ATLAS flavour-tagging algorithms for the LHC Run 2 pp collision dataset - Abusleme Hoffman, A. C.; Angerami, A.; Armbruster, A. J.; Assamagan, K.; Balaji, S.; Balek, P.; Battulga, D.; Bayirli, A.; Berthold, A.; Bielski, R.; Bird, G. A.; Bisanz, T.; et al. (European Physical Journal C, 2023)
Keywords: Algorithms; Artificial neural networks; Astronomy; Astrophysics and Cosmology; Collaboration; Computer simulation; Data Analysis, Statistics and Probability; Datasets; Efficiency; Elementary Particles; Flavor (particle physics); Fysik; Hadrons; Heavy Ions; High Energy Physics - Experiment; Large Hadron Collider; Magnetic fields; Measurement Science and Instrumentation; Natural Sciences; Naturvetenskap; Neural networks; Nuclear Energy; Nuclear Physics; Physical Sciences; Physics; Physics and Astronomy; Quantum Field Theories; Quantum Field Theory; Quarks; Radiation; Regular Article - Experimental Physics; Rejection; Sensors; Silicon; Software; String Theory; Subatomic Physics; Subatomär fysik; ATLAS; bottom particle: particle identification; data analysis method; efficiency; numerical calculations; performance; charmed particle: particle identification; p p: scattering; neural network