Speaker
Description
The identification of massive particles decaying into bottom quark pairs is important for the physics program of the ATLAS experiment at the Large Hadron Collider. A neural network (NN) based double b-tagging algorithm named 𝑋→𝑏𝑏 ̅ tagger is developed and calibrations of the tagger are performed using proton-proton collision data corresponding to 139/𝑓𝑏 collected at a centre-of-mass energy of √𝑠=13𝑇𝑒𝑉.
The technique of 𝑋→𝑏𝑏 ̅ mis-tag rate calibration [1] is developed based on semi-leptonic decay 𝑡𝑡 ̅ events which provide typical non-𝑏𝑏 ̅ flavor combination and high statistics. The mis-tag efficiency is measured and the scale factor, which is defined as the ratio of the mis-tag rate measured in the data over the one in simulation, is found to be in a range of 1~1.1 with uncertainty less than 16%.
