Improving Dark Matter searches using Track Assisted Reclustered (TAR) jets with the ATLAS detector at √s = 13 TeV

Dark Matter searches targeting boosted objects decaying into jets and missing transverse momentum are often limited by the performance in reconstructing the hadronic final state using jet substructure. The Track Assisted Reclustered (TAR) jet algorithm is a new reconstruction method for jets and provides an improved performance relative to standard techniques in a moderate pT range below about 1.5 TeV. This is shown to be particularly useful by improving the ability to identify W, top, and Higgs boson jets. Moreover, the radius of the reclustering algorithm can be optimised to best contain their decay product depending on the kinematic regime considered. Furthermore, TAR techniques can significantly reduce systematic uncertainties related to jet substructure. We discuss a wide variety of analyses applications as well as an analyses of the expected performance gains with respect to conventional calorimeter-based jet substructure observables.