Hybrid Quantum Classical Graph Neural Networks for Particle Track Reconstruction

1 code implementation • 26 Sep 2021 • Cenk Tüysüz, Carla Rieger, Kristiane Novotny, Bilge Demirköz, Daniel Dobos, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant, Richard Forster

This increase in luminosity will significantly increase the number of particles interacting with the detector.

Performance of Particle Tracking Using a Quantum Graph Neural Network

no code implementations • 2 Dec 2020 • Cenk Tüysüz, Kristiane Novotny, Carla Rieger, Federico Carminati, Bilge Demirköz, Daniel Dobos, Fabio Fracas, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant

The Large Hadron Collider (LHC) at the European Organisation for Nuclear Research (CERN) will be upgraded to further increase the instantaneous rate of particle collisions (luminosity) and become the High Luminosity LHC.

Quantum Physics

A Quantum Graph Neural Network Approach to Particle Track Reconstruction

1 code implementation • 14 Jul 2020 • Cenk Tüysüz, Federico Carminati, Bilge Demirköz, Daniel Dobos, Fabio Fracas, Kristiane Novotny, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant

Unprecedented increase of complexity and scale of data is expected in computation necessary for the tracking detectors of the High Luminosity Large Hadron Collider (HL-LHC) experiments.

Quantum Physics

Particle Track Reconstruction with Quantum Algorithms

1 code implementation • 18 Mar 2020 • Cenk Tüysüz, Federico Carminati, Bilge Demirköz, Daniel Dobos, Fabio Fracas, Kristiane Novotny, Karolos Potamianos, Sofia Vallecorsa, Jean-Roch Vlimant

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.

Quantum Physics High Energy Physics - Experiment Data Analysis, Statistics and Probability