17 citations · 52 across the 8 of their papers we have counts for
5 papers · 1 filter
Performance of Particle Tracking Using a Quantum Graph Neural Network
Cenk Tüysüz, Kristiane Novotny, Carla Rieger +7
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 (luminos…
A Quantum Graph Neural Network Approach to Particle Track Reconstruction
Cenk Tüysüz, Federico Carminati, Bilge Demirköz +6
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) experim…
Quantum Machine Learning in High Energy Physics
Wen Guan, Gabriel Perdue, Arthur Pesah +4
Machine learning has been used in high energy physics for a long time, primarily at the analysis level with supervised classification. Quantum computing was postulated in the early…
Particle Track Reconstruction with Quantum Algorithms
Cenk Tüysüz, Federico Carminati, Bilge Demirköz +6
Accurate determination of particle track reconstruction parameters will be a major challenge for the High Luminosity Large Hadron Collider (HL-LHC) experiments. The expected increa…
Quantum adiabatic machine learning with zooming
Alexander Zlokapa, Alex Mott, Joshua Job +3
Recent work has shown that quantum annealing for machine learning, referred to as QAML, can perform comparably to state-of-the-art machine learning methods with a specific applicat…