Heidelberg 2022 – scientific programme
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T: Fachverband Teilchenphysik
T 79: Data Analysis, Information Technology and Artificial Intelligence 4
T 79.9: Talk
Wednesday, March 23, 2022, 18:15–18:30, T-H38
Benchmarking Variational Quantum Algorithms for track reconstruction at LUXE — Arianna Crippa1, Lena Funcke3, Tobias Hartung4, Beate Heinemann1,2, Karl Jansen1, •Annabel Kropf1, Stefan Kühn5, Federico Meloni1, David Spataro1, Cenk Tüysüz1, and Yee Chinn Yap1 — 1Deutsches Elektronen-Synchrotron DESY — 2Albert-Ludwigs-Universität Freiburg — 3Massachusetts Institute of Technology — 4University of Bath — 5CaSToRC, The Cyprus Institute
The primary aim of the recently proposed LUXE experiment is to investigate the transition into the non-perturbative regime of Quantum Electrodynamics. For this, the interaction of photons with electrons, or photons with photons is measured at field strengths where couplings to charges become non-perturbative. In these interactions, up to 106 positrons are produced that then impinge on a four-layered silicon pixel tracking detector. The accurate reconstruction of the positrons’ trajectories from a set of hits is a combinatorial problem challenging for a classical computer to solve. For LUXE, a novel approach is explored that expresses pattern recognition as a quadratic unconstrained binary optimisation, allowing the algorithm to be mapped onto a quantum computer. Variational quantum algorithms provide a promising approach to solve combinatorial optimisation problems on noisy quantum devices. Here, we benchmark the accuracy of two such algorithms, the Variational Quantum Eigensolver and the Quantum Approximate Optimisation Algorithm, against classical tracking using data from an idealised LUXE detector set-up.