logo

The medium temperature dependence of jet transport coefficient in high-energy nucleus-nucleus collisions

NUCLEAR PHYSICS AND INTERDISCIPLINARY RESEARCH

The medium temperature dependence of jet transport coefficient in high-energy nucleus-nucleus collisions

Man Xie
Qing-Fei Han
En-Ke Wang
Ben-Wei Zhang
Han-Zhong Zhang
Nuclear Science and TechniquesVol.35, No.7Article number 125Published in print Jul 2024Available online 16 Jul 2024
78702

The medium-temperature T dependence of the jet transport coefficient q^ was studied via the nuclear modification factor RAA(pT) and elliptical flow parameter v2(pT) for large transverse momentum pT hadrons in high-energy nucleus-nucleus collisions. Within a next-to-leading-order perturbative QCD parton model for hard scatterings with modified fragmentation functions due to jet quenching controlled by q^, we check the suppression and azimuthal anisotropy for large pT hadrons, and extract q^ by global fits to RAA(pT) and v2(pT) data in A + A collisions at RHIC and LHC, respectively. The numerical results from the best fits show that q^/T3 goes down with local medium temperature T in the parton jet trajectory. Compared with the case of a constant q^/T3, the going-down T dependence of q^/T3 makes a hard parton jet to lose more energy near Tc and therefore strengthens the azimuthal anisotropy for large pT hadrons. As a result, v2(pT) for large pT hadrons was enhanced by approximately 10% to better fit the data at RHIC/LHC. Considering the first-order phase transition from QGP to the hadron phase and the additional energy loss in the hadron phase, v2(pT) is again enhanced by 5%-10% at RHIC/LHC.

Jet quenchingjet transport parameterhadron suppressionelliptic flow coefficientenergy loss asymmetry.
1

Introduction

The suppression and azimuthal anisotropy of the high transverse momentum (pT) hadrons are two valuable pieces of evidence for the existence of the quark-gluon plasma (QGP) that might be created in high-energy nucleus-nucleus collisions performed at both the Relativistic Heavy-Ion Collider (RHIC) [1-3] and the Large Hadron Collider (LHC) [4-12]. When high-energy partons propagate through the color-deconfined QGP medium, they encounter multiple scatterings and lose energy through medium-induced gluon radiation. Then, the final state hadrons observed in the nucleus-nucleus (A + A) collisions are suppressed compared to those observed in proton-proton (p + p) collisions. In general, the suppression strength is given by the nuclear modification factor RAA(pT) defined as the ratio of single hadron spectrum in A + A collisions to that in p + p collisions. In a typical noncentral A + A collision, the initial geometric anisotropy can be converted into the azimuthal anisotropy in the gluon density distribution of the produced QGP medium, which leads to azimuthal anisotropy of the total energy loss for energetic jets owing to the path length and gluon density dependence of the jet energy loss. To characterize this anisotropy, one can introduce the elliptic flow coefficient v2(pT), which is defined as the second-order Fourier coefficient in the azimuthal angular distribution of the final-state high pT hadrons. Both of the two observables RAA(pT) and v2(pT) for large pT hadrons are the consequence of jet quenching or energy loss [13-20], which are expected to give a consistent jet quenching description.

The strength of the jet energy loss is controlled by the jet transport coefficient q^, which is proportional to the medium gluon number density ρ and is defined as the average transverse momentum broadening qT squared per unit length for a jet propagating inside the medium [21]: q^=ρdqT2dσdqT2qT2. (1) Quantitative extraction of the energy loss parameter was first performed by the JET Collaboration, utilizing different theoretical models and different approximations compared to experimental data for single hadron production at RHIC and LHC [22]. For simplicity, q^/T3 is generally assumed to be constant when studying bulk matter evolution [23] and the suppression of large pT single hadron and dihadron production [24, 25]. The jet transport coefficient and mean free path at the initial time were simultaneously extracted for the jet energy loss [26]. A comparison of the extracted q^/T3 for different initial temperatures in the center of the QGP between the RHIC and LHC cases indicated that q^/T3 decreased slightly with increasing medium temperature [22-26]. MARTINI [27], MCGILL-AMY [28] and other theoretical studies [29, 30] yielded similar conclusions. In fact, perturbative studies with resummed hard thermal loops in finite-temperature QCD have given rise to an additional temperature dependence of q^/T3 for a fixed strong coupling constant [31, 32]. CUJET model [33, 34] considered there might exist a strong dependence of q^/T3 on temperature and tried to give a systemic description on RAA(pT) and v2(pT) simultaneously with a Gaussian-like temperature dependence form of q^/T3 [35, 36] within the opacity expansion energy loss formalism [37]. There were also many other descriptions and developments for the jet quenching parameter, such as the radiative corrections to q^ [38-40] and nonperturbative calculations for it using the AdS/CFT correspondence at strong coupling in string theory [41-43] and lattice approaches [44-47]. Recently, with the newly developed Bayesian analysis, JETSCAPE studied the medium temperature, virtuality, and jet energy dependence of q^ via single hadron suppression at RHIC and LHC energies [48]. Meanwhile, the LIDO model [49] and JETSCAPE [50] also extracted the q^ value using two types of observables, single inclusive hadron and jet suppression. In Ref. [51], with non-parametric prior distribution of q^, using single hadron production, dihadron, and γ-hadron correlation data calibrated the temperature-dependent q^. All these studies indicate that q^/T3 should have a larger value at critical temperature Tc.

In this study, we investigated the additional temperature dependence of q^/T3 by comparing theoretical calculations with experimental data for both RAA(pT) and v2(pT) at large pT at RHIC and LHC. To reveal a clear tendency for the additional temperature dependence, we assume a linear or Gaussian distribution form for the temperature dependence of q^/T3 within a high-twist energy-loss formalism [52-54]. A (3+1)d ideal hydrodynamic description of the bulk matter evolution is used for the medium expansion, which was outputted in references [55, 56] for Au + Au collisions at 200 GeV and Pb + Pb collisions at 2.76 TeV. The initial conditions for the ideal hydrodynamic equations were fixed, such that the final bulk hadron spectra from the experiments were reproduced. To fit both RAA(pT) and v2(pT) simultaneously, we first consider only the QGP phase for the jet energy loss, and then the hadron phase contribution [23] is also included. Our calculations provide a good description of RAA(pT) for different temperature-dependent schemes of q^/T3, whereas the theoretical results for v2(pT) underestimate the experimental data. However, compared to the case with a constant q^/T3, we find that the going-down temperature dependence of q^/T3 gives an approximately 10% rise to v2(pT) in the QGP phase, and an additional 10% rise at RHIC and a 5% rise at the LHC when hadron phase contribution is included.

The remainder of this paper is organized as follows. We first review the next-to-leading-order (NLO) perturbative QCD (pQCD) parton model with medium-modified fragmentation functions in Sec. 2. Then shown in Sec. 3 and Sec. 4 are our numerical results fitted to RAA(pT) and v2(pT) data for the linear and Gaussian temperature dependence of q^/T3 in QGP phase, respectively. In Sec. 5 the hadron phase contribution is included in the linear temperature dependence of q^/T3. Finally, we conclude this paper in Sec. 6 with a summary.

2

NLO pQCD parton model with modified fragmentation functions

Within the NLO pQCD parton model, the collinear factorized differential cross section of single hadron production in p + p collisions can be factorized into the convolution of parton distribution functions (PDFs), short-distance partonic cross sections, and fragmentation functions (FFs) [57, 58], dσpphdyd2pT=abcddxaddxbfa/p(xa,μ2)fb/p(xb,μ2)×1πdσabcddt^Dch(zc,μ2)zc+O(αs3), (2) where fa/p(xa,μ2) is the parton distribution function for parton a with momentum fraction xa from a free nucleon and CT14 parameterization is used [59]. The fragmentation functions Dch(zc,μ2) for a parton in vacuum is given by the AKK parameterization [60], in which zc is the momentum fraction carried by the outgoing hadrons from the parent parton c. dσ(abcd)/dt^ is the parton-parton hard-scattering cross section at LO αs2. The partonic scattering cross sections in our numerical simulations were computed up to the NLO implied in O(αs3). The NLO corrections include 1-loop contributions to 22 tree level and 23 tree level contributions. More detailed discussions on the NLO calculations can be found in [61].

In A + A collisions, the cross section for single hadron production at high transverse momentum is given by [62, 63] dNAAhdyd2pT=abcdd2rtA(r)tB(r+b)dxadxb×fa/A(xa,μ2,r)fb/B(xb,μ2,r+b)×1πdσabcddt^D˜ch(zc,μ2,ΔEc)zc+O(αs3), (3) where tA(r)=ρA(r)dz is the nuclear thickness function given by the Woods–Saxon distribution and is normalized as d2rtA(r)=A. fa/A(xa,μ2,r) is the nucleus-modified parton distribution function, which is assumed to be factorized into parton distributions in a free nucleon fa/N(xa,μ2) and the nuclear shadowing factor Sa/A(xa,μ2,r) [64, 65], fa/A(xa,μ2,r)=Sa/A(xa,μ2,r)[ZAfa/p(xa,μ2)+(1ZA)fa/n(xa,μ2)], (4) where Z is the proton number of the nucleus and A is the nuclear mass number. Assuming that the shadowing is proportional to the local nuclear density, the shadowing factor Sa/A(xa,μ2,r) can be obtained using the following form [66, 67]: Sa/A(xa,μ2,r)=1+[Sa/A(xa,μ2)1]AtA(r)d2r[tA(r)]2, (5) where Sa/A(xa,μ2) is obtained from the EPPS16 [68].

The medium-modified fragmentation function D˜ch can be calculated as follows [62, 63, 69-71]: D˜ch(zc,μ2,ΔEc)=(1eNg)[zczcDch(zc,μ2)+NgzgzcDgh(zg,μ2)]+eNgDch(zc,μ2), (6) where zc=pT/pTc is the momentum fraction for a parton fragmenting into a hadron in vacuum. zc=pT/(pTcΔEc) is the rescaled momentum fraction and denotes that a parton with pTc propagating through the medium loses energy ΔEc and fragments into a hadron with pT. zg=pT/(ΔEc/Ng) is the momentum fraction of the radiated gluon fragmenting into a hadron. Ng is the number of radiated gluons.

