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Quantum pattern recognition algorithms for charged particle tracking
Author(s) -
H. M. Gray
Publication year - 2021
Publication title -
philosophical transactions - royal society. mathematical, physical and engineering sciences/philosophical transactions - royal society. mathematical, physical and engineering sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.074
H-Index - 169
eISSN - 1471-2962
pISSN - 1364-503X
DOI - 10.1098/rsta.2021.0103
Subject(s) - computer science , theme (computing) , charged particle , quantum computer , tracking (education) , field (mathematics) , quantum , key (lock) , physics , collider , particle physics , data science , quantum mechanics , mathematics , world wide web , ion , psychology , pedagogy , computer security , pure mathematics
High-energy physics is facing a daunting computing challenge with the large datasets expected from the upcoming High-Luminosity Large Hadron Collider in the next decade and even more so at future colliders. A key challenge in the reconstruction of events of simulated data and collision data is the pattern recognition algorithms used to determine the trajectories of charged particles. The field of quantum computing shows promise for transformative capabilities and is going through a cycle of rapid development and hence might provide a solution to this challenge. This article reviews current studies of quantum computers for charged particle pattern recognition in high-energy physics. This article is part of the theme issue ‘Quantum technologies in particle physics’.

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