Jets with Variable R

TL;DR

This paper introduces a novel jet algorithm with a variable radius that adapts to jet transverse momentum, improving the efficiency of resonance reconstruction in high-energy physics experiments.

Contribution

It presents a new jet clustering algorithm with a variable radius parameter, specifically scaling as 1/pT, enhancing the reconstruction of resonance masses and kinematic features.

Findings

10-20% improvement in signal efficiency over fixed radius algorithms

Effective in reconstructing resonance masses and kinematic endpoints

Provides strategies to reduce continuum jet backgrounds

Abstract

We introduce a new class of jet algorithms designed to return conical jets with a variable Delta R radius. A specific example, in which Delta R scales as 1/pT, proves particularly useful in capturing the kinematic features of a wide variety of hard scattering processes. We implement this Delta R scaling in a sequential recombination algorithm and test it by reconstructing resonance masses and kinematic endpoints. These test cases show 10-20% improvements in signal efficiency compared to fixed Delta R algorithms. We also comment on cuts useful in reducing continuum jet backgrounds.