The parton energy loss caused by the medium-induced gluon radiation can be calculated using a higher-twist (HT) approach [52-54]. For a light quark c with an initial energy E, the radiative energy loss Δ Ec can be calculated as ΔEcE=2CAαsπdτdlT2lT4dz×[1+(1z)2]q^sin2(lT2τ4z(1z)E), (7) where CA=3, αs is the strong coupling constant, and lT is the transverse momentum of the radiated gluons. We assume that the energy loss of a gluon is 9/4 times that of a quark owing to the different color factors for the quark-gluon vertex and gluon-gluon vertex [52]. The average number of radiated gluons from the propagating hard parton is calculated as [72]: Ng=2CAαsπdτdlT2lT4dzz×[1+(1z)2]q^ sin2(lT2τ4z(1z)E). (8) The HT formalism contains the transverse momentum lT of the radiated gluon, which also indicates the changes in the transverse momenta of the partons [73, 74, 15]. In our numerical simulations, we adopt the small angle approximation within the collinear factorization theorem, according to Eq. (3). Consequently, we focused solely on the effect of energy loss and assumed that the parton direction remains unchanged in the fragmentation functions. Such an approximation has been used in many current jet energy-loss formalisms and has successfully explained experimental data [49, 50, 75-78].

The parton energy loss and number of radiated gluons are both controlled by the jet transport parameter q^ [21]. According to Eq. (1) for q^ proportional to the medium gluon density ρ, one can simply assume a constant value for the scaled jet transport parameter [25, 26]: q^T3=q^0T03pμuμp0, (9) where is the four momentum of the parton, is the local four flow velocity of the fluid, T is the local temperature of the medium and T0 is a reference temperature taken as the highest temperature at the center of the medium at the initial time τ0.

For an additional T-dependence of q^/T3, one can simply assume a linear form such as q^/T3aT+b. In the following actual calculations, we write the linear form as q^T3=[(q^0T03q^cTc3)TTcT0Tc+q^cTc3]pμuμp0. (10) We also check the additional T dependence of q^/T3 in the Gaussian form: q^T3=q^0T03e(T/Tc1)2/(2σT2/Tc2)e(T0/Tc1)2/(2σT2/Tc2)pμuμp0. (11) Parameters q^0, q^c, and σT were introduced to adjust the strength of the additional temperature dependence. Tc = 170 MeV is the critical temperature. When T = T0 in Eq. (10) and σT2= for Eq. (11), both equations return to Eq. (9).

To describe jet quenching in high-energy nucleus-nucleus collisions, it is necessary to provide the space-time evolution of the jet transport coefficient in Eq. (9, 10, 11) along the parton propagation. In our studies, the dynamic evolution of the medium that governs the space-time evolution of the local temperature T and flow velocity u was obtained using a (3+1)-dimensional hydrodynamic model [55, 56]. This model provides results on the transverse dynamics of the bulk medium in A + A collisions under the initial conditions. Furthermore, the model includes the first-order phase transition between the QGP and hadron phases at Tc = 170 MeV and provides the hadron phase fraction f(r), which is defined as f(r)={0if T>170 MeV,01if T=170 MeV,1if T<170 MeV, (12) where r denotes the local position of jet. As the geometric position moves closer to the periphery of the medium or the medium evolution time increases, the hadronic phase fraction gradually increases from 0 to 1 at Tc = 170 MeV, which is determined by the proportion of the hadron and parton number density [79, 55, 80]. The energy loss of the jet propagating through both the QGP and hadronic phases can be simultaneously described using the higher-twist approach, except that q^ in the separate phase is different. To include the contributions to q^ from both QGP and hadron phases, we changed Eq. (9), (10), and (11) as follows: q^T3q^T3(1f)+q^hT3f, (13) where q^h is the jet transport parameter of the hadronic phase. By combining Eq. (12), one can see that, for studies exclusively concerning the QGP phase, we consider a pure partonic medium at T>170 MeV, along with the QGP fraction (1-f) in the mixed phase at Tc=170 MeV. For studies on the hadronic phase, we only need to consider the q^hT3f term, which accounts for the contributions from the hadronic phase during the mixed phase, as well as the entire hadronic medium when the temperature is below 170 MeV, until the system reaches dynamic freeze-out. When the hadron phase was considered for the jet energy loss, the extracted jet transport parameter for the QGP phase was reduced owing to the long evolution time of the mixed phase, as shown in Ref. [23].

The jet transport parameter in the hadron phase can be expressed as follows [23]: q^h=q^NρN[23MρM(T)+MρB(T)], (14) where q^N0.02 GeV2/fm is the extracted jet transport parameter at the center of the cold nucleonic matter of a large nucleus and ρN0.17 fm-3 is the nucleon density at the center of the large nucleus [52]. ρM and ρB are the meson and baryon density in the hadronic resonance gas at a given temperature, respectively. Factor 2/3 represents the ratio of the constituent quark numbers of the meson and the baryon. The hadron density at a given temperature T and zero chemical potential is expressed as [23] hρh(T)=T32π2h(mhT)2n=1ηhn+1nK2(nmhT), (15) where ηh=± for mesons (M)/baryons (B). In the following calculations, hadron resonances with masses below 1 GeV were included: 17 types of mesons: π+,π,π0,K+,K,K0,K0¯,η,η',ρ+,ρ,ρ0,K*+, K*,K*0,K*0¯,ω; and 2 kinds of baryons, p, n. Here, we ignore the contribution of antinucleons to q^h, which is less than 3%.

3

Linear temperature dependence of q^/T3 in QGP phase

With the spectrum in p + p collisions as a baseline, the nuclear suppression factor RAA(pT) for single hadron production in A + A collisions can be expressed as [71, 81], RAA(pT)=dNAAh/dyd2pTTAA(b)dσpph/dyd2pT, (16) where TAA(b)=d2rtA(r)tB(r+b) is the overlap function of the two colliding nuclei.

The anisotropy of the final-state hadrons in the transverse momentum can be quantified using the Fourier expansion of the hadrons distribution in the azimuthal angle. We focus on the second Fourier coefficient, namely elliptic anisotropy coefficient v2(pT), which can be written as [82-87], v2(pT)=ππdϕcos(2ϕ)dNAAh/dyd2pTdϕππdϕdNAAh/dyd2pTdϕ, (17) where ϕ is the jet azimuthal angle between the jet propagation direction and the impact parameter.

In this section, we will use Eq. (10) and (13) with q^h=0 to consider the linear temperature dependence of q^/T3 in QGP phase. χ2 fitting to both RAA(pT) and v2(pT) for hadrons in the middle rapidity region will be performed for different introduced parameters, which is given by χ2=i=1N[(VthVexp)2/(σsys2+σstat2)], (18) where Vth and Vexp denote the theoretical and experimental results, respectively, and σsys and σstat provide the systematic and statistical errors for the data, respectively. For a global fit of both RAA(pT) and v2(pT), the data number N for the degrees of freedom (d.o.f.) is the sum of RAA(pT) and v2(pT) data numbers. The χ2/d.o.f value was minimized to near unity to determine the best-fit temperature dependence of q^/T3 [36]. In the χ2/d.o.f calculations, we selected only the experimental data points with pT>7.5 GeV/c at both RHIC and the LHC energies to ensure the validity of pQCD parton model.

3.1
Fit RAA and v2 at RHIC

Current studies indicate that q^c/Tc3 at the critical temperature has a larger value, and that the value of q^0/T03 at the highest temperature is smaller. Therefore, we first choose q^c/Tc3[3.0,9.0] and q^0/T03[0.2,5.6] with a bin size of 0.3 and get 399 pairs of (q^c/Tc3,q^0/T03) for Eq. (10) and (13), with q^h=0. To determine the limit value of q^0/T03, we can expand it to zero. Therefore, we make 420 times of calculations for the suppression factor RAA(pT) as a function of pT for single hadrons produced in the most central 0–5% Au + Au collisions at sNN=200 GeV. Each result for RAA(pT) with a given pair of (q^c/Tc3,q^0/T03) provides a value of χ2/d.o.f to fit the experimental data for RAA(pT) [1, 2]. As shown in Fig. 1 (a) is such a 2-dimensional figure for χ2/d.o.f as functions of (q^c/Tc3,q^0/T03). Different colors represent different fitting values. The χ2/d.o.f value was minimized to near unity to determine the best-fitting couples of (q^c/Tc3,q^0/T03).

Fig. 1
(Linear-dependence) Panel (a): The χ2/d.o.f analyses for single hadron RAA(pT) as a function of q^c/Tc3 and q^0/T03 from fitting to PHENIX data [1, 2] in the most central 0-5% Au + Au collisions at sNN=200 GeV. Panel (b): The scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of the panel (a). Panel (c): The single hadron suppression factors RAA(pT) with couples of (q^c/Tc3,q^0/T03)=(7.2,0.0) (red solid curve) and (5.6,5.6) (blue dashed curve) compared with PHENIX [1, 2] data
pic

The best fit given by the red region indicates that the single hadron RAA(pT) is more sensitive to the value of q^c/Tc3 than q^0/T03. However, the fitting fails to obtain a unique pair of (q^c/Tc3,q^0/T03) for an explicit dependence form of q^/T3 on T only through the constraint of single hadron RAA(pT). To demonstrate the different linear temperature dependencies of q^/T3 for the same suppression of single hadrons, in Fig. 1 (b) we draw the gray dashed curves for q^/T3 as a function of T, which are constrained by the best-fitting region of χ2/d.o.f.

Among the gray dashed curves, we choose one horizontal line (blue) for a constant q^/T3 with (q^c/Tc3,q^0/T03)=(5.6,5.6) and one leaning line (red) for a linear T dependence of q^/T3 with (q^c/Tc3,q^0/T03)=(7.2,0.0). Using these two pairs of (q^c/Tc3,q^0/T03), we obtain almost the same RAA(pT) as in Fig. 1 (c) which shows that the single hadron suppression is a consequence of total jet energy loss and is not sensitive to the T dependence of q^/T3 in central Au + Au collisions.

