%0 Electronic Article
%A Crippa, Arianna
%A Funcke, Lena
%A Hartung, Tobias
%A Heinemann, Beate
%A Jansen, Karl
%A Kropf, Annabel
%A Kuehn, Stefan
%A Meloni, Federico
%A Spataro, David
%A Tueysuez, Cenk
%A Yap, Yee Chinn
%T Track reconstruction at the LUXE experiment using quantum algorithms
%N DESY-22-113
%M PUBDB-2022-03238
%M DESY-22-113
%M arXiv:2210.13021
%M PROC-CTD2022-32
%M MIT-CTP/5476
%P 7
%D 2022
%Z 7 pages, 6 figures, Proceedings of the Connecting The Dots workshop 2022 (CTD2022)
%X LUXE (Laser Und XFEL Experiment) is a proposed experiment at DESY which will study Quantum Electrodynamics (QED) in the strong-field regime, where QED becomes non-perturbative. The measurement of the rate of electron-positron pair creation, an essential ingredient to study this regime, is enabled by the use of a silicon tracking detector. Precision tracking of positrons traversing the four layers of the tracking detector becomes very challenging at high laser intensities due to the high rates, which can be computationally expensive for classical computers. In this work, an update of our previous studies of the potential of quantum computers to reconstruct positron tracks is presented. The reconstruction problem is formulated in terms of a Quadratic Unconstrained Binary Optimisation (QUBO), and solved using simulated quantum computers and a hybrid quantum-classical algorithm, namely Variational Quantum Eigensolver (VQE). Different ansatz circuits and optimisers are studied. The results are discussed and compared with classical track reconstruction algorithms using Graph Neural Network and Combinatorial Kalman Filter.
%B Connecting the Dots Workshop
%C 31 May 2022 - 2 Jun 2022, New Jersey (USA)
Y2 31 May 2022 - 2 Jun 2022
M2 New Jersey, USA
%K computer, quantum (INSPIRE)
%K laser, yield (INSPIRE)
%K quantum electrodynamics (INSPIRE)
%K positron (INSPIRE)
%K track data analysis (INSPIRE)
%K tracking detector (INSPIRE)
%K strong field (INSPIRE)
%K binary (INSPIRE)
%K proposed experiment (INSPIRE)
%K hybrid (INSPIRE)
%K quantum algorithm (INSPIRE)
%K pixel (INSPIRE)
%K silicon (INSPIRE)
%K tracks (INSPIRE)
%K nonperturbative (INSPIRE)
%K electron positron (INSPIRE)
%K neural network (INSPIRE)
%K variational quantum eigensolver (INSPIRE)
%F PUB:(DE-HGF)25
%9 Preprint
%R 10.3204/PUBDB-2022-03238
%U https://bib-pubdb1.desy.de/record/479822