Non-Bessel-Gaussianity and Flow Harmonic Fine-Splitting
Hadi Mehrabpour, Seyed Farid Taghavi

TL;DR
This paper introduces a new statistical framework using Gram-Charlier A series to analyze flow harmonic distributions in heavy-ion collisions, improving the understanding of flow fluctuations and geometry effects.
Contribution
It develops a novel set of cumulants and estimators based on Gram-Charlier A series to better characterize flow harmonic distributions and their deviations from Bessel-Gaussianity.
Findings
Corrected Bessel-Gaussian fits data better in peripheral collisions.
New cumulants $q_n\{2k\}$ effectively extract collision geometry effects.
Phase space restrictions on $v_2\{2k\}$ are consistent with experimental data.
Abstract
Both collision geometry and event-by-event fluctuations are encoded in the experimentally observed flow harmonic distribution and -particle cumulants . In the present study, we systematically connect these observables to each other by employing Gram-Charlier A series. We quantify the deviation of from Bessel-Gaussianity in terms of flow harmonic fine-splitting. Subsequently, we show that the corrected Bessel-Gaussian distribution can fit the simulated data better than the Bessel-Gaussian distribution in the more peripheral collisions. Inspired by Gram-Charlier A series, we introduce a new set of cumulants that are more natural to study distributions near Bessel-Gaussian. These new cumulants are obtained from where the collision geometry effect is extracted from it. By exploiting , we introduce a new set of estimators…
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