Due to the jet path length and medium density dependence in the jet trajectory inside the hot medium, the jet energy loss in noncentral Au + Au collisions exhibits azimuthal anisotropy. The hadron suppression depends on the azimuthal angle concerning the reaction plane, thus leading to azimuthal anisotropy in the high-pT hadron spectra. The same energy loss mechanism permits to perform a global fit to constrain (q^c/Tc3,q^0/T03) with both the suppression factor RAA(pT) and elliptic flow parameter v2(pT) for large pT hadrons in noncentral A + A collisions. With the same couples of (q^c/Tc3,q^0/T03) as in 0-5% centrality, we simultaneously make 420 times of calculations for RAA(pT) and v2(pT) as a function of pT to fit to the experimental data [1-3] in 20-30% Au + Au collisions, and get the χ2/d.o.f results for RAA(pT) as shown in Fig. 2(a) and v2(pT) in Fig. 2(b), respectively. The χ2/d.o.f fitting for RAA in noncentral collisions is similar to that in central collisions. This implies that only RAA(pT) constraint does not give an explicit dependence form of q^/T3 on T. The χ2/d.o.f fitting of v2 in Fig. 2 (b) shows that the data of elliptic flow v2(pT) favor larger q^c/Tc3 and are almost insensitive to q^0/T03. Global χ2/d.o.f fitting was performed for both RAA(pT) and v2(pT) in Fig. 2 (c) in which the limited yellow region is found to constrain (q^c/Tc3,q^0/T03).

Fig. 2
(Linear-dependence) The χ2/d.o.f analyses for single hadron RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) as a function of q^c/Tc3 and q^0/T03 from fitting to experimental data [1-3] in 20-30% Au + Au collisions at sNN=200 GeV. The global χ2/d.o.f fitting results for both RAA(pT) and v2(pT) are shown in the panel (c)
pic

Figure 3 (a) is the scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of global χ2 fits of Fig. 2(c). The blue dashed curve is also for the constant-dependence case with (q^c/Tc3,q^0/T03)=(5.6,5.6), and the red solid curve for a linear T dependence of q^/T3 with (q^c/Tc3,q^0/T03)=(6.9,0.0). These two dependence forms yielded almost the same RAA(pT) as shown in Fig. 3(b), which is similar to the situation in central collisions. However, these two dependencies of q^/T3 provide different contributions to v2(pT) as shown in Fig. 3(c). Numerical results show that the linearly-decreasing T dependence of q^/T3 with (q^c/Tc3,q^0/T03)=(6.9,0.0) makes an enhancement by 10% for v2(pT) comparing to the constant dependence case with (q^c/Tc3,q^0/T03)=(5.6,5.6). This linearly decreasing T-dependence of q^/T3 with (q^c/Tc3,q^0/T03)=(6.9,0.0) indicates that more energy loss occurs near the critical temperature Tc.

Fig. 3
(Linear-dependence) Panel (a): the scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of global χ2 fits of Fig. 2 (c) in 20-30% Au + Au collisions at sNN=200 GeV. The single hadron suppression factors RAA(pT) and elliptic flow v2(pT) are shown in panel (b) and (c), respectively, with couples of (q^c/Tc3,q^0/T03)=(6.9,0.0) (red solid curve) and (5.6,5.6) (blue dashed curve) compared with PHENIX [1-3] data
pic
3.2
Fit RAA and v2 at the LHC

Similarly, we present the relevant results for the Pb + Pb collisions at sNN=2.76 TeV. Here, we choose q^c/Tc3[1.2,8.1] and q^0/T03[0.2,6.5] with the same bin size of 0.3, and further include q^0/T03=0.0 to obtain 552 couples of (q^c/Tc3,q^0/T03) for Eq. (10) and (13), with q^h=0. The χ2/d.o.f results for central 0–5% Pb + Pb collisions were performed on single hadron suppression factors, as shown in Fig. 4 (a). The best-fitting contour is similar to that shown in Fig. 1 (a) but with a smaller q^c/Tc3. With constant and linear forms for q^/T3, we again obtain the same single hadron suppression, as shown in Fig. 4 (b).

Fig. 4
(Linear-dependence) Panel (a): The χ2/d.o.f analyses for single hadron RAA(pT) as a function of q^c/Tc3 and q^0/T03 from fitting to experimental data [4, 5] in the most central 0-5% Pb + Pb collisions at sNN=2.76 TeV. Panel (b): The single hadron suppression factors RAA(pT) with couples of (q^c/Tc3,q^0/T03)=(5.1,0.0) (red solid curve) and (3.6,3.6) (blue dashed curve) compared with experimental data
pic

For 20–30% Pb + Pb collisions, χ2/d.o.f fitting for only RAA(pT) or v2(pT) and the global fitting for both are shown in Fig. 5 (a), (b) and (c), respectively. Similar to noncentral Au + Au collisions, both separated χ2/d.o.f fitting for RAA(pT) and v2(pT) cannot provide a clear constraint on the T-dependence of q^/T3. However, the difference between χ2/d.o.f(RAA), χ2/d.o.f(v2) shows that the data of v2(pT) prefer a larger jet energy loss near Tc and are insensitive to changes in q^0/T03. Consequently, the global fits for both RAA(pT) and v2(pT) impose a constraint to some extent on the T-dependence of q^/T3 as shown in Fig. 5 (c), similarly to Fig. 2 (c).

Fig. 5
(Linear-dependence) The χ2/d.o.f analyses of single hadron RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) as a function of q^c/Tc3 and q^0/T03 from fitting to experimental data [4, 5, 9, 10] in 20-30% Pb + Pb collisions at sNN=2.76 TeV. The global χ2/d.o.f fitting results for both RAA(pT) and v2(pT) are shown in the panel (c)
pic

Choosing χ2/d.o.f>1.6 in Fig. 5 (c) for the best fitting, one can get the curves for the T dependence of q^/T3 in Fig. 6 (a). We again observed a tendency for q^/T3 to decrease with an increase in the local temperature along the jet trajectory. Among the best-fitting values, selecting (q^c/Tc3,q^0/T03)=(5.4,0.0) for the linear T dependence and (4.1,4.1) for the constant dependence, we calculate the RAA(pT) and v2(pT) as a function of pT shown in Fig. 6 (b) and (c), respectively. Two almost identical RAA(pT) were obtained, whereas v2(pT) was enhanced by 10% because of the larger jet energy loss near Tc for the linearly decreasing T dependence of q^/T3 at the LHC.

Fig. 6
(Linear-dependence) In 20-30% Pb + Pb collisions at sNN=2.76 TeV, the scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of global χ2 fits of Fig. 5 (c) are shown in the panel (a). The single hadron suppression factors RAA(pT) and elliptic flow v2(pT) are shown in the (b) and (c) panels, respectively, with couples of (q^c/Tc3,q^0/T03)=(5.4,0.0) (red soild curve) and (4.1,4.1) (blue dashed curve) compared with experimental data [4, 5, 9, 10]
pic

Regardless of whether in Pb + Pb or Au + Au collisions, RAA(pT) and v2(pT) are both more sensitive to the jet energy loss near the critical temperature Tc than near the initial highest temperature T0. The data for v2(pT) prefer larger values of q^c/Tc3. Furthermore, the anisotropy of the final-state hadrons at high transverse momentum can be strengthened up to 10% by increasing the jet energy loss near Tc with a linearly decreasing T dependence of q^/T3.

3.3
Jet energy loss distribution

Given a parton jet with any creation site and any moving direction in the initial hard scattering, we consider the jet energy loss distribution when propagating through the hot medium. The average energy loss rate in the jet trajectory is given by dΔEdτ=dϕd2rtA(r)tB(r+b)dΔE(r+nτ)/dτdϕd2rtA(r)tB(r+b), (19) where ΔE(r) is given by Eq. (7), r is the initial creation point for an energy-given jet, and n is the unit vector of the jet movement direction ϕ which is the same as that in Eq. (17). The average cumulative energy loss for the jet traversing the medium is then given as ΔE(τ)=dϕd2rtA(r)tB(r+b)τ0τdτdΔE(r+nτ)dτdϕd2rtA(r)tB(r+b). (20)

Shown in Fig. 7 are the average accumulative (solid curves) and differential (dashed curves) energy loss for one 10 GeV jet with (q^c/Tc3,q^0/T03)=(6.9,0.0) (red curves) and (5.6,5.6) (blue curves) in 20-30% Au + Au collisions at sNN=200 GeV (panel (a) and (b)), and for one 100 GeV jet with (q^c/Tc3,q^0/T03)=(5.4,0.0) (red curves) and (4.1,4.1) (blue curves) in 20-30% Pb + Pb collisions at sNN=2.76 TeV (panel (d) and (e)), respectively. The medium temperature as a function of time at the center point (x,y)=(0,0) for the two collision systems is shown in the lower panels (c) and (f).

Fig. 7
(Linear-dependence) Panels (a) and (d): the average accumulative energy loss for one 10 GeV jet in 20-30% Au + Au collisions at sNN=200 GeV and for one 100 GeV jet in 20-30% Pb + Pb collisions at sNN=2.76 TeV, respectively. Panels (b) and (e): the corresponding differential energy loss. Red solid or dashed curves are for the linearly-decreasing T dependence of q^/T3, and blue for the constant q^/T3. Panels (c) and (f): the medium temperature as a function of time at the center point (x,y)=(0,0) for the two collision systems, respectively
pic

When the jet passes out of the critical region from QGP to the hadron phase, it is over for the jet to accumulate the lost energy, as shown in Eq. (13), with q^h=0. For the two well-chosen cases of constant dependence and linearly decreasing T dependence of q^/T3, the final total energy losses were similar, as shown in Fig. 7 (a) and (d). In the meantime, the peak of the jet energy loss distribution dΔE/dτ along the jet path is “pushed" to move to critical temperature Tc nearby due to the linearly-decreasing T dependence of q^/T3 (red dashed curves) compared to the constant dependence (blue dashed curves), as shown in Fig. 7 (b) and (e). More energy loss occurs as the critical temperature approaches and enhances the final hadron azimuthal anisotropy. Therefore, v2(pT) is strengthened for the linearly decreasing T dependence case, as shown in Fig. 3 (c) and Fig. 6 (c).

