Results 11 to 20 of about 16,614 (261)

Machine learning and LHC event generation

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
doaj   +1 more source

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, Javier Duarte, Jean-Roch Vlimant, Maurizio Pierini, Maria Spiropulu   +4 more
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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, Dong Woo Kang, Tae-Geun Kim, Seong Chan Park, Yeji Park   +4 more
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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, Nowakowski Piotr, Foka Panagiota   +2 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, S. Dalla, S. Dalla, A. Balogh, A. Balogh, A. Balogh   +5 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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Using neural networks as an event trigger in elementary particle physics experiments [PDF]

Proceedings of 1994 IEEE International Conference on Neural Networks (ICNN'94), 2002
Elementary particle physics experiments often have to deal with high data rates. In order to avoid having to write out all data that is occurring online processors, triggers are used to cull out the uninteresting data. These triggers are based on some particular aspect of the physics being examined. At times these aspects are often equivalent to simple
Neis, E., Starr, F. W., Handler, T., Gabriel, T., Glover, C., Saini, S.   +5 more
openaire   +1 more source

Generalised Known Kinematics (GKK): an approach for kinematic observables in pair production events with decays involving invisible particles

Journal of High Energy Physics, 2023
Missing kinematic information of known invisible particles, such as neutrinos, limit several high-energy physics analysis. The undetected particle carries away momentum and energy information, preventing the total reconstruction of such an event.
Thomas M. G. Kraetzschmar, Fabian M. Krinner, Marvin Pfaff, Navid K. Rad, Armine Rostomyan, Lorenz Schlechter, Frank Simon   +6 more
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Pattern recognition and event reconstruction in particle physics experiments [PDF]

Reports on Progress in Physics, 2004
This report reviews methods of pattern recognition and event reconstruction used in modern high energy physics experiments. After a brief introduction into general concepts of particle detectors and statistical evaluation, different approaches in global and local methods of track pattern recognition are reviewed with their typical strengths and ...
openaire   +2 more sources

International Particle Physics Masterclasses with LHC data

EPJ Web of Conferences, 2014
The International Particle Physics Masterclasses is an educational activity developed by the International Particle Physics Outreach Group with the aim to bring the excitement of cutting-edge particle-physics research into the classroom.
Foka Panagiota
doaj   +1 more source