https://doi.org/10.1051/epjconf/202024510006
Quantum annealing algorithms for track pattern recognition
1
International Center for Elementary Particle Physics (ICEPP), The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
2
Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA
3
Department of Physics, University of California, Berkeley, CA 94720, USA
4
Haute ecole d’Ingénierie et d’Architecture de Fribourg, Boulevard de Pérolles 80, 1705 Fribourg, Switzerland
* e-mail: masahiko.saito@cern.ch
Published online: 16 November 2020
The High-Luminosity Large Hadron Collider (HL-LHC) starts from 2027 to extend the physics discovery potential at the energy frontier. The HL-LHC produces experimental data with a much higher luminosity, requiring a large amount of computing resources mainly due to the complexity of a track pattern recognition algorithm. Quantum annealing might be a solution for an efficient track pattern recognition in the HL-LHC environment. We demonstrated to perform the track pattern recognition by using the D-Wave annealing machine and the Fujitsu Digital Annealer. The tracking efficiency and purity for the D-Wave quantum annealer are comparable with those for a classical simulated annealing at a low pileup condition, while a drop in performance is found at a high pileup condition, corresponding to the HL-LHC pileup environment. The tracking efficiency and purity for the Fujitsu Digital Annealer are nearly the same as the classical simulated annealing.
© The Authors, published by EDP Sciences, 2020
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