To clearly illustrate the enhanced azimuthal anisotropy, we define the energy loss asymmetry as follows: AΔE(τ)=ΔE(τ)ϕ=π/2ΔE(τ)ϕ=0ΔE(τ)ϕ=π/2+ΔE(τ)ϕ=0, (21) where ΔE(τ,ϕ) is given by Eq. (20), in which the ϕ integration for the azimuthal average was removed. On average, a parton jet encounters the greatest energy loss because it has the longest path length at ϕ=π/2 and the shortest at ϕ=0. Shown in Fig. 8(a) and (b) are such energy loss asymmetries for an energy-given parton jet in 20-30% Au + Au collisions at 200 GeV and Pb + Pb collisions at 2.76 TeV, respectively. The red solid curves represent the linearly decreasing T-dependence of q^/T3, whereas the blue solid curves represent the constant case. The former is 10% larger than the latter in both panels, which is similar to the enhancement in v2(pT) shown in Fig. 3(c) and 6(c).

Fig. 8
(Linear-dependence) The energy loss asymmetry between the jet propagating direction of ϕ=π/2 and ϕ=0 for one 10 GeV jet with (q^c/Tc3,q^0/T03)=(6.9,0.0) (red curve) and (5.6,5.6) (blue curve) in 20-30% Au + Au collisions at sNN=200 GeV (panel (a)) and for one 100 GeV jet with (q^c/Tc3,q^0/T03)=(5.4,0.0) (red curve) and (4.1,4.1) (blue curve) in 20-30% Pb + Pb collisions at sNN=2.76 TeV (panel (b))
pic

Owing to the medium-temperature evolution, different T dependencies of the jet transport coefficient result in different energy-loss distributions for jet propagation. The large pT hadron suppression RAA was a consequence of the total energy loss and was independent of the jet energy loss distribution. However, compared with the constant case for a given total energy loss, the linearly decreasing T dependence of q^/T3 causes an energy loss to redistribute and leads to more energy loss near the critical temperature, and therefore, a stronger azimuthal anisotropy for hadron production.

4

Gaussian temperature dependence of q^/T3 in QGP phase

In the last section, the numerical results for the linear T-dependence assumption show that q^/T3 goes down as the medium temperature increases. The going-down T dependence of q^/T3 stimulates an attempt to make a Gaussian assumption regarding the T dependence of q^/T3. We assume that the apex of the Gaussian distribution is located at critical temperature, as shown in Eq. (11). This assumption of Gaussian temperature dependence will be submitted into Eq. (13) with q^h=0 for the QGP phase only and Eq. (7) and (8) for the jet energy loss.

4.1
Fit RAA and v2 at RHIC

In Eq. (11) for the assumption of Gaussian temperature dependence, the introduced q^0/T03 remains the scaled jet transport parameter at the initial time at the center of the medium, whereas σT2/Tc2 is the squared Gaussian width. Starting with Au + Au collisions at sNN=200 GeV, we choose σT2/Tc2[0.35,3.5] with bin size 0.35, and q^0/T03[0.4,5.2] with bin size 0.4, and obtain 130 pairs of (σT2/Tc2,q^0/T03) for Eqs. (11) and (13), with q^h=0. We first obtain RAA(pT) in 0–5% collisions and compare them with the data [1, 2] to get a 2-dimensional contour plot for χ2/d.o.f, as shown in Fig. 9 (a). According to the best-fitting region obtained for (σT2/Tc2,q^0/T03), we obtained q^/T3 as a function of T in Fig. 9 (b). The red solid curve represents the downward q^/T3-dependence with (σT2/Tc2,q^0/T03)=(1.4,3.6) whereas the blue dashed curve shows a constant dependence with (σT2/Tc2,q^0/T03)=(,5.6). These two dependence forms yielded almost the same RAA(pT), as shown in Fig. 9 (c). RAA(pT) doesn’t “care" whether q^/T3 is of Gaussian temperature dependence or not at RHIC.

Fig. 9
(Gaussian-dependence) Panel (a): The χ2/d.o.f analyses for single hadron RAA(pT) as a function of σT2/Tc2 and q^0/T03 from fitting to experimental data [1, 2] in the most central 0-5% Au + Au collisions at sNN=200 GeV. Panel (b): The scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of the panel (a). Panel (c): The single hadron suppression factors RAA(pT) with couples of (σT2/Tc2,q^0/T03)=(1.4,3.6) (red solid curve) and (σT2/Tc2,q^0/T03)=(,5.6) (blue dashed curve) compared with PHENIX [1, 2] data
pic

Shown in Fig. 10 (a) and (b) are the χ2/d.o.f analyses of single hadron RAA(pT) and elliptic flow v2(pT) as functions of σT2/Tc2 and q^0/T03 from fitting to experimental data [1, 2, 3] in 20-30% Au + Au collisions at sNN=200 GeV, respectively. The global χ2/d.o.f fitting results for both RAA(pT) and v2(pT) are shown in Fig. 10(c). Although χ2/d.o.f (RAA) performs inactively for temperature dependence in 20–30%, as well as in 0–5% centrality, χ2/d.o.f (v2) expresses a great favor in the small Gaussian width, which gives q^/T3 going down more rapidly with T. Consequently, global χ2/d.o.f fits for both RAA(pT) and v2(pT) provide an explicit constraint on the introduced parameters (σT2/Tc2,q^0/T03).

Fig. 10
(Gaussian-dependence) The χ2/d.o.f analyses of single hadron RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) as a function of σT2/Tc2 and q^0/T03 from fitting to experimental data [1, 2, 3] in 20-30% Au + Au collisions at sNN=200 GeV. The global χ2/d.o.f fitting results for both RAA(pT) and v2(pT) are shown in the panel (c)
pic

With the best global fitting values for (σT2/Tc2,q^0/T03), we show the Gaussian T dependence of q^/T3 in Fig. 11 (a). Choosing the constant dependence with (σT2/Tc2,q^0/T03)=(,5.6) (blue dashed curve) and a Gaussian T dependence with (σT2/Tc2,q^0/T03)=(1.4,3.6) (red solid curve) for q^/T3, we again get the almost same RAA(pT) as shown in Fig. 11 (b), and v2(pT) with difference less than 5% in Fig. 11 (c). Compared with the case of a linearly decreasing T dependence, the two v2(pT) in Fig. 11 (c) are closer to each other because the difference between the Gaussian T dependence and the constant dependence is smaller, which leads to an almost invisible change in v2(pT).

Fig. 11
(Gaussian-dependence) In 20-30% Au + Au collisions at sNN=200 GeV, the scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of global χ2 fits of Fig. 10 (c) are shown in panel (a). The single hadron suppression factors RAA(pT) and elliptic flow parameter v2(pT) are shown in panel (b) and (c), respectively, with couples of (σT2/Tc2,q^0/T03)=(1.4,3.6) (red solid curve) and (,5.6) (blue dashed curve) compared with PHENIX [1-3] data
pic

The use of a Gaussian form for q^/T3 was intended to provide a more flexible temperature dependence by narrowing the Gaussian width compared with the linear form. Nevertheless, although v2 data favor a higher Gaussian peak, RAA fitting imposes constraints. The global χ2-fitting results for the Gaussian temperature-dependence hypothesis presented in Fig. 11(a) did not manifest a steeper decline with increasing temperature. A comparison of the red curves shown in Fig. 11(a) with that in Fig. 3(a), it is apparent that the linear temperature dependence results in a higher q^c/Tc3 at the critical temperature. Moreover, as stated previously, v2 was more sensitive to energy loss near the critical temperature. Therefore, the performance of the Gaussian shape is not significantly better than that of the linear shape.

4.2
Fit RAA and v2 at the LHC

The same process was performed for the Pb + Pb collisions at sNN=2.76 TeV. For the most central collisions, we choose σT2/Tc2[0.35,3.5] with bin size 0.35 and q^0/T03[0.2,2.4] with bin size 0.2 and get 120 couples of (σT2/Tc2,q^0/T03) to get RAA(pT) and the 2-dimensional χ2/d.o.f-fitted contour plot, as shown in Fig. 12 (a). With a constant dependence with (σT2/Tc2,q^0/T03)=(,3.6) and a Gaussian T dependence with (σT2/Tc2,q^0/T03)=(1.75,1.6), we obtain the same RAA(pT) to fit the data well, as shown in Fig. 12 (b).

Fig. 12
(Gaussian-dependence) Panel (a): The χ2/d.o.f analyses for single hadron RAA(pT) as a function of q^c/Tc3 and q^0/T03 from fitting to experimental data [4, 5] in the most central 0-5% Pb + Pb collisions at sNN=2.76 TeV. Panel (b): The single hadron suppression factors RAA(pT) with couples of (σT2/Tc2,q^0/T03)=(1.75,1.6) (red solid curve) and (σT2/Tc2,q^0/T03)=(,3.6) (blue dashed curve) compared with experimental data
pic

For 20–30% collisions, we choose σT2/Tc2[0.35,7.0] and q^0/T03[0.2,4.4] and separately obtain 440 groups of RAA(pT) and v2(pT) to perform χ2/d.o.f fitting, as shown in Fig. 13 (a) and (b), respectively. The global fits for both RAA(pT) and v2(pT) are presented in Fig. 13 (c) where the constraints for the introduced parameters (σT2/Tc2,q^0/T03) are obtained. With these constraints, the Gaussian T-dependence of q^/T3 is shown in Fig. 14 (a). Choosing a Gaussian T dependence with (σT2/Tc2,q^0/T03)=(1.05,1.2) (red solid curve) and the constant dependence with (σT2/Tc2,q^0/T03)=(,4.1) (blue dashed curve) for q^/T3, we again get almost the same RAA(pT) shown in Fig. 14 (b), and different v2(pT) in Fig. 14 (c). Compared with the constant case, the decreasing Gaussian T-dependence of q^/T3 gives v2(pT) an enhancement of approximately 10%.

