Particle production as a function of underlying-event activity measured with ALICE at the LHC

TL;DR

This paper investigates how particle production varies with underlying-event activity in proton-proton collisions at the LHC, using ALICE data and comparing results with PYTHIA simulations to understand collective effects and particle-production mechanisms.

Contribution

It introduces a novel approach to study particle production as a function of underlying-event activity, helping to disentangle soft and hard components in high-multiplicity pp collisions.

Findings

High-$p_{\rm T}$ particle yields increase more than linearly with multiplicity.

Underlying-event activity can be used to separate event components.

Comparison with PYTHIA shows qualitative agreement with some discrepancies.

Abstract

ALICE has performed several measurements aimed at understanding the collective-like effects observed in small collision systems. New approaches may be needed to clarify particle-production mechanisms in high-multiplicity pp collisions. Transverse momentum ($p_{\rm T}$) spectra as a function of charged-particle multiplicity show intriguing features. For example, data exhibit a stronger-than-linear increase of the self-normalised high-$p_{\rm T}$ particle yields versus multiplicity. In order to understand the role of auto-correlations on these effects, it has been proposed to use the underlying event as a multiplicity estimator to factorise the hardest and the softest components of the events. This approach can also be used to study collective effects in events with exceptionally large activity in the underlying-event region with respect to the event-averaged mean. In these proceedings, $p_{\rm T}$ spectra as a function of underlying-event activity in pp collisions measured with the ALICE detector are presented. Results are compared with PYTHIA 8.2 event generator.