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Development of Interest in Particle Physics as an Effect of School Events in an Authentic Setting
Scientia in Educatione, 2017 The Particle Physics Masterclasses are events offered by the “Netzwerk Teilchenwelt”, a German network of particle physicists, students and teachers with the intention to make original data from CERN available for own measurements of students.
Kerstin Gedigk +2 more
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Machine learning and LHC event generation [PDF]
SciPost Physics, 2023 First-principle simulations are at the heart of the high-energy physics research program. They link the vast data output of multi-purpose detectors with fundamental theory predictions and interpretation.
Anja Butter, Tilman Plehn, Steffen Schumann, Simon Badger, Sascha Caron, Kyle Cranmer, Francesco Armando Di Bello, Etienne Dreyer, Stefano Forte, Sanmay Ganguly, Dorival Gonçalves, Eilam Gross, Theo Heimel, Gudrun Heinrich, Lukas Heinrich, Alexander Held, Stefan Höche, Jessica N. Howard, Philip Ilten, Joshua Isaacson, Timo Janßen, Stephen Jones, Marumi Kado, Michael Kagan, Gregor Kasieczka, Felix Kling, Sabine Kraml, Claudius Krause, Frank Krauss, Kevin Kröninger, Rahool Kumar Barman, Michel Luchmann, Vitaly Magerya, Daniel Maitre, Bogdan Malaescu, Fabio Maltoni, Till Martini, Olivier Mattelaer, Benjamin Nachman, Sebastian Pitz, Juan Rojo, Matthew Schwartz, David Shih, Frank Siegert, Roy Stegeman, Bob Stienen, Jesse Thaler, Rob Verheyen, Daniel Whiteson, Ramon Winterhalder, Jure Zupan
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New developments for ALICE MasterClasses and the new Particle Therapy MasterClass [PDF]
EPJ Web of Conferences, 2020 International MasterClasses (IMC), an outreach activity of the International Particle Physics Outreach Group (IPPOG), has been bringing cuttingedge particle physics research to schoolchildren for over 15 years now. All four LHC experiments participate in
Graczykowski Łukasz +2 more
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Accelerating End-to-End Deep Learning for Particle Reconstruction using CMS open data [PDF]
EPJ Web of Conferences, 2021 Machine learning algorithms are gaining ground in high energy physics for applications in particle and event identification, physics analysis, detector reconstruction, simulation and trigger. Currently, most data-analysis tasks at LHC experiments benefit
Andrews Michael +8 more
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Graph Variational Autoencoder for Detector Reconstruction and Fast Simulation in High-Energy Physics [PDF]
EPJ Web of Conferences, 2021 Accurate and fast simulation of particle physics processes is crucial for the high-energy physics community. Simulating particle interactions with the detector is both time consuming and computationally expensive.
Hariri Ali +2 more
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VBF Event Classification with Recurrent Neural Networks at ATLAS’s LHC Experiment
Applied Sciences, 2023 A novel machine learning (ML) approach based on a recurrent neural network (RNN) for event topology identification in high energy physics (HEP) is presented.
Silvia Auricchio +2 more
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MLPF: efficient machine-learned particle-flow reconstruction using graph neural networks
European Physical Journal C: Particles and Fields, 2021 In general-purpose particle detectors, the particle-flow algorithm may be used to reconstruct a comprehensive particle-level view of the event by combining information from the calorimeters and the trackers, significantly improving the detector ...
Joosep Pata +4 more
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Investigating the origin of strangeness enhancement in small systems through multi-differential analyses [PDF]
EPJ Web of Conferences, 2022 The main goal of the ALICE experiment is to study the physics of strongly interacting matter, including the properties of the quark-gluon plasma (QGP). The relative production of strange hadrons with respect to non-strange hadrons in heavy-ion collisions
Ercolessi Francesca
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Missing information search with deep learning for mass estimation
Physical Review Research, 2023 We introduce DeeLeMa, a deep learning-based network for the analysis of energy and momentum in high-energy particle collisions. This novel approach is specifically designed to address the challenge of analyzing collision events with multiple invisible ...
Kayoung Ban +4 more
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Detection of zero anisotropy at 5.2 AU during the November 1998 solar particle event: Ulysses Anisotropy Telescopes observations [PDF]
Annales Geophysicae, 2000 For the first time during the mission, the Anisotropy Telescopes instrument on board the Ulysses spacecraft measured constant zero anisotropy of protons in the 1.3-2.2 MeV energy range, for a period lasting more than three days.
S. Dalla +5 more
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