Fig. 13
(Gaussian-dependence) The χ2/d.o.f analyses of single hadron RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) as a function of σT2/Tc2 and q^0/T03 from fitting to experimental data [4, 5, 9, 10] in 20-30% Pb + Pb collisions at sNN=2.76 TeV. The global χ2/d.o.f fitting results for both RAA(pT) and v2(pT) are shown in panel (c)
pic
Fig. 14
(Gaussian-dependence) In 20-30% Pb + Pb collisions at sNN=2.76 TeV, the scaled dimensionless jet transport parameters q^/T3 as a function of medium temperature T from the best fitting region of global χ2 fits of Fig. 10 (c) are shown in the panel (a). The single hadron suppression factors RAA(pT) and elliptic flow v2(pT) are shown in panels (b) and (c), respectively, with couples of (σT2/Tc2,q^0/T03)=(1.05,1.2) (red solid curve) and (4.1, 4.1) (blue dashed curve) compared with experimental data [4, 5, 9, 10]
pic

At both RHIC and the LHC, numerical results for simultaneously fitting RAA(pT) and v2(pT) show that the Gaussian T dependence of q^/T3 is smoothly going down with T and similar to the linearly decreasing T dependence of q^/T3. Compared with the constant q^/T3, the going-down T-dependence of q^/T3 enhances the hadron azimuthal anisotropy by approximately 5%-10% to improve v2(pT) to fit the data.

Thus far, we have demonstrated the constraining power of the experimental data on three temperature-dependent forms of q^/T3. To more clearly distinguish the separate constraining effects of RAA and v2, we list the best-fit parameters and corresponding minimum χ2/d.o.f values for each scenario in Table 1. These values correspond to the results shown in Figs. 2, 5, 10, and 13. For the constant form of q^/T3, v2 data are not utilized.

Table 1
Optimal parameter and corresponding χ2/d.o.f for different data sets in different q^/T3 form
  Constant Linear T dependence Gaussian T dependence
  q^c/Tc3=q^0/T03 χ2/d.o.f (q^c/Tc3,q^0/T03) χ2/d.o.f (σT2/Tc2,q^0/T03) χ2/d.o.f
20-30% Au + Au collisions at 200 GeV
RAA (5.8,5.8) 0.17 (6.9,1.1) 0.17 (2.8,4.4) 0.48
v2 (8.7,0.5) 2.39 (0.4,2.4) 2.98
(RAA+v2) (7.5,0.2) 1.51 (0.7,2.4) 2.45
20-30% Pb + Pb collisions at 2.76 TeV
RAA (4.0,4.0) 0.59 (5.0,3.6) 0.54 (4.8,3.2) 0.56
v2 (5.4,0.2) 1.52 (2.1,2.4) 1.23
(RAA+v2) (5.1,0.2) 0.94 (1.4,1.6) 1.23
Show more
Note that for the constant form of q^/T3, the v2 data were not utilized
5

Linear temperature dependence of q^/T3 in QGP and hadron phases

For the complete study of the linear temperature dependence of q^/T3, we use Eqs. (10), (13), and (14) to include the contributions from both QGP and hadron phases in 20–30% A + A collisions.

5.1
Best fits for RAA and v2 due to energy loss in QGP and hadron phases

We begin with Au + Au collisions in 20–30% centrality at sNN=200 GeV. Shown in Fig. 15 are hadron suppression factors RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) with jet energy loss of both QGP and hadronic phases (black solid curves) and of only QGP phase (red solid curves from Fig. 16) for 20-30% Au + Au collisions at sNN=200 GeV, respectively. With the same q^0/T03=0.2 shown in Fig. 3, we have to decrease the value of q^c/Tc3 from 6.9 to 5.7 due to the included hadronic phase to get the same RAA(pT). The 20% reduction in q^/T3 is consistent with Ref. [23]. The jet energy loss in the hadron phase gives an enhancement of 10% for the elliptic flow v2(pT), which means that the jet energy loss of the hadronic phase has an important and non-negligible contribution to v2(pT).

Fig. 15
(Color online) Single hadron suppression factors RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) with jet energy loss of QGP + Hadron phases (black solid curves with (q^c/Tc3,q^0/T03)=(5.7,0.0) and q^h) and of only QGP phase (red solid curves with (q^c/Tc3,q^0/T03)=(6.9,0.0) from Fig. 3) for 20-30% Au + Au collisions at sNN=200 GeV
pic

As shown in Fig. 16 is for the case of 20–30% Pb + Pb collisions at sNN=2.76 TeV. For consistency, RAA(pT) in Fig. 16 (a), the v2(pT) (black solid curve) with (q^c/Tc3,q^0/T03)=(4.5,0.0) of QGP phase and q^h of hadronic phase has an additional enhancement by 5% compared with (q^c/Tc3,q^0/T03)=(5.4,0.0) of only QGP phase (red solid curve from Fig. 6) in Fig. 16 (b). This enhancement was less than that at RHIC because the fraction of hadron phase contribution to the jet energy loss at the LHC was less than that at RHIC, as shown in Fig. 17 (a) and (d).

Fig. 16
(Color online) Single hadron suppression factors RAA(pT) (panel (a)) and elliptic flow v2(pT) (panel (b)) with jet energy loss of both QGP + Hadron phases (black solid curves with (q^c/Tc3,q^0/T03)=(4.5,0.0) and q^h) and of only QGP phase (red solid curves with (q^c/Tc3,q^0/T03)=(5.4,0.0) from Fig. 16) for 20-30% Pb + Pb collisions at sNN=2.76 TeV
pic
Fig. 17
(Color online) Comparisons of the average jet energy loss distribution between QGP + Hadron phases (black solid curves) and only QGP phase (red solid curves from Fig. 7 and 8) in noncentral A + A collisions at RHIC (left panels) and the LHC (right panels), respectively. The black dot-dashed curves are for hadron phase contribution in the case of QGP + Hadron phases. From top to bottom are the average accumulative energy loss, differential energy loss, and energy loss asymmetry, respectively
pic

It is worth noting that the description of pT dependence of v2 still deserves further improvement. This study considers only the T dependence of q^/T3. Taking into account the dependence of q^/T3 on the parton energy E, which is more directly related to the pT distribution of the jet energy loss [48, 50, 88], is likely to aid in improving the pT dependence of v2. Moreover, considering the dependence of q^/T3 on the collision energy, sNN can also contribute to a more accurate description [89]. Additionally, elastic energy loss and jet-induced medium responses have a significant impact on hadron production at intermediate transverse momentum, which could enhance v2 in this pT region [90, 91]. In the future, we will incorporate these considerations into our model to further improve its descriptive power for experimental data.

5.2
Jet energy loss distribution in QGP and hadron phases

Similarly to Figs. 7 and 8, we show in Fig. 17 the comparisons of the average jet energy loss distribution between QGP + Hadron phases (black solid curves) and only QGP phase (red solid curves) in noncentral A + A collisions at RHIC (left panels) and the LHC (right panels), respectively. The black dot-dashed curves represent the hadron phase contribution in the case of QGP + Hadron phases. From top to bottom are the average accumulated energy loss, differential energy loss, and energy loss asymmetry, respectively.

The hadron phase contribution to the total energy loss of QGP + Hadron phases was approximately 17% at RHIC in Fig. 17(a) while about 14% at the LHC in Fig. 17(d). Because of the first-order phase transition in the current model shown in Fig. 7(c) and (f), the hadron phase contribution happens mainly in the Tc nearby shown in Fig. 17 (b) and (e), which strengthens the azimuthal anisotropy of the system and then enhances the elliptic flow parameter. This is similar to the peak of the energy loss rate pushed to Tc owing to the linear T dependence of q^/T3 in Fig. 7(b) and (e). Such enhancements in the azimuthal anisotropy are also exhibited by the energy loss asymmetry shown in Fig. 17(c) and (f).

5.3
Temperature dependence of q^/T3 in QGP and hadron phases

Shown in Fig. 18 is the q^/T3 of the hadronic phase (dot-dashed line) and QGP phase (solid lines) as a function of medium temperature T. The hadronic phase q^/T3 is given by Eq. (14). The values of q^/T3 for the QGP phase with linear temperature dependence are given by Eq. (10) with (q^c/Tc3,q^0/T03)=(5.7,0.0) at RHIC (denoted by the red curve) and (4.5,0.0) at the LHC (denoted by the blue curve), respectively. The contributions to q^/T3 of the QGP and hadron phases combined using Eq. (13) were applied to RAA(pT) and v2(pT) at RHIC/LHC, as shown in Fig. 15 and Fig. 16. For comparison, representative samples of q^/T3 extracted from single hadron, dihadron, and γ-hadron production at RHIC and LHC energies with information field (IF) Bayesian analysis [51] are also shown in Fig. 18, which are denoted by grey curves. Ref. [51] does not consider the jet energy loss in the hadronic phase with a pseduocritical temperature Tc= 0.165 GeV. When considering the experimental data covering a wider temperature range, q^/T3 still indicates a large value at the critical temperature. Our numerical results for temperature-dependent q^/T3 are consistent with those obtained using the IF-Bayesian method.

Fig. 18
(Color online) The scaled jet transport coefficient q^/T3 as a function of medium temperature T. T< 0.17 GeV for the hadronic phase (dot-dashed curve), and T> 0.17 GeV for the QGP phase (solid curves). The q^/T3 of QGP phase for Au + Au collisions at sNN=200 GeV is denoted in red, and for Pb + Pb collisions at sNN=2.76 TeV is denoted in blue. As comparisons, the q^/T3 posterior samples from single hadron, dihadron, and γ-hadron production at RHIC and the LHC energies with IF-Bayesian analysis [51] are also shown in grey curves
pic

After adding the hadron phase contribution to the jet energy loss, one should decrease the QGP phase contribution so as to obtain a total energy loss equal to that of the QGP phase alone. The decreased QGP-phase energy loss makes v2(pT) smaller, whereas the added hadron-phase energy loss makes v2(pT) larger. The numerical results show that the competition between them gives v2(pT) a larger value than in the case of only the QGP phase because of the energy loss contribution of the hadronic phase concentrated near the critical temperature. Regardless of the added hadron phase or the linear going-down T-dependence of q^/T3 in the QGP phase, as shown in Fig. 18, the jet is made to lose much more energy near the critical temperature, which results in a larger v2(pT) for the large pT to fit data better. This numerical result of stronger jet quenching in the near-Tc region is consistent with that of a previous theoretical study [33].

