SearcharxivSearch

arXiv subjects

Jason Veatch

Publications and source records attributed to Jason Veatch.

2 recordsLinked to original sources

TRSMScans

In this work, we propose a new scan tool that automatically calculates maximal cross section predictions for a new physics scenario with additional scalar states. While the tool is currently optimized for asymmetric production and decay processes in the form of p p -> h3 -> h1 h2, where hi denote CP even neutral scalars, in principle it can be extended to include any production and decay mode. As the code builds largely on the structure of the publicly available code ScannerS, it can in principle be extended to any other model contained within this tool. We here show first applications for a specific model, the Two-Real-Singlet Model (TRSM), and compare to publicly available results from the LHC collaborations from the previous runs. We also in detail discuss the structure of the code, including code installation, usage, as well as underlying algorithms.

hep-ph

Jet SIFT-ing: a new scale-invariant jet clustering algorithm for the substructure era

We introduce a new jet clustering algorithm named SIFT (Scale-Invariant Filtered Tree) that maintains the resolution of substructure for collimated decay products at large boosts. The scale-invariant measure combines properties of kT and anti-kT by preferring early association of soft radiation with a resilient hard axis, while avoiding the specification of a fixed cone size. Integrated filtering and variable-radius isolation criteria block assimilation of soft wide-angle radiation and provide a halting condition. Mutually hard structures are preserved to the end of clustering, automatically generating a tree of subjet axis candidates. Excellent object identification and kinematic reconstruction for multi-pronged resonances are realized across more than an order of magnitude in transverse energy. The clustering measure history facilitates high-performance substructure tagging, which we quantify with the aid of supervised machine learning. These properties suggest that SIFT may prove to be a useful tool for the continuing study of jet substructure.

hep-ph