| CMS Detector Performance Summaries | |
| Report number | CMS-DP-2024-064 ; CERN-CMS-DP-2024-064 |
| Title | Jet energy scale and resolution of jets with ParticleNet $p_{\mathrm{T}}$ regression using Run3 data collected by the CMS experiment in 2022 and 2023 at 13.6 TeV |
| Corporate author(s) | CMS Collaboration |
| Publication | 2024 |
| Collaboration | CMS Collaboration |
| Imprint | 15 Jul 2024 |
| Number of pages | 12 |
| Subject category | Detectors and Experimental Techniques |
| Accelerator/Facility, Experiment | CERN LHC ; CMS |
| Keywords | Physics Performance and Dataset |
| Abstract | Jet energy scale (JES) calibration is presented, based on the first reprocessing of data collected in pp collisions at $\sqrt{s}=13.6\mathrm{TeV}$ for data taking periods Era C (5.0$\,\text{fb}^{-1}$) and Era D (3.0$\,\text{fb}^{-1}$) of 2022, and prompt-reconstructed data from Era C (17.8$\,\text{fb}^{-1}$) of 2023. The results are shown for jets clustered from particle flow (PF) candidates using the anti-$k_{\mathrm{T}}$ algorithm with $R = 0.4$, and applying the Pileup Per Particle Identification (PUPPI) algorithm for pileup (PU) mitigation. Additionally, a new machine learning algorithm based on ParticleNet (PNet) is used for energy regression. |
Record created 2024-07-17, last modified 2024-07-17
