Speaker
Description
Distinguishing quark-initiated jets from gluon-initiated jets is impactful for numerous LHC physics analyses, including precision Higgs boson measurements and searches for a production of two Higgs bosons in vector-boson fusion topologies. This talk presents DeParT, a transformer-based quark/gluon tagger developed by ATLAS that exploits the full information from jet constituents reconstructed in both the tracker and calorimeter systems, operating across an extended kinematic phase space. The efficiency measurement in data and tagger calibration is performed using dijet events from the LHC Run 2 and Run 3 proton--proton collision data. A key advancement is the deployment of the jet topics method, a data-driven technique that reduces reliance on Monte Carlo modelling compared to traditional approaches, yielding up to 20% smaller systematic uncertainties in some kinematic regions. The resulting efficiency scale factors enable robust application of the tagger across the ATLAS physics program.