Data-driven analysis methods for the measurement of reconstructed jets in heavy ion collisions at RHIC and LHC

TL;DR

This paper introduces data-driven techniques for accurately reconstructing jets in heavy ion collisions at RHIC and LHC, addressing background noise and biases to improve jet quenching measurements.

Contribution

The paper develops and evaluates new data-driven methods to correct background effects and biases in jet reconstruction in heavy ion collision experiments.

Findings

Effective background correction techniques are proposed.

Methods reduce fragmentation bias in jet measurements.

Model studies validate the accuracy of the proposed methods.

Abstract

We present data-driven methods for the full reconstruction of jets in heavy ion collisions, for inclusive and co-incidence jet measurements at both RHIC and LHC. The complex structure of heavy ion events generates a large background of combinatorial jets, and smears the measured energy of the true hard jet signal. Techniques to correct for these background effects can induce biases in the reported jet distributions, which must be well controlled for accurate measurement of jet quenching. Using model studies, we evaluate the proposed methods for measuring jet distributions accurately while minimizing the fragmentation bias of the measured population.