138 citations · 237 across the 15 of their papers we have counts for
6 papers · 1 filter
Particle Generative Adversarial Networks for full-event simulation at the LHC and their application to pileup description
Jesus Arjona Martinez, Thong Q Nguyen, Maurizio Pierini +2
We investigate how a Generative Adversarial Network could be used to generate a list of particle four-momenta from LHC proton collisions, allowing one to define a generative model…
Interaction networks for the identification of boosted decays
Eric A. Moreno, Thong Q. Nguyen, Jean-Roch Vlimant +6
We develop an algorithm based on an interaction network to identify high-transverse-momentum Higgs bosons decaying to bottom quark-antiquark pairs and distinguish them from ordinar…
Charged particle tracking with quantum annealing-inspired optimization
Alexander Zlokapa, Abhishek Anand, Jean-Roch Vlimant +4
At the High Luminosity Large Hadron Collider (HL-LHC), traditional track reconstruction techniques that are critical for analysis are expected to face challenges due to scaling wit…
JEDI-net: a jet identification algorithm based on interaction networks
Eric A. Moreno, Olmo Cerri, Javier M. Duarte +7
We investigate the performance of a jet identification algorithm based on interaction networks (JEDI-net) to identify all-hadronic decays of high-momentum heavy particles produced…
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…
The Tracking Machine Learning challenge : Accuracy phase
Sabrina Amrouche, Laurent Basara, Paolo Calafiura +24
This paper reports the results of an experiment in high energy physics: using the power of the "crowd" to solve difficult experimental problems linked to tracking accurately the tr…