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PUBDB-2023-06467

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Track reconstruction of charged particles using a 4D quantum algorithm

Meloni, F.DESY* ; Spataro, D. (Corresponding author)DESY* ; Yap, Y. C.DESY*

2023
SISSA Trieste

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Please use a persistent id in citations: doi:10.22323/1.449.0560  doi:10.3204/PUBDB-2023-06467

Report No.: DESY-23-219

Abstract: Particle track reconstruction plays a crucial role in the exploration of new physical phenomena,particularly when rare signal tracks are obscured by a significant background. In muon colliderswhere beam muons interacting with the detector produce secondary and tertiary background par-ticles, track reconstruction can be computationally intensive due to the large number of detectorhits. The formulation of the reconstruction task as Quadratic Unconstrained Binary Optimisa-tion (QUBO) enables the use of quantum computers, which are believed to offer an advantageover classical computers in such optimisation scenarios. The QUBO parameters are determinedby combining spatial and temporal information from detector hits, resulting in a 4D quantumalgorithm. To demonstrate the effectiveness of this approach, the quantum algorithm is usedto reconstruct signal tracks from samples consisting of Monte Carlo simulated charged particlesoverlaid with background hits for a Muon Collider tracking detector. We will present the obtainedreconstruction performance and discuss possible paths for further improvements.

Keyword(s): muon: beam ; computer: quantum ; background ; quantum algorithm ; track data analysis ; optimization ; Monte Carlo ; charged particle ; performance ; tracking detector

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Contributing Institute(s):

1. Technol. zukünft. Teilchenph. Experim. (FTX)

Research Program(s):

1. 622 - Detector Technologies and Systems (POF4-622) (POF4-622)
2. MuCol - A Design Study for a Muon Collider complex at 10+ TeV center of mass (101094300) (101094300)

Experiment(s):

1. (Planned International Muon Collider Facility)

Appears in the scientific report 2023

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Database coverage:
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