Constraining the CME in AVFD-simulated heavy-ion collisions using the Sliding Dumbbell Method

TL;DR

This paper uses the AVFD simulation framework and the Sliding Dumbbell Method to identify and analyze potential Chiral Magnetic Effect signals in heavy-ion collision data, accounting for background effects.

Contribution

It introduces the Sliding Dumbbell Method as a novel technique to detect CME-like events within simulated heavy-ion collision data.

Findings

SDM identifies CME-like events with characteristics consistent with CME.

Quantification of CME fraction in selected events considering background contributions.

Analysis of CME signal modulation through axial charge per entropy density.

Abstract

The Anomalous Viscous Fluid Dynamics (AVFD) framework is utilized to generate $^{197}_{79}Au+^{197}_{79}Au$, $^{96}_{44}Ru+^{96}_{44}Ru$, and $^{96}_{40}Zr+^{96}_{40}Zr$ collision events at $\sqrt{s_{\mathrm{NN}}}$ = 200 GeV to investigate the Chiral Magnetic Effect (CME). The CME signal is modulated through the axial charge per entropy density ($n_5/s$) in each event to produce data sets with varying CME signal strengths. Additionally, a 33$\%$ local charge conservation (LCC) is implemented in each event. These data sets are analyzed using CME-sensitive two- and three-particle correlators. Furthermore, the Sliding Dumbbell Method (SDM) is employed to identify potential CME-like events within each data set. The identified events selected using the SDM exhibit characteristics consistent with CME. The CME fraction in these events is quantified while accounting for background contributions.