1.2k citations · 7.5k across the 116 of their papers we have counts for
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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…
Deploying Scientific AI Networks at Petaflop Scale on Secure Large Scale HPC Production Systems with Containers
David Brayford, Sofia Vallercorsa
There is an ever-increasing need for computational power to train complex artificial intelligence (AI) & machine learning (ML) models to tackle large scientific problems. High perf…
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…
GeantV: Results from the prototype of concurrent vector particle transport simulation in HEP
G. Amadio, A. Ananya, J. Apostolakis +39
Full detector simulation was among the largest CPU consumer in all CERN experiment software stacks for the first two runs of the Large Hadron Collider (LHC). In the early 2010's, t…
Particle Identification Using Boosted Decision Trees in the Semi-Digital Hadronic Calorimeter Prototype
D. Boumediene, A. Pingault, M. Tytgat +87
The CALICE Semi-Digital Hadronic CALorimeter (SDHCAL) prototype using Glass Resistive Plate Chambers as a sensitive medium is the first technological prototype of a family of high-…
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…
Calorimetry with Deep Learning: Particle Simulation and Reconstruction for Collider Physics
Dawit Belayneh, Federico Carminati, Amir Farbin +13
Using detailed simulations of calorimeter showers as training data, we investigate the use of deep learning algorithms for the simulation and reconstruction of particles produced i…