Optimizing Higgs Boson Reconstruction Using Small-R (R=0.4) and Large-R (R=1.0) Jets

Many beyond the Standard Model searches by the ATLAS experiment at the CERN Large Hadron Collider employ jets to simplify event reconstruction. Two types of jets have been studied to optimize the selection and reconstruction of a final state with many jets originating from four b-quarks. A large-R (R = 1.0) jet combines particle shower products into one jet that spans 2 radians, while a small-R (R = 0.4) jet gives finer-grained information. In this talk, we consider the pair production of charginos with R-parity violating (RPV) decays to a charged lepton and a Higgs boson, which subsequently decays to two b-quarks. In studies of Monte Carlo simulation, we found that parameters such as the distance between Higgs bosons and the distance between b-jets were relevant in selecting the most accurate small-R jet reconstructions. These parameters were then used to refine small-R jet selection, increasing reconstruction efficiency across a wide range of possible chargino masses compared to a selection using large-R jets. To extend these findings to a model with a RPV decay directly to two b-quarks and a lepton without the intermediate Higgs boson, machine learning techniques are now being explored.