CTD2020: Exploring (Quantum) Track Reconstruction Algorithms for non-HEP applications

Download

10.5281zenodo.4034357.pdf
10.5281zenodo.4088466.pdf

Date

2020-4-20

Author

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

Metadata

Show full item record

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

Item Usage Stats

190
views

87
downloads

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) are used, they are expected to scale worse than quadratically and thus strongly increasing the total processing time. Graph Neural Networks (GNN) are currently explored for HEP, but also non HEP trajectory reconstruction applications. Quantum Computers with their feature of evaluating a very large number of states simultaneously are therefore good candidates for such complex searches in large parameter and graph spaces. In this paper we present our work on implementing a quantum-based graph tracking machine learning algorithm to evaluate Traffic collision avoidance system (TCAS) probabilities of commercial flights.

URI

https://hdl.handle.net/11511/69085
https://youtu.be/GUQ4UJVrx-A

DOI

https://doi.org/10.5281/zenodo.4034357

Conference Name

Connecting the Dots Workshop (2020)

Collections

Department of Physics, Conference / Seminar

Suggestions

OpenMETU
Core

CTD2020: A Quantum Graph Network Approach to Particle Track Reconstruction Tüysüz, Cenk; Demirköz, Melahat Bilge; Dobos, Daniel; Fracas, Fabio; Carminati, Federico; Vlimant, Jean-Roch; Potamianos, Karolos; Novotny, Kristiane; Vallecorsa, Sofia (2020-4-20) The unprecedented increase of complexity and scale of data is expected in the necessary computation for tracking detectors of the High Luminosity Large Hadron Collider (HL-LHC) experiments. While currently used Kalman filter based algorithms are reaching their limits in terms of ambiguities from increasing number of simultaneous collisions, occupancy, and scalability (worse than quadratic), a variety of machine learning approaches to particle track reconstruction are explored. It has been demonstrated previ...
Particle Track Reconstruction with Quantum Algorithms Demirköz, Melahat Bilge; Carminati, Federico; Dobos, Daniel; Fracas, Fabio; Novotny, Kristiane; Potamianos, Karolos; Vallecorsa, Sofia; Vlimant, Jean-Roch (2020-11-16) 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 as...
Inclusive Search for Supersymmetry Using Razor Variables in pp Collisions at root s=7 TeV Chatrchyan, S.; et. al. (2013-08-01) An inclusive search is presented for new heavy particle pairs produced in root s = 7 TeV proton-proton collisions at the LHC using 4.7 +/- 0.1 fb(-1) of integrated luminosity. The selected events are analyzed in the 2D razor space of M-R, an event-by-event indicator of the heavy particle mass scale, and R, a dimensionless variable related to the missing transverse energy. The third-generation sector is probed using the event heavy-flavor content. The search is sensitive to generic supersymmetry models with ...
Constituting financialized subjectivities: cultural political economy of financial literacy in Turkey Ayhan, Berkay (Informa UK Limited, 2019-10-20) A search for neutral Higgs bosons in the minimal supersymmetric extension of the standard model (MSSM) decaying to tau-lepton pairs in pp collisions is performed, using events recorded by the CMS experiment at the LHC. The dataset corresponds to an integrated luminosity of 24.6 fb−1, with 4.9 fb−1 at 7 TeV and 19.7 fb−1 at 8 TeV. To enhance the sensitivity to neutral MSSM Higgs bosons, the search includes the case where the Higgs boson is produced in association with a b-quark jet. No excess is observed in ...
Precise determination of the mass of the Higgs boson and tests of compatibility of its couplings with the standard model predictions using proton collisions at 7 and 8 TeV Khachatryan, V.; et. al. (Springer Science and Business Media LLC, 2015-05-01) Properties of the Higgs boson with mass near 125 GeV are measured in proton-proton collisions with the CMS experiment at the LHC. Comprehensive sets of production and decay measurements are combined. The decay channels include gamma gamma, ZZ, WW, tau tau, bb, and mu mu pairs. The data samples were collected in 2011 and 2012 and correspond to integrated luminosities of up to 5.1 fb(-1) at 7 TeV and up to 19.7 fb(-1) at 8 TeV. From the high-resolution gamma gamma and ZZ channels, the mass of the Higgs boson ...

Citation Formats

K. Novotny et al., “CTD2020: Exploring (Quantum) Track Reconstruction Algorithms for non-HEP applications,” presented at the Connecting the Dots Workshop (2020), 2020, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/69085.