One may notice that we extracted q^/T3 at RHIC and the LHC with different parameter ranges. This is mainly because, in this work, we observed that extracting q^/T3 at RHIC and LHC separately could provide a better χ2 result than the simultaneous fit at both collision energies. In this study, we only considered the dependence of q^ on the temperature. As mentioned previously, if the dependencies of q^ on parton energy E and sNN, as well as the jet-induced medium responses and elastic energy loss, were all considered, the value of q^ could be constrained more accurately from RAA and v2 at both RHIC and LHC energies simultaneously. Nevertheless, the q^/T3 obtained in this study is also consistent with the q^/T3 extracted by the IF-Bayesian approach [51] and JETSCAPE [48, 50], which constrained q^/T3 from RHIC and the LHC simultaneously, as shown in Fig. 18. We hope that in the future, by updating the model and enriching the information on q^, we can better describe RAA and v2 simultaneously for both RHIC and the LHC energies.

6

Summary

In this study, within a next-to-leading-order perturbative QCD model, the medium-temperature dependence of jet energy loss was studied via the nuclear modification factor RAA(pT) and elliptic flow parameter v2(pT) of large transverse momentum hadrons. Owing to the jet quenching, medium-modified fragmentation functions based on the higher-twist energy-loss formalism were used in the numerical calculations. We assumed that the scaled jet transport coefficient q^/T3 depends on the medium temperature in linear or Gaussian form, with which we calculated the single hadron suppression factor RAA(pT) and elliptic flow parameter v2(pT) and compared them with experimental data. To constrain the q^/T3 temperature dependence forms, a global χ2/d.o.f fitting was performed on the the experimental data. Finally, the jet energy loss in the hadronic phase was also considered.

With the linear T dependence of q^/T3 for only the QGP phase, the global χ2/d.o.f fitting for both RAA(pT) and v2(pT) shows that q^c/Tc3 = 6.0-8.0 at RHIC and 4.0-6.0 at the LHC while q^0/T03 = 0.0-4.2 at both RHIC and the LHC, as shown in Fig. 3 (a) and Fig. 6 (a). The numerical results indicate that RAA(pT) and v2(pT) are both more sensitive to the value of q^/T3 near the critical temperature Tc than near the initial highest temperature T0. Furthermore, the fitting results show a decreasing trend of q^/T3 depending on the medium temperature, which is also supported by the Gaussian T dependence of q^/T3 for only the QGP phase.

Compared with the case of constant q^/T3, the going-down T dependence of q^/T3 causes a hard parton jet to lose more energy near the critical temperature Tc and therefore strengthens the azimuthal anisotropy for large pT hadron production. As a result, the elliptic flow parameter v2(pT) for large pT hadrons was enhanced by approximately 10% to better fit the data at RHIC/LHC. Considering the first-order phase transition from QGP to hadron and the hadron phase contribution to the jet energy loss, v2(pT) is again enhanced by 5%-10% at RHIC/LHC.

References
1 A. Adare, S. Afanasiev, C. Aidala et al.,

Suppression pattern of neutral pions at high transverse momentum in Au+Au collisions at sNN = 200 GeV and constraints on medium transport coefficients

. Phys. Rev. Lett. 101, 232301 (2008). https://doi.org/10.1103/PhysRevLett.101.232301
Baidu ScholarGoogle Scholar
2 A. Adare, S. Afanasiev, C. Aidala et al.,

Neutral pion production with respect to the centrality and reaction plane in Au+Au collisions at sNN=200 GeV

. Phys. Rev. C 87, 034911 (2013). https://doi.org/10.1103/PhysRevC.87.034911
Baidu ScholarGoogle Scholar
3 A. Adare, S. Afanasiev, C. Aidala et al.,

Azimuthal anisotropy of neutral pion production in Au+Au collisions at sNN = 200 GeV: Path-length dependence of jet quenching and the role of initial geometry

. Phys. Rev. Lett. 105, 142301 (2010). https://doi.org/10.1103/PhysRevLett.105.142301
Baidu ScholarGoogle Scholar
4 B. Abelev, J. Adam, D. Adamová et al.,

Centrality dependence of charged particle production at large transverse momentum in Pb–Pb collisions at sNN=2.76 TeV

. Phys. Lett. B 720, 52-62 (2013). https://doi.org/10.1016/j.physletb.2013.01.051
Baidu ScholarGoogle Scholar
5 S. Chatrchyan, V. Khachatryan, A.M. Sirunyan et al.,

Study of high-pT charged particle suppression in PbPb compared to pp collisions at sNN=2.76 TeV

. Eur. Phys. J. C 72, 1945 (2012). https://doi.org/10.1140/epjc/s10052-012-1945-x
Baidu ScholarGoogle Scholar
6 S. Acharya, F.T.-. Acosta, D. Adamová et al.,

Transverse momentum spectra and nuclear modification factors of charged particles in pp, p-Pb, and Pb-Pb collisions at LHC

. JHEP 11, 013 (2018). https://doi.org/10.1007/JHEP11(2018)013
Baidu ScholarGoogle Scholar
7 V. Khachatryan, A.M. Sirunyan, A. Tumasyan et al.,

Charge-particle nuclear modification factors in PbPb and pPb collisions at sNN=5.02 TeV

. JHEP 04 039 (2017). https://doi.org/10.1007/JHEP04(2017)039
Baidu ScholarGoogle Scholar
8 S. Acharya, F.T. Acosta, D. Adamová et al.,

Transverse momentum spectra and nuclear modification factors of charged particles in Xe-Xe collisions at sNN = 5.44 TeV

. Phys. Lett. B 788, 166-179 (2019). https://doi.org/10.1016/j.physletb.2018.10.052
Baidu ScholarGoogle Scholar
9 S. Chatrchyan, V. Khachatryan, A.M. Sirunyan et al.,

Azimuthal anisotropy of charged particles at high transverse momenta in Pb-Pb collisions at sNN=2.76 TeV

. Phys. Rev. Lett. 109, 022301 (2012). https://doi.org/10.1103/PhysRevLett.109.022301
Baidu ScholarGoogle Scholar
10 B. Abelev, J. Adam, D. Adamová et al.,

Anisotropic flow of charged hadrons, pions, and (anti)protons measured at a high transverse momentum in Pb-Pb collisions at sNN=2.76 TeV

. Phys. Lett. B 719, 18-28 (2013). https://doi.org/10.1016/j.physletb.2012.12.066
Baidu ScholarGoogle Scholar
11 J. Adam, D. Adamová, M.M. Aggarwal et al.,

Anisotropic flow of charged particles in Pb-Pb collisions at sNN=5.02 TeV

. Phys. Rev. Lett. 116, 132302 (2016). https://doi.org/10.1103/PhysRevLett.116.132302
Baidu ScholarGoogle Scholar
12 A.M. Sirunyan, A. Tumasyan, W. Adam et al.,

Azimuthal anisotropy of charged particles with transverse momentum up to 100 GeV/c in PbPb collisions at sNN=5.02 TeV

. Phys. Lett. B 776, 195-216 (2018). https://doi.org/10.1016/j.physletb.2017.11.041
Baidu ScholarGoogle Scholar
13 M. Gyulassy and M. Plumer,

Jet quenching in dense matter

. Phys. Lett. B 243, 432-438 (1990). https://doi.org/10.1016/0370-2693(90)91409-5
Baidu ScholarGoogle Scholar
14 X. N. Wang and M. Gyulassy,

Gluon shadowing, and jet quenching in A + A collisions at sNN = 200 GeV

. Phys. Rev. Lett. 68, 1480-1483 (1992). https://doi.org/10.1103/PhysRevLett.68.1480
Baidu ScholarGoogle Scholar
15 G.Y. Qin and X.N. Wang,

Jet quenching in high-energy heavy-ion collisions

. Int. J. Mod. Phys. E 24, 1530014 (2015). https://doi.org/10.1142/S0218301315300143
Baidu ScholarGoogle Scholar
16 Z.W. Lin and L. Zheng,

Further developed a multi-phase transport model for relativistic nuclear collisions

. Nucl. Sci. Tech. 32, 113 (2021). https://doi.org/10.1007/s41365-021-00944-5
Baidu ScholarGoogle Scholar
17 Z. Tang, Z.B. Tang, W. Zha et al.,

An experimental review of open heavy flavor and quarkonium production at RHIC

. Nucl. Sci. Tech. 31, 81 (2020). https://doi.org/10.1007/s41365-020-00785-8
Baidu ScholarGoogle Scholar
18 L. Ma, X. Dong, H. Z. Huang et al.,

Study of background reconstruction method for the measurement of D-meson azimuthal angular correlations

. Nucl. Sci. Tech. 32, 61 (2021). https://doi.org/10.1007/s41365-021-00896-w
Baidu ScholarGoogle Scholar
19 H. Song, Y. Zhou, K. Gajdosova,

Collective flow and hydrodynamics in large and small systems at LHC

. Nucl. Sci. Tech. 28, 99 (2017). https://doi.org/10.1007/s41365-017-0245-4
Baidu ScholarGoogle Scholar
20 X.F. Luo and N. Xu,

Searched for the QCD critical point with fluctuations of conserved quantities in relativistic heavy-ion collisions at RHIC: an overview

. Nucl. Sci. Tech. 28, 112 (2017). https://doi.org/10.1007/s41365-017-0257-0
Baidu ScholarGoogle Scholar
21 R. Baier, Y. L. Dokshitzer, A.H. Mueller et al..

