A new dipole-based jet clustering algorithm

Abstract

Jet production occurs very often in particle physics experiments, and a very good understanding of how partons evolve into jets has been achieved over the last 30 years. The main tool in jet analysis is jet clustering algorithms, and because the problem of clustering particles back to initial partons can not be solved exactly, many different algorithms have been developed. In this work, we propose a new dipole-based jet clustering algorithm, called the dipole-$k_t$ algorithm with two main features; it uses a Lorentz invariant distance measure, and it does 3 to 2 recombinations in an attempt to "invert" a dipole-based parton shower. We validate its exclusive version by comparing it to the k_t-algorithm. We then proceed to analyze the dipole-k_t results in W-production events in proton proton collisions, where the has a large transverse momentum and decays into jets. A simple analysis of the W mass reconstruction strengthens our hope that with future developments this area of work will become dipole-k_t algorithm's main forte