Optimizing XW → h0i Reconstruction Efficiency with Small-R (R = 0.4) and Large-R (R = 1.0) Jets
Abstract
Many Beyond the Standard Model searches at ATLAS employ jets to simplify event reconstruction. These jets cluster particle shower products into calculable objects, which are then used to obtain information about parent particles. Large-R (R = 1.0) jets combine these products into one jet that spans 2 radians, while small-R (R = 0.4) jets are used to further refine individual b-quark trajectories. Optimizing the use of jets is crucial for making precision measurements of Higgs bosons with high transverse momenta, and this paper uses b-quarks produced in the Wino chargino LSP decay to identify parameters that best do so. Monte Carlo simulation 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 reconstructions. Truth data analysis corroborated the paper's findings, especially for charginos with higher mass. These parameters were then used to refine small-R jet selection, increasing reconstruction efficiency across chargino masses. Further analysis into large-R jet selection would enhance these results, especially at higher chargino masses. A neural network would also prove useful for exploring the effects of combinations of parameters across chargino masses.
Turn this paper into a full lesson
ArcXiv compiles a staged curriculum from this paper: 8-12 lessons across beginner → advanced, synthesised section guides, visuals, flashcards, a quiz, exercises, and on-demand deep dives per section. Grounded in the abstract, never invented.