Particle Track Reconstruction with Quantum Algorithms

Date

2020-11-16

Author

Demirköz, Melahat Bilge
Carminati, Federico
Dobos, Daniel
Fracas, Fabio
Novotny, Kristiane
Potamianos, Karolos
Vallecorsa, Sofia
Vlimant, Jean-Roch

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

160
views

0
downloads

Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increase in the number of simultaneous collisions at the HL-LHC and the resulting high detector occupancy will make track reconstruction algorithms extremely demanding in terms of time and computing resources. The increase in number of hits will increase the complexity of track reconstruction algorithms. In addition, the ambiguity in assigning hits to particle tracks will be increased due to the finite resolution of the detector and the physical "closeness" of the hits. Thus, the reconstruction of charged particle tracks will be a major challenge to the correct interpretation of the HL-LHC data. Most methods currently in use are based on Kalman filters which are shown to be robust and to provide good physics performance. However, they are expected to scale worse than quadratically. Designing an algorithm capable of reducing the combinatorial background at the hit level, would provide a much "cleaner" initial seed to the Kalman filter, strongly reducing the total processing time. One of the salient features of Quantum Computers is the ability to evaluate a very large number of states simultaneously, making them an ideal instrument for searches in a large parameter space. In fact, different R&D initiatives are exploring how Quantum Tracking Algorithms could leverage such capabilities. In this paper, we present our work on the implementation of a quantum-based track finding algorithm aimed at reducing combinatorial background during the initial seeding stage. We use the publicly available dataset designed for the kaggle TrackML challenge.

URI

http://dx.doi.org/10.1051/epjconf/202024509013
https://hdl.handle.net/11511/92946

DOI

https://doi.org/10.1051/epjconf/202024509013

Conference Name

24TH INTERNATIONAL CONFERENCE ON COMPUTING IN HIGH ENERGY AND NUCLEAR PHYSICS

Collections

Department of Physics, Conference / Seminar

Suggestions

OpenMETU
Core

CTD2020: Exploring (Quantum) Track Reconstruction Algorithms for non-HEP applications Novotny, Kristiane; Dobos, Daniel; Demirköz, Melahat Bilge; Tüysüz, Cenk; Fracas, Fabio; Carminati, Federico; Vlimant, Jean-Roch; Potamianos, Karolos; Vallecorsa, Sofia (2020-4-20) The expected increase in simultaneous collisions creates a challenge for accurate particle track reconstruction in High Luminosity LHC experiments. Similar challenges can be seen in non-HEP trajectory reconstruction use-cases, where tracking and track evaluation algorithms are used. High occupancy, track density, complexity and fast growth therefore exponentially increase the demand of algorithms in terms of time, memory and computing resources. While traditionally Kalman filter (or even simpler algorithms)...
Particle-flow reconstruction and global event description with the CMS detector Sirunyan, A. M.; et. al. (IOP Publishing, 2017-10-01) The CMS apparatus was identified, a few years before the start of the LHC operation at CERN, to feature properties well suited to particle-flow (PF) reconstruction: a highly-segmented tracker, a fine-grained electromagnetic calorimeter, a hermetic hadron calorimeter, a strong magnetic field, and an excellent muon spectrometer. A fully-fledged PF reconstruction algorithm tuned to the CMS detector was therefore developed and has been consistently used in physics analyses for the first time at a hadron collide...
Strange particle production in pp collisions at root s=0.9 and 7 TeV Khachatryan, V.; et. al. (Springer Science and Business Media LLC, 2011-05-01) The spectra of strange hadrons are measured in proton-proton collisions, recorded by the CMS experiment at the CERN LHC, at centre-of-mass energies of 0.9 and 7TeV. The K-S(0), A, and Xi(-) particles and their antiparticles are reconstructed from their decay topologies and the production rates are measured as functions of rapidity and transverse momentum, p(T). The results are compared to other experiments and to predictions of the PYTHIA Monte Carlo program. The p(T) distributions are found to differ subst...
Particle Filtering with Propagation Delayed Measurements Orguner, Umut (2010-03-13) This paper investigates the problem of propagation delayed measurements in a particle filtering scenario. Based on implicit constraints specified by target dynamics and physics rules of signal propagation, authors apply the ideas that were first proposed in their previous work to the case of particle filters. Unlike the deterministic sampling based approach called propagation delayed measurement filter (PDMF) in their previous work, the new algorithm proposed here (called as PDM particle filter (PDM-PF)) ha...
Molecular-dynamics simulations of carbon nanocage structures: Nanoballs and nanotoroids Erkoç, Şakir; Vural, DC (World Scientific Pub Co Pte Lt, 2001-06-01) The structural stability of carbon nanocages, fullerens and toroids, have been investigated by performing molecular-dynamics computer simulations. The systems considered are C-120 and C-240 in ball and toroidal structures. Calculations have been realized by using an empirical many-body potential energy function for carbon. It has been found that C-120 ball is very unstable, and the other structures are relatively more strong against heat treatment.

Citation Formats

M. B. Demirköz et al., “Particle Track Reconstruction with Quantum Algorithms,” 2020, vol. 245, Accessed: 00, 2021. [Online]. Available: http://dx.doi.org/10.1051/epjconf/202024509013.