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Journal Article | PUBDB-2023-07901 |
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2023
Springer International Publishing
Cham, Switzerland
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Please use a persistent id in citations: doi:10.1007/s41781-023-00109-6 doi:10.3204/PUBDB-2023-07901
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 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 ; track data analysis ; strong field ; charged particle ; quantum electrodynamics ; binary ; quantum algorithm ; silicon ; tracking detector ; optimization ; quantum device ; neural network ; Quantum algorithms ; Pattern recognition ; HEP particle tracking ; Strong-field QED experiment
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Quantum algorithms for charged particle track reconstruction in the LUXE experiment
[10.3204/PUBDB-2023-01517]
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