Preprint PUBDB-2023-01517

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Quantum algorithms for charged particle track reconstruction in the LUXE experiment

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2023

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Report No.: DESY-23-045; MIT-CTP/5481; arXiv:2304.01690

Abstract: The LUXE experiment is a new experiment in planning in Hamburg, which will study Quantum Electrodynamics at the strong-field frontier. LUXE intends to measure the positron production rate in this unprecedented regime by using, among others, a silicon tracking detector. The large number of expected positrons traversing the sensitive detector layers results in an extremely challenging combinatorial problem, which can become computationally expensive for classical computers. This paper investigates the potential future use of gate-based quantum computers for pattern recognition in track reconstruction. Approaches based on a quadratic unconstrained binary optimisation and a quantum graph neural network are investigated in classical simulations of quantum devices and compared with a classical track reconstruction algorithm. In addition, a proof-of-principle study is performed using quantum hardware.

Keyword(s): hardware, quantum ; positron, production ; computer, quantum ; track data analysis ; strong field ; quantum electrodynamics ; charged particle ; binary ; quantum algorithm ; silicon ; tracking detector ; optimization ; quantum device ; neural network


Note: 15 pages, 12 figures

Contributing Institute(s):
  1. Technol. zukünft. Teilchenph. Experim. (FTX)
  2. Centre f. Quantum Techno. a. Application (CQTA)
Research Program(s):
  1. 611 - Fundamental Particles and Forces (POF4-611) (POF4-611)
Experiment(s):
  1. Laser Und XFEL Experiment

Appears in the scientific report 2023
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Creative Commons Attribution CC BY 4.0 ; OpenAccess ; Published
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Quantum Algorithms for Charged Particle Track Reconstruction in the LUXE Experiment
Computing and software for big science 7(1), 14 () [10.1007/s41781-023-00109-6]  GO OpenAccess  Download fulltext Files  Download fulltextFulltext by arXiv.org BibTeX | EndNote: XML, Text | RIS


 Record created 2023-03-31, last modified 2024-01-21