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Similarity hashing for charged particle tracking

The tracking of charged particles produced in high energy collisions is particularly challenging. The combinatorics approach currently used to track tens of thousands of particles becomes inadequate as the number of simultaneous collisions increase at the High Luminosity Large Hadron Collider (HLLHC...

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Detalles Bibliográficos
Autores principales: Amrouche, Sabrina, Golling, Tobias, Kiehn, Moritz, Plant, Claudia, Salzburger, Andreas
Lenguaje:eng
Publicado: 2019
Materias:
Acceso en línea:https://dx.doi.org/10.1109/BigData47090.2019.9006316
http://cds.cern.ch/record/2827225
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author Amrouche, Sabrina
Golling, Tobias
Kiehn, Moritz
Plant, Claudia
Salzburger, Andreas
author_facet Amrouche, Sabrina
Golling, Tobias
Kiehn, Moritz
Plant, Claudia
Salzburger, Andreas
author_sort Amrouche, Sabrina
collection CERN
description The tracking of charged particles produced in high energy collisions is particularly challenging. The combinatorics approach currently used to track tens of thousands of particles becomes inadequate as the number of simultaneous collisions increase at the High Luminosity Large Hadron Collider (HLLHC). We propose to reduce the complexity of tracking in such dense environments with the use of similarity hashing. We use hashing techniques to separate the detector space into buckets. The particle purity of these buckets is increased using Approximate Nearest Neighbors search. The bucket size is sufficiently small to significantly reduce the complexity of track reconstruction within the buckets. We demonstrate the use of the proposed approach on a public dataset of simulated collisions. The performance evaluation shows a significant speed improvement over the current technique and a further understanding of charged particles structure.
id cern-2827225
institution Organización Europea para la Investigación Nuclear
language eng
publishDate 2019
record_format invenio
spelling cern-28272252022-09-16T21:13:04Zdoi:10.1109/BigData47090.2019.9006316http://cds.cern.ch/record/2827225engAmrouche, SabrinaGolling, TobiasKiehn, MoritzPlant, ClaudiaSalzburger, AndreasSimilarity hashing for charged particle trackingComputing and ComputersParticle Physics - ExperimentThe tracking of charged particles produced in high energy collisions is particularly challenging. The combinatorics approach currently used to track tens of thousands of particles becomes inadequate as the number of simultaneous collisions increase at the High Luminosity Large Hadron Collider (HLLHC). We propose to reduce the complexity of tracking in such dense environments with the use of similarity hashing. We use hashing techniques to separate the detector space into buckets. The particle purity of these buckets is increased using Approximate Nearest Neighbors search. The bucket size is sufficiently small to significantly reduce the complexity of track reconstruction within the buckets. We demonstrate the use of the proposed approach on a public dataset of simulated collisions. The performance evaluation shows a significant speed improvement over the current technique and a further understanding of charged particles structure.oai:cds.cern.ch:28272252019
spellingShingle Computing and Computers
Particle Physics - Experiment
Amrouche, Sabrina
Golling, Tobias
Kiehn, Moritz
Plant, Claudia
Salzburger, Andreas
Similarity hashing for charged particle tracking
title Similarity hashing for charged particle tracking
title_full Similarity hashing for charged particle tracking
title_fullStr Similarity hashing for charged particle tracking
title_full_unstemmed Similarity hashing for charged particle tracking
title_short Similarity hashing for charged particle tracking
title_sort similarity hashing for charged particle tracking
topic Computing and Computers
Particle Physics - Experiment
url https://dx.doi.org/10.1109/BigData47090.2019.9006316
http://cds.cern.ch/record/2827225
work_keys_str_mv AT amrouchesabrina similarityhashingforchargedparticletracking
AT gollingtobias similarityhashingforchargedparticletracking
AT kiehnmoritz similarityhashingforchargedparticletracking
AT plantclaudia similarityhashingforchargedparticletracking
AT salzburgerandreas similarityhashingforchargedparticletracking