Report number
| ATL-PHYS-PUB-2024-015 |
Title
| Transformer networks for constituent-based b-jet calibration with the ATLAS detector |
Corporate
Author(s)
| The ATLAS collaboration |
Collaboration
| ATLAS Collaboration |
Publication
| 2024 |
Imprint
| 28 Jul 2024 |
Number of pages
| 29 |
Note
| All figures including auxiliary figures are available at https://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PUBNOTES/ATL-PHYS-PUB-2024-015 |
In:
| BOOST 2024 - 16th International Workshop on Boosted Object Phenomenology, Reconstruction, Measurements, and Searches at Colliders, Genova, It, 29 Jul - 2 Sep 2024 |
Subject category
| Particle Physics - Experiment |
Accelerator/Facility, Experiment
| CERN LHC ; ATLAS |
Free keywords
| machine learning ; neural networks ; transformers ; energy calibration ; mass calibration ; b-jets ; JetEtMiss ; JETETMISS |
Abstract
| The precise measurement of a jet’s kinematics is a critical component of the physics program based on proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider. The determination of the energy and mass of jets containing bottom quarks b-jets is particularly difficult as, for example, they have different radiation patterns compared to the average jet and can contain heavy-flavour decays into a charged lepton and an unobserved neutrino. This document reports on a novel calibration technique for jets focusing on b-jets using transformer-based neural networks trained on simulation samples to correct reconstructed jet properties to the true values. Separate simulation-based regression methods have been developed to estimate the transverse momentum of small-radius jets and the transverse momentum and mass of large-radius jets. In both cases, the regression methods move the median measurement closer to the true value. A relative resolution improvement with respect to the nominal calibration between 18% and 31%, depending on the transverse momentum, is demonstrated for small-radius jets. Both the large-radius jet transverse momentum and mass resolution are shown to improve by 25–35%. |
Scientific contact person
| Cerutti, F, (fabio.cerutti@cern.ch) |