Finite V 2 Δ puzzle in low-multiplicity p p collisions from ultralong-range azimuthal correlations in the string-shoving model

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Authors: Antonio Ortiz, Dushmanta Sahu, G. Bencedi
Cited by: 0
References: 51

Abstract

Ultralong range angular correlations have been recently reported by the ALICE collaboration in pp collisions at s = 13 TeV below d N ch / d η = 7 . The measurements have been performed as a function of the charged-particle multiplicity at midrapidity ( N ch in | η | < 0.8 ), which is known to be strongly sensitive to local multiplicity fluctuations. The present work investigates the impact of the event-activity estimator on ultralong range angular correlations. The study is conducted in the framework of 8 with the string shoving mechanism since it gives a nonzero elliptic flow coefficient, V 2 Δ . Such collectivelike effects arise from repulsive interactions between overlapping color strings, without invoking hydrodynamic collectivity. The analysis is conducted as a function of N ch , the number of parton-parton scatterings ( N mpi ) and flattenicity. Surprisingly, for ultralong range correlations, pp collisions with N mpi = 1 (dijets) seem to be the most sensitive to string shoving. The effect diminishes with increasing N mpi . While in data, within uncertainties, V 2 Δ exhibits a weak multiplicity dependence; the string shoving mechanism gives a V 2 Δ that decreases with the increase in N ch . The present work therefore supports the picture stating that mechanisms such as string shoving might explain the low multiplicity limit, whereas, hydro becomes relevant in high-multiplicity pp collisions. This work also suggests that flattenicity might be more effective than N ch to better handle collectivelike effects.

Fields of Study & Subjects

High-Energy Particle Collisions Research Particle physics theoretical and experimental studies Quantum Chromodynamics and Particle Interactions

Publication details

Journal / source
Physical review. D/Physical review. D.
Volume
113
Issue
11
Publication date
26 May 2026
Language
EN