Introduction
Relativistic heavy-ion collisions create a unique environment where a quark-gluon plasma with strong collectivity is formed [1-8], accompanied by the strongest known magnetic field generated by spectator protons from the colliding nuclei [9-16]. This environment provides an ideal laboratory for studying the topological properties of the QCD vacuum and anomalous chiral transport phenomena under extreme magnetic field conditions. The chiral magnetic effect (CME), which induces electric charge separation along the magnetic field direction in systems with chiral imbalances, is crucial for detecting these phenomena [17-19].
The charge-dependent azimuthal correlation
Numerous experimental observables have been employed to detect true CME signals while minimizing the background interference in Au+Au and isobar collisions. For this purpose, a two-plane measurement method utilizing charge-dependent azimuthal correlations relative to the spectator plane (SP) and participant plane (PP) was proposed [60, 61]. This method is based on the fact that background and CME signals exhibit different sensitivities or correlations to the two planes [62]. The STAR collaboration applied this method to quantify the fraction of the CME signal within the inclusive Δγ correlation in both Au+Au and isobar collisions. For Au+Au collisions at
The remainder of this paper is organized as follows. In Sect. 2, we describe the setup of the AMPT model with an initial CME signal and outline our two-plane method for extracting the fraction of the CME signal from the inclusive Δγ. Our model results are presented and compared with measurements from the STAR experiment in Sect. 3, in which we discuss the implications of our findings for the interpretation of the experimental data and possible physical sources. Finally, Sect. 4 summarizes the main conclusions of the study.
Model and method
The AMPT model with initial CME signal
The AMPT model is a multiphase transport framework designed to simulate the four main stages of relativistic heavy-ion collisions [65-67], which includes the following components:
(1) The HIJING model provides the initial conditions. The transverse density profile of the colliding nucleus is modeled as a Woods–Saxon distribution. Multiple scatterings among the participant nucleons generate the spatial and momentum distributions of minijet partons and soft excited strings. Using a string-melting mechanism, quark plasma is generated by melting the parent hadrons.
(2) Zhang’s parton cascade (ZPC) model simulates the parton cascade stage. The ZPC model describes parton interactions via two-body elastic scattering. The parton cross-section is calculated using leading-order pQCD for gluon–gluon interactions.
(3) A quark coalescence model combines two or three nearest quarks into hadrons to simulate hadronization.
(4) A relativistic transport (ART) model simulates the stage of hadronic rescatterings, including resonance decays and all hadronic reactions involving elastic and inelastic scatterings among baryon–baryon, baryon–meson, and meson–meson interactions.
Numerous previous studies have demonstrated that the AMPT model effectively describes various experimental observables in both large and small collision systems at the RHIC and LHC [65-74].
According to the methodology described in Ref. [75], we implemented a CME-like charge separation mechanism in the initial partonic stage of the AMPT model. The CME signal strength can be controlled by adjusting the percentage p, which defines the fraction of quarks participating in the CME-like charge separation. The percentage p is defined as follows:
Spectator and participant planes
The two-plane method utilizes distinct plane correlations, that is, the elliptical flow-driven background is predominantly correlated with the PP, whereas the CME signal exhibits a stronger correlation with the SP [60, 61]. The SP and PP can be reconstructed using the following equations:
Figure 1 presents the centrality dependence of v2{PP} and v2{SP} for charged hadrons with 0.2<pT<2.0 GeV / c and |η|<1, obtained from the AMPT model with varying CME strengths in Au+Au collisions at

Figure 2 shows the ratios of v2{PP} and v2{SP} for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions. Note that all the calculations for the Ru+Ru and Zr+Zr collisions were taken from Ref. [64]. Because the CME is more likely to occur at centrality bins of 20–50%, and to avoid large errors, the comparison is restricted to these centrality bins. The ratio of v2{PP} is larger than that of v2{SP}, which is consistent with the experimental trends. Compared with the experimental data, a relatively larger ratio in our results arises because the v2{PP} and v2{SP} values calculated from our isobar collision simulations are smaller than the experimental results. Similarly, the v2{PP} and v2{SP} ratios of Au+Au to Ru+Ru collisions are smaller than those of Au+Au to Zr+Zr collisions, reflecting the influence of the nuclear structure. This indicates that the v2{PP} and v2{SP} values for Ru+Ru collisions are larger than those for Zr+Zr collisions owing to the nuclear structure effect [54, 64]. In the 20–50% centrality bin, the changes in v2{PP} and v2{SP} values for Au+Au collisions are mere; however, in isobar collisions, the v2{PP} and v2{SP} values decrease with increasing p [64], resulting in an increase in the v2{PP} and v2{SP} ratio with the strength of the CME.

