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Snowmass 2001: Jet Energy Flow Project

C. F. Berger, E. L. Berger, P. C. Bhat, J. M. Butterworth, S. D. Ellis, B. Flaugher, W. T. Giele, W. Kilgore, A. Kulesza, S. Lammers, S. Magill, H. Prosper

TL;DR

Conventional jet algorithms enforce a unique jet-parton mapping that is vulnerable to showering, hadronization, and detector effects. Jet Energy Flow (JEF) reframes final states as continuous energy-flow distributions without assigning jets to partons on an event-by-event basis, using a normalized kernel to smear energy across angles. The approach yields analytic, occupancy-based observables (e.g., jet mass, $E_T$, di-jet mass) and demonstrates reduced sensitivity to higher-order corrections in a di-jet example compared with cone analyses. This suggests JEF could provide more robust, perturbatively stable jet measurements in hadronic collisions, pending broader validation and refinement.

Abstract

Conventional cone jet algorithms arose from heuristic considerations of LO hard scattering coupled to independent showering. These algorithms implicitly assume that the final states of individual events can be mapped onto a unique set of jets that are in turn associated with a unique set of underlying hard scattering partons. Thus each final state hadron is assigned to a unique underlying parton. The Jet Energy Flow (JEF) analysis described here does not make such assumptions. The final states of individual events are instead described in terms of flow distributions of hadronic energy. Quantities of physical interest are constructed from the energy flow distribution summed over all events. The resulting analysis is less sensitive to higher order perturbative corrections and the impact of showering and hadronization than the standard cone algorithms.

Snowmass 2001: Jet Energy Flow Project

TL;DR

Conventional jet algorithms enforce a unique jet-parton mapping that is vulnerable to showering, hadronization, and detector effects. Jet Energy Flow (JEF) reframes final states as continuous energy-flow distributions without assigning jets to partons on an event-by-event basis, using a normalized kernel to smear energy across angles. The approach yields analytic, occupancy-based observables (e.g., jet mass, , di-jet mass) and demonstrates reduced sensitivity to higher-order corrections in a di-jet example compared with cone analyses. This suggests JEF could provide more robust, perturbatively stable jet measurements in hadronic collisions, pending broader validation and refinement.

Abstract

Conventional cone jet algorithms arose from heuristic considerations of LO hard scattering coupled to independent showering. These algorithms implicitly assume that the final states of individual events can be mapped onto a unique set of jets that are in turn associated with a unique set of underlying hard scattering partons. Thus each final state hadron is assigned to a unique underlying parton. The Jet Energy Flow (JEF) analysis described here does not make such assumptions. The final states of individual events are instead described in terms of flow distributions of hadronic energy. Quantities of physical interest are constructed from the energy flow distribution summed over all events. The resulting analysis is less sensitive to higher order perturbative corrections and the impact of showering and hadronization than the standard cone algorithms.

Paper Structure

This paper contains 5 sections, 12 equations, 4 figures.

Table of Contents

  1. Introduction
  2. The JEF Formalism
  3. Observables
  4. An Example JEF Analysis
  5. Concluding Remarks

Figures (4)

  • Figure 1: Transverse energy (in GeV color coding) calorimeter readout in a typical CDF event as a function of pseudorapidity and azimuthal angle. The reconstructed CDF cone jets are indicated by the circles (with the same GeV color coding).
  • Figure 2: The $E_{T}\left( \eta,\phi\right)$ flow (including the factor $\pi R^{2}$) using the CDF event of Figure 1.
  • Figure 3: Same as Figure 2 except that the maximum $E_{T}$ for the color coding is 15 GeV.
  • Figure 6: Differential cross section of Eq. \ref{['diffdiJEF']} for both JEF (moving cone) and EKS (fixed cone) analysis at LO and NLO.