Extracting Essential Non-perturbative Information in Jet Invariant Mass via the Bayesian Analysis

TL;DR

This paper introduces a new three-dimensional non-perturbative function to better understand jet invariant mass spectra by analyzing experimental data from various collider experiments, revealing the dominant contributions in different regions.

Contribution

It is the first to simultaneously extract non-perturbative effects from hadronization, soft-gluon radiation, and underlying events using Bayesian analysis across diverse datasets.

Findings

Hadronization dominates in small-R region

Underlying events dominate in large-R region

Soft-gluon radiation contribution is negligible

Abstract

In this paper, we present a new three-dimensional non-perturbative (NP) function to account for and parameterize the NP contributions in the jet invariant mass spectrum, in addition to the conventional NP mass shift parametrization. By implementing Bayesian analysis on experimental data of the jet invariant mass from exclusive $W/Z+$jet events and inclusive jet events in $pp$ collisions at RHIC and LHC, where collisional energy increases by a factor of up to $65$ from RHIC to LHC, we ensure the analysis covers a wide range of data. For the first time, we simultaneously extract NP contributions from hadronization, initial soft-gluon radiation, and underlying events, based on two different NP prescriptions. We find that the contribution from initial soft-gluon radiation is negligible, and the hadronization effect dominates in the small-$R$ region, while underlying events provide the dominant contribution in the large-$R$ region. Moreover, when only hadronization effects are considered, our results successfully describe the jet mass data measured in $e^+e^-$ collisions, where only hadronization effects are expected to be present. Our work offers quantitative insights into understanding the soft hadronic contribution to jet substructure.