Measurement of the b-tagging efficiency using multi-jet events in ATLAS.

The identification of jets containing b-hadrons, b-tagging, plays an important role in many physics analyses in ATLAS. Several different machine learning algorithms have been deployed for the purpose of b-tagging. These tagging algorithms are trained using Monte-Carlo simulation samples, as such their performance in data must be measured. The b-tagging efficiencies have been measured in data using 𝑡𝑡 events in the past and this work presents the measurements in multijet events using data collected by the ATLAS detector at √𝑠 = 13 TeV for the first time. This offers several key advantages over the 𝑡𝑡 based calibrations, including a higher precision at low jet 𝑝𝑇 and the ability to perform measurements of 𝜀𝑏 at significantly higher jet 𝑝𝑇 . Two approaches are applied and for both a profile likelihood fit is performed to extract the number of b-jets in samples passing and failing a given b-tagging requirement. The b-jets yields are then used to determine 𝜀𝑏 in data and from that scale factors to the efficiency measured in MC. The two approaches differ primarily in the discriminating variable used in the fit. At low jet 𝑝𝑇 the variable muon 𝑝Trel is used, while for high jet 𝑝𝑇 the signed impact parameter significance is used. Both calibrations give measurements of the scale factors as a function of the jet 𝑝𝑇 .