {Switzerland},
year = {2021},
month = {11}
}
Copy to clipboard
Journal Article:
Free Publicly Available Full Text
Publisher's Version of Record
https://doi.org/10.1007/s42484-021-00054-w
Copyright Statement
Other availability
Search WorldCat Search WorldCat to find libraries that may hold this journal
Save / Share:
Export Metadata
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.

Works referenced in this record:

Track finding with neural networks
journal, July 1989

  • Peterson, Carsten
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 279, Issue 3
  • DOI: 10.1016/0168-9002(89)91300-4

Mapping Constrained Optimization Problems to Quantum Annealing with Application to Fault Diagnosis
journal, July 2016

Quantum annealing versus classical machine learning applied to a simplified computational biology problem
journal, February 2018

Fast track finding with neural networks
journal, April 1991

Neural networks and cellular automata in experimental high energy physics
journal, June 1988

Parallelized Kalman-Filter-Based Reconstruction of Particle Tracks on Many-Core Architectures
journal, September 2018

Architectural Considerations in the Design of a Superconducting Quantum Annealing Processor
journal, August 2014

  • Bunyk, P. I.; Hoskinson, Emile M.; Johnson, Mark W.
  • IEEE Transactions on Applied Superconductivity, Vol. 24, Issue 4
  • DOI: 10.1109/TASC.2014.2318294

Quantum Optimization of Fully Connected Spin Glasses
journal, September 2015

A Roadmap for HEP Software and Computing R&D for the 2020s
journal, March 2019

  • Albrecht, Johannes; Alves, Antonio Augusto; Amadio, Guilherme
  • Computing and Software for Big Science, Vol. 3, Issue 1
  • DOI: 10.1007/s41781-018-0018-8

Test-driving 1000 qubits
journal, June 2018

Ising formulations of many NP problems
journal, January 2014

Parallel track reconstruction in CMS using the cellular automaton approach
journal, June 2014

Evidence for quantum annealing with more than one hundred qubits
journal, February 2014

  • Boixo, Sergio; Rønnow, Troels F.; Isakov, Sergei V.
  • Nature Physics, Vol. 10, Issue 3
  • DOI: 10.1038/nphys2900

Identification of b-quark jets with the CMS experiment
journal, April 2013

Track fitting with multiple scattering: A new method
journal, August 1984

Quantum adiabatic machine learning by zooming into a region of the energy surface
journal, December 2020

Fast Hough-transform track reconstruction for the ALICE TPC
journal, October 2006

  • Cheshkov, C.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 566, Issue 1
  • DOI: 10.1016/j.nima.2006.05.036

Minor-embedding in adiabatic quantum computation: II. Minor-universal graph design
journal, October 2010

Adiabatic quantum programming: minor embedding with hard faults
journal, November 2013

  • Klymko, Christine; Sullivan, Blair D.; Humble, Travis S.
  • Quantum Information Processing, Vol. 13, Issue 3
  • DOI: 10.1007/s11128-013-0683-9

Performance of the CMS missing transverse momentum reconstruction in pp data at √ s = 8 TeV
journal, February 2015

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV
journal, May 2018

Tracking by a modified rotor model of neural network
journal, April 1994

Quantum annealing in the transverse Ising model
journal, November 1998

Defining and detecting quantum speedup
journal, June 2014

Neural tracking in the ALICE Inner Tracking System
journal, November 2004

  • Pulvirenti, A.; Badalà, A.; Barbera, R.
  • Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment, Vol. 533, Issue 3
  • DOI: 10.1016/j.nima.2004.06.176

A coherent Ising machine for 2000-node optimization problems
journal, October 2016

Description and performance of track and primary-vertex reconstruction with the CMS tracker
journal, October 2014

Optimization by Simulated Annealing
journal, May 1983

Solving a Higgs optimization problem with quantum annealing for machine learning
journal, October 2017

  • Mott, Alex; Job, Joshua; Vlimant, Jean-Roch
  • Nature, Vol. 550, Issue 7676
  • DOI: 10.1038/nature24047

Track and vertex reconstruction: From classical to adaptive methods
journal, May 2010

Beam-induced and cosmic-ray backgrounds observed in the ATLAS detector during the LHC 2012 proton-proton running period
journal, May 2016

Minor-embedding in adiabatic quantum computation: I. The parameter setting problem
journal, September 2008

    Sort by:
    [ × clear filter / sort ]

    Similar Records in DOE PAGES and OSTI.GOV collections: