Speaker
Description
Measurements of jet substructure are key to probing the energy frontier at colliders, and many of them use track-based observables which take advantage of the angular precision of tracking detectors. Theoretical calculations of track-based observables require “track functions”, which characterize the transverse momentum fraction $r_q$ carried by charged hadrons from a fragmenting quark or gluon. This work presents a direct measurement of $r_q$ distributions in dijet events from the 140 fb$^{-1}$ of $\sqrt{s}=13$ TeV proton-proton collisions collected by the ATLAS detector. The data are corrected for detector effects using a machine learning-based method named OmniFold. The scale evolution of the moments of the $r_q$ distribution provides direct access to non-linear renormalization group evolution equations of QCD, and is compared with analytic predictions. When incorporated into future theoretical calculations, these results will enable a precision program of theory-data comparison for track-based jet substructure observables.
| Track | Unfolding |
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