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Ajaz, M.; Ismail, A. Haj; Ahmed, Awais; Wazir, Z.; Shehzadi, R.; Younis, H.; Khan, Gulzar; Khan, R. A.; Ali, Shahid; Waqas, M.; Yang, Pei-Pin; Dawi, Elmuez A.

doi:10.1016/j.rinp.2021.104790

Cited by 26 publications

(10 citation statements)

References 19 publications

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“…The difference in the two temperatures is due to the reason that they occur at two different process in the system evolution. Furthermore, it is also possible that the centrality dependence of the two types of temperatures is also different if one gets the increasing trend from central to peripheral for T 0 which is observed in our recent work [64,65]. In fact the trend dependence of T 0 is also an open question in high energy collisions because different literature give different trend.…”

Section: B Tendencies Of Parametersmentioning

confidence: 82%

“…Generally, the soft excitation process is distributed in a narrow p T range of less than 2-3 GeV/c or a little more, and mostly light flavor particles are produced in this region. The soft process have many choices of formalisms such as Blast wave model with Boltzmann Gibb's statistics [19][20][21][22], Blast wave model with Tsallis statistics [23][24][25][26],Tsallis pareto-type function [27], Erlang distribution [28][29][30], Scwinger mechanism [31][32][33][34], Hagedorn distribution function [35], Standard distribution [36] etc. The p T region above 3 GeV/c is contributed for the hard process and is described by Quantum chromodynamics (QCD) calculus [37][38][39] or inverse power law which is also known as Hagedron function…”

Section: Formalism and Methodsmentioning

confidence: 99%

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Observation of different scenarios in different temperatures in small and large collision systems

Waqas¹,

Liu²,

Peng³

et al. 2021

Preprint

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We used the modified Hagedron function and analyzed the experimental data measured by the BRAHMS, STAR, PHENIX and ALICE Collaborations in Copper-Copper, Gold-Gold, deuteron-Gold, Lead-Lead, proton-Lead and proton-proton collisions, and extracted the related parameters (kinetic freeze-out temperature, transverse flow velocity, kinetic freeze-out volume, mean transverse momentum and initial temperature) from the transverse momentum spectra of the particles (non-strange and strange particles). We observed that all the above parameters decrease from central to peripheral collisions, except transverse flow velocity which remains unchanged from central to peripheral collisions. The kinetic freeze-out temperature depends on the cross-section interaction of the particle such that larger cross-section of the particle corresponds to smaller T0, and reveals the two kinetic freeze-out scenario, while the initial temperature depends on the mass of the particle and it increase with the particle mass. The transverse flow velocity and mean transverse momentum depends on the mass of the particle and the former decrease while the later increase with the particle mass. In addition, the kinetic kinetic freeze-out volume also decrease with particle mass which reveals the volume differential freeze-out scenario and indicates different freeze-out surfaces for different particles. We also extracted the entropy index-parameter n and the parameter N0, and the former remains almost unchanged while the later decrease from central to peripheral collisions. Furthermore, the kinetic freeze-out temperature, transverse flow velocity, kinetic freeze-out volume, initial temperature, mean transverse momentum and the parameter N0 at LHC are larger than that of RHIC, and they show their dependence on the collision cross-section as well as on collision energy at RHIC and LHC.

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Section: B Tendencies Of Parametersmentioning

confidence: 82%

Section: Formalism and Methodsmentioning

confidence: 99%

Observation of different scenarios in different temperatures in small and large collision systems

Waqas¹,

Liu²,

Peng³

et al. 2021

Preprint

Self Cite

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“…The present work is a continuation of our work published in [ 16 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 ] using different statistical fit functions to extract parameters relevant to the collective properties of the hadronic medium.…”

Section: The Methods and Formalismmentioning

confidence: 94%

Analyses of pp, Cu–Cu, Au–Au and Pb–Pb Collisions by Tsallis-Pareto Type Function at RHIC and LHC Energies