Radiative energy loss and p(T) broadening of high-energy partons in the nuclei

. Nucl. Phys. B 484, 265-282 (1997). https://doi.org/10.1016/S0550-3213(96)00581-0
Baidu ScholarGoogle Scholar
22 K. M. Burke, A. Buzzatti, N.B. Chang et al.,

Extracting the jet transport coefficient from jet quenching in high-energy heavy-ion collisions

. Phys. Rev. C 90, 014909 (2014). https://doi.org/10.1103/PhysRevC.90.014909
Baidu ScholarGoogle Scholar
23 X.F. Chen, C. Greiner, E. Wang et al.,

Bulk matter evolution and extraction of jet transport parameters in heavy-ion collisions at RHIC

. Phys. Rev. C 81, 064908 (2010). https://doi.org/10.1103/PhysRevC.81.064908
Baidu ScholarGoogle Scholar
24 X.F. Chen, T. Hirano, E. Wang et al.,

Suppression of high pT hadrons in Pb+Pb Collisions at LHC

. Phys. Rev. C 84, 034902 (2011). https://doi.org/10.1103/PhysRevC.84.034902
Baidu ScholarGoogle Scholar
25 M. Xie, S.Y. Wei, G. Y. Qin et al.,

Extracting jet transport coefficient via single hadron and dihadron production in high-energy heavy-ion collisions

. Eur. Phys. J. C 79, 589 (2019). https://doi.org/10.1140/epjc/s10052-019-7100-1
Baidu ScholarGoogle Scholar
26 Z.Q. Liu, H. Zhang, B.W. Zhang et al.,

Quantifying jet transport properties via large pT hadron production

. Eur. Phys. J. C 76, 20 (2016). https://doi.org/10.1140/epjc/s10052-016-3885-3
Baidu ScholarGoogle Scholar
27 B. Schenke, C. Gale, S. Jeon,

MARTINI: An event generator for relativistic heavy-ion collisions

. Phys. Rev. C 80, 054913 (2009). https://doi.org/10.1103/PhysRevC.80.054913
Baidu ScholarGoogle Scholar
28 G.Y. Qin, J. Ruppert, C. Gale, et al..

Radiative and collisional jet energy loss in quark-gluon plasma at RHIC

. Phys. Rev. Lett. 100, 072301 (2008). https://doi.org/10.1103/PhysRevLett.100.072301
Baidu ScholarGoogle Scholar
29 S.K. Das, F. Scardina, S. Plumari et al.,

Toward a solution to RAA and v2 puzzles for heavy quarks

. Phys. Lett. B 747, 260-264 (2015). https://doi.org/10.1016/j.physletb.2015.06.003
Baidu ScholarGoogle Scholar
30 S. Cao, L. G. Pang, T. Luo et al.,

RAA vs. v2 of heavy and light hadrons within a linear Boltzmann transport model

. Nucl. Part. Phys. Proc. 289–290, 217-220 (2017). https://doi.org/10.1016/j.nuclphysbps.2017.05.048
Baidu ScholarGoogle Scholar
31 X.N. Wang,

Dynamic screening and radiative parton energy loss in quark glucose plasma

. Phys. Lett. B 485, 157-161 (2000). https://doi.org/10.1016/S0370-2693(00)00642-0
Baidu ScholarGoogle Scholar
32 J. Casalderrey-Solana and X.N. Wang,

Energy dependence of jet transport parameters and parton saturation in quark-gluon plasma

. Phys. Rev. C 77, 024902 (2008). https://doi.org/10.1103/PhysRevC.77.024902
Baidu ScholarGoogle Scholar
33 J.F. Liao and E. Shuryak,

Angular dependence of jet quenching indicated a strong enhancement near the QCD phase transition

. Phys. Rev. Lett. 102, 202302 (2009). https://doi.org/10.1103/PhysRevLett.102.202302
Baidu ScholarGoogle Scholar
34 J. Xu, J. Liao and M. Gyulassy,

Consistency of perfect fluidity and jet quenching in semi-quark-gluon monopole plasmas

. Chin. Phys. Lett. 32, 092501 (2015). https://doi.org/10.1088/0256-307X/32/9/092501
Baidu ScholarGoogle Scholar
35 J. Xu, J. Liao, M. Gyulassy,

Bridging soft-hard transport properties of quark-gluon plasmas with CUJET3.0

. JHEP 02, 169 (2016). https://doi.org/10.1007/JHEP02(2016)169
Baidu ScholarGoogle Scholar
36 S. Shi, J. Liao, M. Gyulassy,

Global constraints from RHIC and LHC on transport properties of QCD fluids in CUJET/CIBJET framework

. Chin. Phys. C 43, 044101 (2019). https://doi.org/10.1088/1674-1137/43/4/044101
Baidu ScholarGoogle Scholar
37 M. Gyulassy, P. Levai and I. Vitev,

Reaction operator approach to nonAbelian energy loss

. Nucl. Phys. B 594, 371-419 (2001). https://doi.org/10.1016/S0550-3213(00)00652-0
Baidu ScholarGoogle Scholar
38 B. Wu,

Radiative energy loss, and radiative p⊥ broadening of high-energy partons in QCD matter

. JHEP 12, 081 (2014). https://doi.org/10.1007/JHEP12(2014)081
Baidu ScholarGoogle Scholar
39 A.H. Mueller, B. Wu, B.W. Xiao et al.,

Medium-induced transverse momentum broadening in hard processes

. Phys. Rev. D 95, 034007 (2017). https://doi.org/10.1103/PhysRevD.95.034007
Baidu ScholarGoogle Scholar
40 E. Iancu, P. Taels, B. Wu,

Jet quenching parameters in expanding QCD plasma

. Phys. Lett. B 786, 288-295 (2018). https://doi.org/10.1016/j.physletb.2018.10.007
Baidu ScholarGoogle Scholar
41 H. Liu, K. Rajagopal and U.A. Wiedemann,

Calculating the jet quenching parameter from AdS/CFT,

Phys. Rev. Lett. 97, 182301 (2006). https://doi.org/10.1103/PhysRevLett.97.182301
Baidu ScholarGoogle Scholar
42 Z.Q. Zhang, D.F. Hou, Y. Wu et al.,

R2 corrections to the jet quenching parameter

. Adv. High Energy Phys. 2016, 9503491 (2016). https://doi.org/10.1155/2016/9503491
Baidu ScholarGoogle Scholar
43 J. Ghiglieri, H. Kim,

Transverse momentum broadening and collinear radiation at NLO in a N=4 SYM plasma

. JHEP 12, 049 (2018). https://doi.org/10.1007/JHEP12(2018)049
Baidu ScholarGoogle Scholar
44 M. Panero, K. Rummukainen, and A. Schäfer,

Lattice study of the jet quenching parameter

. Phys. Rev. Lett. 112, 162001 (2014). https://doi.org/10.1103/PhysRevLett.112.162001
Baidu ScholarGoogle Scholar
45 M. Panero, K. Rummukainen, and A. Schäfer,

Investigating jet quenching on the lattice

. Nucl. Phys. A 932, 122-127 (2014). https://doi.org/10.1016/j.nuclphysa.2014.07.008
Baidu ScholarGoogle Scholar
46 M. Panero, K. Rummukainen, and A. Schäfer,

Jet quenching from the lattice

. Nucl. Phys. A 931, 393-398 (2014). https://doi.org/10.1016/j.nuclphysa.2014.07.037
Baidu ScholarGoogle Scholar
47 A. Kumar, A. Majumder, C. Nonaka,

First calculation of q^ on quenched SU(3) plasma

. PoS 2018, 169 (2018). https://doi.org/10.22323/1.334.0169
Baidu ScholarGoogle Scholar
48 S. Cao, Y. Chen, J. Coleman et al.,

Determined the jet transport coefficient q^ from inclusive hadron suppression measurements by using Bayesian parameter estimation

. Phys. Rev. C 104, 024905 (2021). https://doi.org/10.1103/PhysRevC.104.024905
Baidu ScholarGoogle Scholar
49 W. Ke and X. N. Wang,

QGP modification of single-inclusive jets in a calibrated transport model

. JHEP 05, 041 (2021). https://doi.org/10.1007/JHEP05(2021)041
Baidu ScholarGoogle Scholar
50 A. Kumar, Y. Tachibana, C. Sirimanna et al.,

Inclusive jet and hadron suppression in a multistage approach

. Phys. Rev. C 107, 034911 (2023). https://doi.org/10.1103/PhysRevC.107.034911
Baidu ScholarGoogle Scholar
51 M. Xie, W. Ke, H. Zhang et al.,

Information-field-based global Bayesian inference of jet transport coefficient

. Phys. Rev. C 108, L011901 (2023). https://doi.org/10.1103/PhysRevC.108.L011901
Baidu ScholarGoogle Scholar
52 W.T. Deng, X.N. Wang,

Multiple Parton scattering in nuclei: modified DGLAP evolution for fragmentation functions

. Phys. Rev. C 81, 024902 (2010). https://doi.org/10.1103/PhysRevC.81.024902
Baidu ScholarGoogle Scholar
53 E. Wang and X. N. Wang,

Parton energy loss with detailed balance

. Phys. Rev. Lett. 87, 142301 (2001). https://doi.org/10.1103/PhysRevLett.87.142301
Baidu ScholarGoogle Scholar
54 E. Wang and X. N. Wang,

Jet tomography of dense and nuclear matter

. Phys. Rev. Lett. 89, 162301 (2002). https://doi.org/10.1103/PhysRevLett.89.162301
Baidu ScholarGoogle Scholar
55 T. Hirano,

Is early thermalization achieved near mid-rapidity at RHIC

? Phys. Rev. C 65, 011901 (2002). https://doi.org/10.1103/PhysRevC.65.011901
Baidu ScholarGoogle Scholar
56 T. Hirano and K. Tsuda,

Collective flow and two pion correlations from a relativistic hydrodynamic model with early chemical freezeout

. Phys. Rev. C 66, 054905 (2002). https://doi.org/10.1103/PhysRevC.66.054905
Baidu ScholarGoogle Scholar
57 J.F. Owens,

Large momentum transfer production of Direct photons, jets, and particles

. Rev. Mod. Phys. 59, 465 (1987). https://doi.org/10.1103/RevModPhys.59.465
Baidu ScholarGoogle Scholar
58 G. Sterman, J. Smith, J.C. Collins et al.,

Handbook of perturbative QCD

. Rev. Mod. Phys. 67, 157-248 (1995). https://doi.org/10.1103/RevModPhys.67.157
Baidu ScholarGoogle Scholar
59 T.J. Hou, S. Dulat, J. Gao et al.,

CTEQ-TEA parton distribution functions, and HERA runs I and II combined the data

. Phys. Rev. D 95, 034003 (2017). https://doi.org/10.1103/PhysRevD.95.034003
Baidu ScholarGoogle Scholar
60 S. Albino, B. A. Kniehl, G. Kramer,

AKK Update: Improvements from new theoretical inputs and experimental data

. Nucl. Phys. B 803, 42-104 (2008). https://doi.org/10.1016/j.nuclphysb.2008.05.017
Baidu ScholarGoogle Scholar
61 B.W. Harris, J.F. Owens,

Two-cutoff phase-space slicing method

. Phys. Rev. D 65, 094032 (2002). https://doi.org/10.1103/PhysRevD.65.094032
Baidu ScholarGoogle Scholar
62 H. Zhang, J.F. Owens, E. Wang et al.,

Dihadron tomography of high-energy nuclear collisions in NLO pQCD

. Phys. Rev. Lett. 98, 212301 (2007). https://doi.org/10.1103/PhysRevLett.98.212301
Baidu ScholarGoogle Scholar
63 H. Zhang, J.F. Owens, E. Wang et al..

