New Angles on Energy Correlation Functions
Ian Moult, Lina Necib, Jesse Thaler

TL;DR
This paper introduces a systematic framework for generalized energy correlation functions to develop new jet substructure observables, enhancing particle identification and discrimination capabilities at the LHC.
Contribution
It defines a generalized class of energy correlation functions and proposes three new series of discriminants tailored for specific jet tagging tasks.
Findings
Identified three new discriminant series: M_i, N_i, U_i.
Demonstrated improved discrimination power with groomed jets.
Provided a flexible basis for constructing optimized jet substructure observables.
Abstract
Jet substructure observables, designed to identify specific features within jets, play an essential role at the Large Hadron Collider (LHC), both for searching for signals beyond the Standard Model and for testing QCD in extreme phase space regions. In this paper, we systematically study the structure of infrared and collinear safe substructure observables, defining a generalization of the energy correlation functions to probe -particle correlations within a jet. These generalized correlators provide a flexible basis for constructing new substructure observables optimized for specific purposes. Focusing on three major targets of the jet substructure community---boosted top tagging, boosted tagging, and quark/gluon discrimination---we use power-counting techniques to identify three new series of powerful discriminants: , , and . The series is designed for…
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