Effect of event classifiers on jet quenching-like signatures in high-multiplicity $p+p$ collisions at $\sqrt{s} = 13$ TeV
Hushnud Hushnud, Omveer Singh, Srikanta Kumar Tripathy, Aditya Nath, Mishra, Kalyan Dey

TL;DR
This paper investigates how different event classifiers, especially flattenicity, influence the observation of jet quenching-like signatures in high-multiplicity proton-proton collisions at 13 TeV, aiming to better understand the underlying physics.
Contribution
It introduces flattenicity as a new event classifier to reduce bias and studies its impact on jet quenching signatures using PYTHIA8 simulations.
Findings
Flattenicity shows heavy-ion-like effects in high-multiplicity $p+p$ collisions.
The use of flattenicity reduces bias towards hard processes compared to V0M.
Results suggest flattenicity can better probe soft and hard process interplay.
Abstract
The motivation behind exploring jet quenching-like phenomena in small systems arises from the experimental observation of heavy-ion-like behavior of particle production in high-multiplicity proton-proton () collisions. Quantifying the jet quenching in collisions is a challenging task, as the magnitude of the nuclear modification factor ( or ), which is used to quantify jet quenching, is influenced by several factors, such as the estimation of centrality and the scaling factor. The most common method of centrality estimation employed by the ALICE collaboration is based on measuring charged-particle multiplicity with the V0 detector situated at the forward rapidity. This technique of centrality estimation makes the event sample biased towards hard processes like multijet final states. This bias of the V0 detector towards hard processes makes it difficult…
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Taxonomy
TopicsHigh-Energy Particle Collisions Research · Particle physics theoretical and experimental studies · Quantum Chromodynamics and Particle Interactions
