Exploring Event-by-Event $\it{p}_{\rm T}$ Fluctuations in pp Collisions at $\sqrt{s} = 13$ TeV: An Insight from ALICE

TL;DR

This study investigates event-by-event mean transverse momentum fluctuations in proton-proton collisions at 13 TeV using ALICE data, exploring correlations across different $p_T$ regions and comparing with Monte Carlo models to understand underlying physics mechanisms.

Contribution

It provides a detailed analysis of $p_T$ fluctuations and correlations in pp collisions at 13 TeV, including their dependence on multiplicity and $p_T$ range, with comparisons to theoretical models.

Findings

Correlator decreases with increasing charged particle density.

Power-law behavior of correlations observed across systems.

Model comparisons reveal insights into fluctuation mechanisms.

Abstract

Event-by-event fluctuations of the mean transverse momentum ($p_{\rm T}$) of relativistic charged particles are analyzed using the two-particle correlator $\sqrt{C_m}/M(p_{\rm T})_m$, which quantifies the correlations strength in units of the mean $p_{\rm T}$ in proton-proton collision at $\sqrt{s} = 13$ TeV in ALICE both for minimum bias and and high-multiplicity triggered events. The non-monotonic variations in $p_{\rm T}$ correlations with changing energy could serve as a signature of QGP formation. A comprehensive investigation across soft-, intermediate-, and hard-$p_{\rm T}$ regions could provide crucial insights into both equilibrium (e.g., thermal radial flow) and non-equilibrium (e.g., jet/minijet) contributions to $p_{\rm T}$ fluctuations. The dependence of the correlator on particle multiplicity for different $p_{\rm T}$ window widths and positions is explored. The correlator values are found to decrease with increasing charged particle density, following a power-law behavior similar to observations in both small and large systems at lower energies. Additionally, the influence of $p_{\rm T}$ range on the power-law coefficient is studied and results are compared with predictions from Monte Carlo models, such as PYTHIA (pQCD string model) and EPOS (core-corona model), to enhance understanding of the underlying mechanisms driving $p_{\rm T}$ fluctuations.