Effects of an Improved Baseline and Selection Bias for Groomed Jet Data in Heavy-ion Collisions

Abstract

The plethora of existenting jet observables in heavy-ion collisions has allowed for an extensive description of jet quenching phenomena over the last decades. Despite this, we still lack a concise theoretical interpretation of the observed data, namely at the level of jet substructure observables. In an attempt to be dominated by perturbative dynamics, one usually relies on grooming methods which remove soft, wide-angle radiation, but even for this scenario, there are still competing explanations for the physical origin of the measured medium-induced modifications. To this end, we present a minimal approach to compute groomed substructure observables, with medium effects treated as an effective energy shift dependent on the jet substructure itself. By matching the NLO dijet matrix element with a leading-logarithmic-accurate parton shower and using an energy-loss model which includes colour coherence effects, we obtain a solid theory-to-data agreement (within 10%) when compared to ALICE and ATLAS data. We also find an overall better agreement with data when including colour coherence effects and we inspect the role of quark–gluon selection bias. Published by the Jagiellonian University 2026 authors