Ajaz

et al. 2022

Entropy

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The parameters revealing the collective behavior of hadronic matter extracted from the transverse momentum spectra of π+, π−, K+, K−, p, p¯, Ks0, Λ, Λ¯, Ξ or Ξ−, Ξ¯+ and Ω or Ω¯+ or Ω+Ω¯ produced in the most central and most peripheral gold–gold (Au–Au), copper–copper (Cu–Cu) and lead–lead (Pb–Pb) collisions at 62.4 GeV, 200 GeV and 2760 GeV, respectively, are reported. In addition to studying the nucleus–nucleus (AA) collisions, we analyzed the particles mentioned above produced in pp collisions at the same center of mass energies (62.4 GeV, 200 GeV and 2760 GeV) to compare with the most peripheral AA collisions. We used the Tsallis–Pareto type function to extract the effective temperature from the transverse momentum spectra of the particles. The effective temperature is slightly larger in a central collision than in a peripheral collision and is mass-dependent. The mean transverse momentum and the multiplicity parameter (N0) are extracted and have the same result as the effective temperature. All three extracted parameters in pp collisions are closer to the peripheral AA collisions at the same center of mass energy, revealing that the extracted parameters have the same thermodynamic nature. Furthermore, we report that the mean transverse momentum in the Pb–Pb collision is larger than that of the Au–Au and Cu–Cu collisions. At the same time, the latter two are nearly equal, which shows their comparatively strong dependence on energy and weak dependence on the size of the system. The multiplicity parameter, N0 in central AA, depends on the interacting system’s size and is larger for the bigger system.

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“…The RHIC at BNL [5,6] and LHC at CERN [7] used proton-proton (pp) and proton-nucleus (pA) collisions as well as heavy-ion or nucleus-nucleus (AA) collisions at high energies to study the bulk properties of the strongly interacting matter [8]. Simultaneously, various Monte Carlo models (event generators) and analytic functions have been proposed to describe the stages of evolution of the system [9,10].…”

Section: Introductionmentioning

confidence: 99%

Pseudorapidity dependence of the $p_T$ spectra of charged hadrons in $pp$ collisions at $\sqrt{s}$ = 0.9 and 2.36 TeV

Yang,

Ajaz,

Waqas

et al. 2022

Preprint

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We report the predictions of different Monte Carlo event generators including HIJING, Pythia, and QGSJETII in comparison with the experimental data measured by the CMS Collaboration at CERN in proton-proton (pp) collisions at center-of-mass energy √ s = 0.9 and 2.36 TeV. The CMS experimental transverse momentum (pT or p ⊥ ) spectra of charged hadrons were measured for pseudorapidity range 0 ≤ η ≤ 2.4 with bin width of η = 0.2 (for pT from 0.1 to 2 GeV/c) and a single bin of η for |η| < 2.4 (for pT from 0.1 to 4 GeV/c). Pythia reproduced the pT spectra with reasonable agreement for most of the pT range. It depicts better results in the case of the |η| < 2.4 than HIJING and QGSJETII which could reproduce the spectra in a limited pT range. Furthermore, to analyze the pT spectra of charged hadrons measured by the CMS Collaboration, we used a three-component function (structured from the Boltzmann distribution) and the q-dual function (from the q-dual statistics) to extract parameter values relevant for the study of bulk properties of hadronic matter at high energy. We have also applied the two analytic functions over the model predictions. The values extracted by the functions from the HIJING and Pythia models are closer to the experimental data than the QGSJETII model. Although the models could reproduce the pT spectra of all charged particles in some of the pT range but none of them could reproduce the distributions over the entire pT range and in all the pseudorapidity regions.

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Centrality dependence of PT distributions and nuclear modification factor of charged particles in Pb–Pb interactions at S

Cited by 26 publications

References 19 publications

Observation of different scenarios in different temperatures in small and large collision systems

Observation of different scenarios in different temperatures in small and large collision systems

Analyses of pp, Cu–Cu, Au–Au and Pb–Pb Collisions by Tsallis-Pareto Type Function at RHIC and LHC Energies

Pseudorapidity dependence of the $p_T$ spectra of charged hadrons in $pp$ collisions at $\sqrt{s}$ = 0.9 and 2.36 TeV

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