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
doaj +1 more source
Coprocessor integration for real-time event processing in particle physics detectors
, 2016 High-energy physics experiments today have higher energies, more accurate sensors, and more flexible means of data collection than ever before. Their rapid progress requires ever more computational power; and massively parallel hardware, such as graphics cards, holds the promise to provide this power at a much lower cost than traditional CPUs.
Alexey Pavlovich Badalov
openalex +2 more sources
Machine learning-based jet and event classification at the Electron-Ion Collider with applications to hadron structure and spin physics [PDF]
Journal of High Energy Physics, 2022 We explore machine learning-based jet and event identification at the future Electron-Ion Collider (EIC). We study the effectiveness of machine learning-based classifiers at relatively low EIC energies, focusing on (i) identifying the flavor of the jet ...
Kyle Lee +4 more
semanticscholar +1 more source
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
doaj +1 more source
Primordial gravitational waves in a minimal model of particle physics and cosmology [PDF]
Journal of Cosmology and Astroparticle Physics, 2020 In this paper we analyze the spectrum of the primordial gravitational waves (GWs) predicted in the Standard Model*Axion*Seesaw*Higgs portal inflation (SMASH) model, which was proposed as a minimal extension of the Standard Model that addresses five ...
A. Ringwald, K. Saikawa, C. Tamarit
semanticscholar +1 more source
A survey of machine learning-based physics event generation [PDF]
International Joint Conference on Artificial Intelligence, 2021 Event generators in high-energy nuclear and particle physics play an important role in facilitating studies of particle reactions. We survey the state of the art of machine learning (ML) efforts at building physics event generators.
Y. Alanazi +7 more
semanticscholar +1 more source
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 ...
Claudia Hoell +14 more
openaire +3 more sources
A comprehensive guide to the physics and usage of PYTHIA 8.3 [PDF]
SciPost Physics Codebases, 2022 This manual describes the Pythia event generator, the most recent version of an evolving physics tool used to answer fundamental questions in particle physics. The program is most often used to generate high-energy-physics collision “events”, i.e.
C. Bierlich +13 more
semanticscholar +1 more source
Fast inference of deep neural networks in FPGAs for particle physics [PDF]
Journal of Instrumentation, 2018 Recent results at the Large Hadron Collider (LHC) have pointed to enhanced physics capabilities through the improvement of the real-time event processing techniques.
Javier Mauricio Duarte +10 more
semanticscholar +1 more source
Ultra-high-granularity detector simulation with intra-event aware generative adversarial network and self-supervised relational reasoning [PDF]
Nature Communications, 2023 Simulating high-resolution detector responses is a computationally intensive process that has long been challenging in Particle Physics. Despite the ability of generative models to streamline it, full ultra-high-granularity detector simulation still ...
H. Hashemi +4 more
semanticscholar +1 more source