Speaker
Description
Future collider experiments, such as the upcoming high luminosity phase of the LHC, are expected to be extremely data-rich. This anticipates a significant demand for innovative track reconstruction techniques to more efficiently reconstruct particle trajectories. Specifically, LUXE (Laser Und XFEL Experiment) at DESY, a proposed experiment to investigate the transition into strong-field QED, presents an ideal platform for developing and testing novel techniques, due to the large range of generated positrons and detector occupancies of up to 100 hits/mm2 for the initial phase.
To reconstruct positron tracks from the four-layered Silicon pixel detector used in LUXE, we formulate the track reconstruction as a quadratic unconstrained binary optimisation (QUBO) problem. This formulation allows the problem to be solved with either a gate-based quantum computer or a quantum annealer. In this talk, the simulated performance of these methods is benchmarked against the classical track reconstruction technique of using a Combinatorial Kalman Filter. Additionally, the talk will include a discussion on the methodologies for transforming pattern recognition problems, like track reconstruction, into effective QUBO problems
