Description
We present results using an optimized jet clustering with variable R, where the jet distance parameter $R$ depends on the mass and transverse momentum $𝑝_𝑇$ of the jet. The jet size decreases with increasing $𝑝_𝑇$, and increases with increasing mass. This choice is motivated by the kinematics of hadronic decays of highly Lorentz boosted top quarks, W, Z, and H bosons. The jet clustering features an inherent grooming with soft drop and a reconstruction of subjets in one sequence. These features have been implemented in the Heavy Object Tagger with Variable $R$ (HOTVR) algorithm, which we use to study the performance of jet substructure tagging with different choices of grooming parameters and functional forms of $R$.
| Collaboration / Activity | Jet substructure |
|---|
Primary authors
Anna Benecke
(UCLouvain)
Anna Monika Albrecht
(UNI/EXP (Uni Hamburg, Institut fur Experimentalphysik))
Roman Kogler
(DESY)
