New techniques for jet calibration with the ATLAS detector

AbstraktAbstract

A determination of the jet energy scale is presented using proton-proton collision data with a centre-of-mass energy of root s = 13 TeV, corresponding to an integrated luminosity of 140 fb(-1) collected using the ATLAS detector at the LHC. Jets are reconstructed using the ATLAS particle-flow method that combines charged-particle tracks and topo-clusters formed from energy deposits in the calorimeter cells. The anti-kt jet algorithm with radius parameter R = 0.4 is used to define the jet. Novel jet energy scale calibration strategies developed for the LHC Run 2 are reported that lay the foundation for the jet calibration in Run 3. Jets are calibrated with a series of simulation-based corrections, including state-of-the-art techniques in jet calibration such as machine learning methods and novel in situ calibrations to achieve better performance than the baseline calibration derived using up to 81 fb(-1) of Run 2 data. The performance of these new techniques is then examined in the in situ measurements by exploiting the transverse momentum balance between a jet and a reference object. The b-quark jet energy scale using particle flow jets is measured for the first time with around 1% precision using gamma+jet events.

A determination of the jet energy scale is presented using proton-proton collision data with a centre-of-mass energy of root s = 13 TeV, corresponding to an integrated luminosity of 140 fb(-1) collected using the ATLAS detector at the LHC. Jets are reconstructed using the ATLAS particle-flow method that combines charged-particle tracks and topo-clusters formed from energy deposits in the calorimeter cells. The anti-kt jet algorithm with radius parameter R = 0.4 is used to define the jet. Novel jet energy scale calibration strategies developed for the LHC Run 2 are reported that lay the foundation for the jet calibration in Run 3. Jets are calibrated with a series of simulation-based corrections, including state-of-the-art techniques in jet calibration such as machine learning methods and novel in situ calibrations to achieve better performance than the baseline calibration derived using up to 81 fb(-1) of Run 2 data. The performance of these new techniques is then examined in the in situ measurements by exploiting the transverse momentum balance between a jet and a reference object. The b-quark jet energy scale using particle flow jets is measured for the first time with around 1% precision using gamma+jet events.