A quantum algorithm for track reconstruction in the LHCb vertex detector

• Published in: Journal of instrumentation Vol. 18; no. 11; p. P11028
• Main Authors: Nicotra, D., Lucio Martinez, M., de Vries, J.A., Merk, M., Driessens, K., Westra, R.L., Dibenedetto, D., Cámpora Pérez, D.H.
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.11.2023
• Subjects: Algorithms; Ising model; Luminosity; Particle tracking; Particle tracking detectors; Pattern recognition, cluster finding, calibration and fitting methods; Real time; Reconstruction
• ISSN: 1748-0221; 1748-0221
• DOI: 10.1088/1748-0221/18/11/P11028

Abstract High-energy physics is facing increasingly demanding computational challenges in real-time event reconstruction for the near-future high-luminosity era. Using the LHCb vertex detector as a use case, we explore a new algorithm for particle track reconstruction based on the minimisation of an Ising-like Hamiltonian with a linear algebra approach. The use of a classical matrix inversion technique results in tracking performance similar to the current state-of-the-art but with worse scaling complexity in time. To solve this problem, we also present an implementation as a quantum algorithm, using the Harrow-Hassadim-Lloyd (HHL) algorithm: this approach can potentially provide an exponential speedup as a function of the number of input hits over its classical counterpart, in spite of limitations due to the well-known HHL Hamiltonian simulation and readout problems. The findings presented in this paper shed light on the potential of leveraging quantum computing for real-time particle track reconstruction in high-energy physics.