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

Jagbir Singh, Anjali Sharma, Ankita Nain, Madan M. Aggarwal

TL;DR

The paper investigates CME signals in heavy-ion collisions using AVFD simulations for $Au+Au$, $Ru+Ru$, and $Zr+Zr$ at $ abla s_{NN}=200$ GeV, varying CME strength with the axial charge per entropy density $n_5/s$ and including $33\%$ local charge conservation. It introduces the Sliding Dumbbell Method (SDM) to identify event-by-event CME-like configurations by scanning the azimuthal plane with a dumbbell region of width $ abla\phi=90^\u00b0$ and computing charge-separation metrics $Db_{+-}$ and $f_{DbCS}$, while estimating backgrounds via charge-shuffle and correlated components. By analyzing CME-sensitive observables, notably the three- and two-particle correlators $b3$ and $bDelta\gamma$ as a function of $f_{DbCS}$, the authors extract a CME fraction $f_{CME}$ in the top $f_{DbCS}$ bins and show it increases with $n_5/s$, particularly for $Au+Au$; they also caution that $33\%$ LCC can mimic CME signals, especially in low-multiplicity isobars. The study demonstrates SDM as a promising tool for isolating CME signals in experimental data and highlights the importance of careful background treatment when interpreting isobar results.

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.

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

TL;DR

The paper investigates CME signals in heavy-ion collisions using AVFD simulations for , , and at GeV, varying CME strength with the axial charge per entropy density and including local charge conservation. It introduces the Sliding Dumbbell Method (SDM) to identify event-by-event CME-like configurations by scanning the azimuthal plane with a dumbbell region of width and computing charge-separation metrics and , while estimating backgrounds via charge-shuffle and correlated components. By analyzing CME-sensitive observables, notably the three- and two-particle correlators and as a function of , the authors extract a CME fraction in the top bins and show it increases with , particularly for ; they also caution that LCC can mimic CME signals, especially in low-multiplicity isobars. The study demonstrates SDM as a promising tool for isolating CME signals in experimental data and highlights the importance of careful background treatment when interpreting isobar results.

Abstract

The Anomalous Viscous Fluid Dynamics (AVFD) framework is utilized to generate , , and collision events at = 200 GeV to investigate the Chiral Magnetic Effect (CME). The CME signal is modulated through the axial charge per entropy density () 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.

Paper Structure

This paper contains 7 sections, 9 equations, 10 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Sliding Dumbbell Method
  3. Background Estimation
  4. Data Analyzed
  5. Results and discussion
  6. Analyzing data using Sliding Dumbbell Method
  7. Summary

Figures (10)

  • Figure 1: Pictorial representation of the transverse plane with hits of positive (+) and negative (-) charge particles in an event. The dumbbell is shown in solid red line while the slid dumbbell is displayed in dotted green line.
  • Figure 2: (Color Online) Three-particle $\gamma$-correlator (top left), two-particle $\delta$-correlator (top right), and $\Delta\gamma$ (bottom) for AVFD generated $Ru+Ru$, $Zr+Zr$ and $Au+Au$ collisions at $\sqrt{s_{\mathrm NN}}$ = 200 GeV versus $n_5/s$ for 30-40$\%$ collision centrality. The $\Delta\gamma$ plot (bottom) also includes charge shuffle ($\Delta\gamma_{ChS}$) values. Markers are slightly shifted along the x-axis for clarity. Statistical uncertainties are small and are within the marker size.
  • Figure 3: (Color Online) In-plane and out-of-plane correlations for opposite sign (left) and same sign (right) charge pairs versus $n_5/s$ for the 30-40$\%$ collision centrality. Markers are slightly shifted along the x-axis for clarity. Statistical uncertainties are small and are within the marker size.
  • Figure 4: (Color Online) Flow chart displaying various steps involved in computing $\gamma$ and $\delta$ correlators employing the SDM.
  • Figure 5: $f_{DbCS}$ distributions for AVFD generated $Au+Au$ (left) and $Ru+Ru$ (right) collisions at $\sqrt{s_{\mathrm NN}}$ = 200 GeV. The rightmost side of the distribution represents the highest charge separation (0-10$\%$$f_{DbCS}$) and the leftmost side of the distribution represents the lowest charge separation (90-100$\%$$f_{DbCS}$).
  • ...and 5 more figures