Two-plane method to extract fCME
This subsection presents the original two-plane method for detecting and extracting the fraction of the CME signal and its optimization using the AMPT model. The experimentally measurable CME observable, denoted as Δγ, consists of the CME signal and background effect. These background effects are predominantly attributed to the elliptic flow and non-flow effects, which originate from the resonance decays and jet correlations. Consequently, the experimentally measured observable with respect to different planes can be mathematically expressed as the sum of two components:
Results and Discussions
This section presents the AMPT model results, focusing on the charge-dependent azimuthal correlations for charged particles relative to both the SP and PP. For comparison with the measurements from the STAR experiment, we used kinetic cuts of 0.2<pT<2.0 GeV/c and |η|<1, which are consistent with the STAR experimental setup.
Figure 3 shows the centrality dependence of Δγ{PP} and Δγ{SP} from the AMPT model with varying CME strengths in Au+Au collisions at

Figure 4(a) and (b) present the centrality dependence of the Δγ{PP} and Δγ{SP} ratios for Au+Au collisions relative to the Ru+Ru and Zr+Zr collisions, respectively. Considering the effect of errors, both the experimental and theoretical results indicate that the Δγ value for Au+Au collisions is smaller than that for isobar collisions, because most of the ratios are less than one. For the ratio of Δγ{PP} in Fig. 4(a), the AMPT results without the CME signal agree closely with the experimental results, whereas for the ratio Δγ{SP} in Fig. 4(b), the AMPT results with the CME signal show better agreement with the experimental results. As the CME signal correlates more strongly with the SP than with the PP, we observe that the ratio of Δγ{SP} in Fig. 4(b) decreases with increasing CME strength. This suggests that Δγ{SP} in isobar collisions increases more rapidly than that in Au+Au collisions as the CME strength increases.

Figure 5 shows the centrality dependence of


Figure 7 shows the centrality dependence of the A and a ratios for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions, respectively. The ratio of a remains nearly unchanged, which is consistent with the experimental data within error. An a ratio greater than one indicates that the

Figure 8 shows A/a as a function of the centrality predicted by the AMPT model with varying CME strengths. According to Eqs. (9) and (12), A/a values greater than unity indicate the presence of a CME signal within the Δγ observable. Focusing on mid-central collisions (20–50% centrality), where the CME effect is more measurable, A/a>1 is observed for all cases except when p=0 and p=2%. Notably, A/a increases with CME strength, suggesting that this ratio reflects the strength of the CME signal. The experimental data are closer to the cases with lower strengths of the CME signal.

Figure 9 shows the centrality dependence of the A/a ratios for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions. Focusing on mid-central collisions (20–50% centrality), the A/a ratios for the Au+Au and isobar collisions exhibit a trend similar to that of the A ratio shown in Fig. 7, driven by a smaller variation in a and larger variation in A. The experimental data are also closer to the cases with lower strengths of the CME signal.
Figure 10 shows the centrality dependence of a and b calculated using Eq. (13), based on the AMPT model with varying CME strengths. Notably, a and b exhibit significant differences. In the 20–50% centrality bins, b remains consistently smaller than a. Moreover, a shows minimal dependence on CME strength, as presented in Fig. 5. By contrast, b reflects the capability of the PP method to capture the CME signal observed in the SP method. Although the statistical errors are substantial, b shows no significant variation with CME strengths, except for the 2% CME strength case, which is excluded because of its large statistical uncertainties.

Figure 11 shows the centrality dependence of the a and b ratios for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions, respectively, based on the AMPT model with various CME strengths. Focusing on the 20–50% centrality bins, the a ratio remains nearly unchanged and is smaller than the b ratio. The uncertainties of b ratios are large. According to Eq. (13), a larger b value indicates a smaller difference in the net CME strength between the two planes. Therefore, our results indicate that the difference is smaller in Au+Au collisions than in isobar collisions.

Figure 12 shows the centrality dependence of the b/a ratio as predicted by the AMPT model with varying CME strengths. Focusing on the 20–50% centrality bins in Au+Au collisions at

Figure 13 shows the centrality dependence of b/a for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions, respectively, based on the AMPT model with varying CME strengths. Because the value of

The upper panel of Fig. 14 shows the centrality dependence of the two types of fCME based on the AMPT model with varying CME strengths. The open and solid symbols represent fCME and fCME{b} calculated using Eqs. (9) and (12), respectively. Our results are consistent with the STAR experimental data [32], favoring the cases of p=0% and p=2%. Notably, for the 20–50% centrality bins, when

Figure 15 shows the fCME, fCME{b}, and fCME{p} ratios for Au+Au collisions relative to Ru+Ru and Zr+Zr collisions, respectively, in the 20–50% centrality bins at

As the introduced CME signal strength increases, the ratios calculated using all the three methods decrease. This is because the A/a value increases more significantly in isobar collisions than in Au+Au collisions, leading to a reduction in the calculated ratios. It is also observed that the Au/Ru ratio is smaller than the Au/Zr ratio in the presence of CME signals, indicating that the fraction of CME signal is higher in Ru+Ru than in Zr+Zr.
The preceding results demonstrate that the ratio b/a = 0.88(± 0.08) significantly influences the final result of fCME in the 20–50% centrality bins for Au+Au collisions. To elucidate the origin of this relationship, we investigated the evolution of a and b at different stages of the Au+Au collisions at

In Ref. [75], the authors demonstrated that the final-state interactions in relativistic heavy-ion collisions significantly suppress the initial charge separation, with a reduction factor reaching up to an order of magnitude. In our previous work [64], we found that, because of the anisotropic overlap zone, these interactions not only reduce the magnitude of the CME current but also alter its direction, resulting in a modified maximum current orientation. Figure 17 shows the centrality dependence of the b/a ratio in the Ru+Ru [64] and Au+Au collisions at

To constrain the CME strengths across Au+Au and isobar collisions simultaneously, we performed a chi-square analysis using the following method. We aimed to compare the CME observable between our results with different CME strengths and the experimental data for those three collision systems simultaneously. The chi-square for a CME observable O in centrality bin i is defined as follows:

Summary
Using a multiphase transport model with varying CME strengths, we extended our two-plane method analysis from isobar to Au+Au collisions, both at
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