Unveiling the effects of multiple soft partonic interactions in pp collisions at $\sqrt{{\textit s}}=13.6$ TeV using charged-particle flattenicity
Antonio Ortiz, Arvind Khuntia, Omar V\'azquez-Rueda, Sushanta, Tripathy, Gyula Bencedi, Suraj Prasad, Feng Fan

TL;DR
This paper investigates how the new event classifier flattenicity, based on forward-region multiplicity, can reveal effects of multiple soft partonic interactions in high-energy pp collisions, offering insights beyond traditional multiplicity measures.
Contribution
It introduces and explores flattenicity as a novel event classifier to study multi-partonic interactions in pp collisions at 13.6 TeV, reducing biases of traditional methods.
Findings
Flattenicity is sensitive to multi-partonic interactions.
Transverse momentum spectra vary with flattenicity.
PYTHIA 8 simulations show distinct patterns in hadron production.
Abstract
Event classifiers based either on the charged-particle multiplicity or the event shape have been extensively used in proton-proton (pp) collisions by the ALICE collaboration at the LHC. The use of these tools became very instrumental since the observation of fluid-like behavior in high-multiplicity pp collisions. In particular, the study as a function of the charged-particle multiplicity registered in the forward V0 ALICE detector allowed for the discovery of strangeness enhancement in high-multiplicity pp collisions. However, one drawback of the multiplicity-based event classifiers is that requiring a high charged-particle multiplicity biases the sample towards hard processes like multi-jet final states. These biases make it difficult to perform jet-quenching searches in high-multiplicity pp collisions. In this context, the present paper explores the use of the new event classifier,…
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Taxonomy
TopicsHigh-Energy Particle Collisions Research · Particle physics theoretical and experimental studies · Quantum Chromodynamics and Particle Interactions
