Measurement of two-particle correlations with respect to second- and third-order event planes in Au$+$Au collisions at $\sqrt{s_{_{NN}}}=200$ GeV
A. Adare, S. Afanasiev, C. Aidala, N.N. Ajitanand, Y. Akiba, H., Al-Bataineh, J. Alexander, M. Alfred, K. Aoki, Y. Aramaki, E.T. Atomssa, R., Averbeck, T.C. Awes, B. Azmoun, V. Babintsev, A. Bagoly, M. Bai, G. Baksay,, L. Baksay, K.N. Barish, B. Bassalleck, A.T. Basye, S. Bathe

TL;DR
This paper investigates two-particle azimuthal correlations in gold-gold collisions at 200 GeV, revealing modifications consistent with jet quenching and path-length-dependent energy loss, and explores their dependence on event-plane angles.
Contribution
It provides detailed measurements of azimuthal correlations with respect to second- and third-order event planes, including their shape, yield, and asymmetries, advancing understanding of jet quenching mechanisms.
Findings
Suppressed away-side yield at high trigger pT compared to p+p collisions.
Modified away-side shape and yield at low associated pT, consistent with radiative energy loss.
Observed asymmetry related to the second-order event plane, indicating path-length dependence.
Abstract
We present measurements of azimuthal correlations of charged hadron pairs in GeV AuAu collisions for the trigger and associated particle transverse-momentum ranges of ~GeV/ and ~GeV/. After subtraction of an underlying event using a model that includes higher-order azimuthal anisotropy , , and , the away-side yield of the highest trigger-\pt (~GeV/) correlations is suppressed compared to that of correlations measured in collisions. At the lowest associated particle ( GeV/), the away-side shape and yield are modified relative to those in collisions. These observations are consistent with the scenario of radiative-jet energy loss. For the low- trigger correlations ( GeV/), a finite away-side yield exists and we explore the dependence of the…
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Taxonomy
TopicsHigh-Energy Particle Collisions Research · Nuclear physics research studies · Statistical Methods and Bayesian Inference
