Minimising event size, maximising physics: inclusive particle isolation for LHCb’s Run 3 [PDF]
European Physical Journal C: Particles and FieldsThe Run 3 of the LHC brings unprecedented luminosity and a surge in data volume to the LHCb detector, necessitating a critical reduction in the size of each reconstructed event without compromising the physics reach of the heavy-flavour programme.
Marta Calvi +14 more
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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
doaj +7 more sources
Attention to the strengths of physical interactions: Transformer and graph-based event classification for particle physics experiments [PDF]
SciPost PhysicsA major task in particle physics is the measurement of rare signal processes. Even modest improvements in background rejection, at a fixed signal efficiency, can significantly enhance the measurement sensitivity. Building on prior research by others that
Luc Builtjes, Sascha Caron, Polina Moskvitina, Clara Nellist, Roberto Ruiz de Austri, Rob Verheyen, Zhongyi Zhang
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Physics-based Simulation of the 2013 April 11 Solar Energetic Particle Event
The Astrophysical JournalSolar energetic particles (SEPs) can pose hazardous radiation risks to both humans and spacecraft electronics in space. Numerical modeling based on first principles offers valuable insights into the underlying physics of SEPs and provides synthetic ...
Weihao Liu +13 more
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Efficient discrete-event based particle tracking simulation for high energy physics [PDF]
Computer Physics Communications, 2021 Accepted for publication in Computer Physics ...
Lucio Santi, Lucas Rossi, Rodrigo Castro
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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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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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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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Physical characterization of aerosol particles during nucleation events [PDF]
Tellus B: Chemical and Physical Meteorology, 2001 Particle concentrations and size distributions have been measured from different heights inside and above a boreal forest during three BIOFOR campaigns (14 April–22 May 1998, 27 July–21 August 1998 and 20 March–24 April 1999) in Hyytiälä, Finland. Typically, the shape of the background distribution inside the forest exhibited 2 dominant modes: a fine ...
PASI AALTO +13 more
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Modern Particle Physics Event Generation with WHIZARD [PDF]
Journal of Physics: Conference Series, 2015 We describe the multi-purpose Monte-Carlo event generator WHIZARD for the simulation of high-energy particle physics experiments. Besides the presentation of the general features of the program like SM physics, BSM physics, and QCD effects, special emphasis will be given to the support of the most accurate simulation of the collider environments at ...
Reuter, J. +6 more
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