Tomography of high-energy nuclear collisions with photon-hadron correlations

. Phys. Rev. Lett. 103, 032302 (2009). https://doi.org/10.1103/PhysRevLett.103.032302
Baidu ScholarGoogle Scholar
64 X.N. Wang,

pQCD based approach to parton production and equilibration in high-energy nuclear collisions

. Phys. Rept. 280, 287-371 (1997). https://doi.org/10.1016/S0370-1573(96)00022-1
Baidu ScholarGoogle Scholar
65 S.Y. Li and X.N. Wang,

Gluon shadowing and hadron production at RHIC

. Phys. Lett. B 527, 85-91 (2002). https://doi.org/10.1016/S0370-2693(02)01179-6
Baidu ScholarGoogle Scholar
66 V. Emel’yanov, A. Khodinov, S.R. Klein, et al.,

The Effect of shadowing on initial conditions, transverse energy and hard probes in ultrarelativistic heavy ion collisions

. Phys. Rev. C 61, 044904 (2000). https://doi.org/10.1103/PhysRevC.61.044904
Baidu ScholarGoogle Scholar
67 T. Hirano, Y. Nara,

Interplay between soft and hard hadronic components for identified hadrons in relativistic heavy-ion collisions at RHIC

. Phys. Rev. C 69, 034908 (2004). https://doi.org/10.1103/PhysRevC.69.034908
Baidu ScholarGoogle Scholar
68 K.J. Eskola, P. Paakkinen, H. Paukkunen et al.,

EPPS16: Nuclear parton Distributions with LHC Data

. Eur. Phys. J. C 77, 163 (2017). https://doi.org/10.1140/epjc/s10052-017-4725-9
Baidu ScholarGoogle Scholar
69 X.N. Wang, Z. Huang, I. Sarcevic,

Jet quenching in the opposite direction of a tagged photon in high-energy heavy-ion collisions

. Phys. Rev. Lett. 77, 231-234 (1996). https://doi.org/10.1103/PhysRevLett.77.231
Baidu ScholarGoogle Scholar
70 X.N. Wang and Z. Huang,

Study medium-induced parton energy loss in gamma + jet events of high-energy heavy-ion collisions

. Phys. Rev. C 55, 3047-3061 (1997). https://doi.org/10.1103/PhysRevC.55.3047
Baidu ScholarGoogle Scholar
71 X.N. Wang,

Energy dependence of jet quenching and lifetime of dense matter in high-energy heavy-ion collisions

. Phys. Rev. C 70, 031901 (2004). https://doi.org/10.1103/PhysRevC.70.031901
Baidu ScholarGoogle Scholar
72 N.B. Chang, W.T. Deng, and X.N. Wang,

Initial conditions for the modified evolution of fragmentation functions in nuclear medium

. Phys. Rev. C 89, 034911 (2014). https://doi.org/10.1103/PhysRevC.89.034911
Baidu ScholarGoogle Scholar
73 B.W. Zhang and X.N. Wang,

Multiple parton scattering in nuclei: beyond helicity amplitude approximation

. Nucl. Phys. A 720, 429-451 (2003). https://doi.org/10.1016/S0375-9474(03)01003-0
Baidu ScholarGoogle Scholar
74 B.W. Zhang, E.K. Wang, X.N. Wang,

Multiple parton scattering in nuclei: Heavy quark energy loss and modified fragmentation functions

. Nucl. Phys. A 757, 493-524 (2005). https://doi.org/10.1016/j.nuclphysa.2005.04.022
Baidu ScholarGoogle Scholar
75 N. Armesto, B. Cole, C. Gale, et al.,

Comparison of Jet Quenching Formalisms for a Quark-Gluon Plasma ’Brick.’

Phys. Rev. C 86, 064904 (2012). https://doi.org/10.1103/PhysRevC.86.064904
Baidu ScholarGoogle Scholar
76 S. Cao, G. Coci, S.K. Das, et al.,

Toward the determination of heavy-quark transport coefficients in quark-gluon plasma

. Phys. Rev. C 99, 054907 (2019). https://doi.org/10.1103/PhysRevC.99.054907
Baidu ScholarGoogle Scholar
77 S. Shi, J. Liao, M. Gyulassy,

Global constraints from RHIC and LHC on transport properties of QCD fluids in CUJET/CIBJET framework

. Chin. Phys. C 43, 044101 (2019). https://doi.org/10.1088/1674-1137/43/4/044101
Baidu ScholarGoogle Scholar
78 W. Dai, S. Wang, S.L. Zhang et al.,

Transverse Momentum Balance and Angular Distribution of bb¯ Dijets in Pb+Pb collisions

. Chin. Phys. C 44, 104105 (2020). https://doi.org/10.1088/1674-1137/abab8f
Baidu ScholarGoogle Scholar
79 C. Nonaka, E. Honda, and S. Muroya,

(3+1)-dimensional relativistic hydrodynamical expansion of hot and dense matter in ultrarelativistic nuclear collisions

. Eur. Phys. J. C 17, 663-673 (2000). https://doi.org/10.1007/s100520000509
Baidu ScholarGoogle Scholar
80 T. Hirano, U. W. Heinz, D. Kharzeev, et al.,

Mass ordering of differential elliptic flow and its violation for phi mesons

. Phys. Rev. C 77, 044909 (2008). https://doi.org/10.1103/PhysRevC.77.044909
Baidu ScholarGoogle Scholar
81 H. Wang and J.H. Chen,

Study on open-charm hadron production and angular correlation in high-energy nuclear collisions

. Nucl. Sci. Tech. 32, 2 (2021). https://doi.org/10.1007/s41365-020-00839-x
Baidu ScholarGoogle Scholar
82 A.M. Poskanzer, S.A. Voloshin,

Methods for analyzing anisotropic flow in relativistic nuclear collisions

. Phys. Rev. C 58, 1671-1678 (1998). https://doi.org/10.1103/PhysRevC.58.1671
Baidu ScholarGoogle Scholar
83 X.N. Wang,

Jet quenching and azimuthal anisotropy of large p(T) spectra in noncentral high-energy heavy-ion collisions

. Phys. Rev. C 63, 054902 (2001). https://doi.org/10.1103/PhysRevC.63.054902
Baidu ScholarGoogle Scholar
84 S.Y. Tang, L. Zheng, X.M. Zhang et al.,

Investigating the elliptic anisotropy of identified particles in p–Pb collisions using a multi-phase transport model

. Nucl. Sci. Tech. 35, 32 (2024). https://doi.org/10.1007/s41365-024-01387-4
Baidu ScholarGoogle Scholar
85 M. Wang, J. Q. Tao, H. Zheng, et al.,

Number of constituent-quark scaling of elliptic flow: A quantitative study

. Nucl. Sci. Tech. 33, 37 (2022). https://doi.org/10.1007/s41365-022-01019-9
Baidu ScholarGoogle Scholar
86 S.W. Lan and S.S. Shi,

Anisotropic flow in the high-baryon-density region

. Nucl. Sci. Tech. 33, 21 (2022). https://doi.org/10.1007/s41365-022-01006-0
Baidu ScholarGoogle Scholar
87 H. Wang, J.H. Chen,

Anisotropy flows in Pb–Pb collisions at LHC energies from parton scatterings with heavy quark triggers

. Nucl. Sci. Tech. 33, 15 (2022). https://doi.org/10.1007/s41365-022-00999-y
Baidu ScholarGoogle Scholar
88 Y. He, L.G. Pang, and X.N. Wang,

Bayesian extraction of jet energy-loss distributions in heavy-ion collisions

. Phys. Rev. Lett. 122, 252302 (2019). https://doi.org/10.1103/PhysRevLett.122.252302
Baidu ScholarGoogle Scholar
89 L. L. Zhu, B. Wang, M. Wang et al.,

Energy and Centrality Dependence of Light Nuclei Production in Relativistic Heavy Ion Collisions

. Nucl. Sci. Tech. 33, 45 (2022). https://doi.org/10.1007/s41365-022-01028-8
Baidu ScholarGoogle Scholar
90 G.Y. Qin,

Anisotropic flow and jet quenching in relativistic nuclear collisions

. Int. J. Mod. Phys. E 24, 1530001 (2015). https://doi.org/10.1142/S0218301315300015
Baidu ScholarGoogle Scholar
91 W. Zhao, W. Ke, W. Chen et al.,

From Hydrodynamics to Jet Quenching, Coalescence, and Hadron Cascade: A Coupled Approach to Solving the RAA⊗v2 puzzle

. Phys. Rev. Lett. 128, 022302 (2022). https://doi.org/10.1103/PhysRevLett.128.022302
Baidu ScholarGoogle Scholar
Footnote

The authors declare that they have no competing interests.