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Adler, C.; Ahammed, Z.; Allgower, C.; Amonett, J.; Anderson, B.D.; Anderson, M.; Averichev, G. S.; Balewski, J.; Barannikova, O.; Barnby, Lee Stuart; Baudot, J.; Bekele, S.; Belaga, V. V.; Bellwied, R.; Berger, J.; Bichsel, H.; Bland, L. C.; Blyth, C. O.; Bonner, B. E.; Boucham, A.; Brandin, A. V.; Cadman, R. V.; Caines, H.; Sánchez, M. Calderón De La Barca; Cardenas, A.; Carroll, John L.; Castillo, J.; Castro, Maria Ines Abreu Juliao Ochoa de; Cebra, D.; Chattopadhyay, S.; Chen, M. L.; Chen, Y.; Chernenko, S.; Cherney, M.; Chikanian, A.; Choi, B.; Christie, W.; Coffin, J. P.; Cormier, T. M.; Cramer, J. G.; Crawford, H. J.; DeMello, M.; Deng, WS; Derevschikov, A. A.; Didenko, L.; Draper, J. E.; Dunin, V. B.; Dunlop, J. C.; Eckardt, V.; Efimov, L. G.; Емелянов, В.; Engelage, J.; Eppley, G.; Erazmus, B.; Fachini, P.; Faine, V.; Finch, E.; Fisyak, Y.; Flierl, D.; Foley, K. J.; Fu, J.; Gagunashvili, N.; Gans, J.; Gaudichet, L.; Germain, M.; Geurts, F.; Ghazikhanian, V.; Grabski, J.; Grachov, O.; Greiner, D.; Grigoriev, V.; Guedon, M.; Gushin, E.; Hallman, T. J.; Hardtke, D.; Harris, J. W.; Heffner, M.; Heppelmann, S.; Herston, T.; Hippolyte, B.; Hirsch, A.; Hjort, E.; Hoffmann, G. W.; Horsley, M.; Huang, H. Z.; Humanic, T. J.; Hümmler, Holm Gero; Igo, G.; Ishihara, A.; Ivanshin, Yu.; Jacobs, P.; Jacobs, W. W.; Janik, M. A.; Johnson, I.; Jones, P. G.; Judd, E. G.; Kaneta, M.; Kaplan, M.; Keane, D.; Kisiel, A.; Klay, J.; Klein, S. R.; Klyachko, A.; Константинов, А. С.; Kotchenda, L.; Kovalenko, A. D.; Krämer, M.; Кравцов, П.; Krueger, K.; Kuhn, C.; Куликов, А. И.; Kunde, G. J.; Kunz, C. L.; Kutuev, R.Kh.; Кузнецов, А. А.; Lakéhal-Ayat, L.; Lamas-Valverde, J.; Lamont, M. A.C.; Landgraf, J. M.; Lange, S.; Lansdell, C. P.; Lasiuk, B.; Laue, F.; Lebedev, A.A.; LeCompte, T.; Lednický, R.; Leontiev, V. M.; LeVine, M. J.; Li, Q.; Lindenbaum, S. J.; Lisa, M. A.; Ljubičić, T.; Llope, W. J.; LoCurto, G.; Long, H.; Longacre, R. S.; Lopez-Noriega, M.; Love, W.A.; Lynn, D.; Majka, R.; Margetis, S.; Martin, L.; Marx, J. N.; Matis, H. S.; Matulenko, Yu. A.; McShane, T. S.; Meißner, F.; Melnick, Yu; Meschanin, A.; Messer, M.; Miller, Michael L.; Milosevich, Z.; Minaev, N. G.; Mitchell, J. W.; Moiseenko, V. A.; Moltz, D.M.; Moore, C. F.; Morozov, V.; Moura, M. M. de; Munhoz, M. G.; Mutchler, G. S.; Nelson, J. M.; Nevski, P.; Nikitin, V.A.; Nogach, L. V.; Norman, B.; Nurushev, S. B.; Odyniec, G.; Ogawa, A.; Окороков, В. А.; Oldenburg, M.; Olson, D.; Paić, G.; Pandey, S. U.; Panebratsev, Y.; Panitkin, S.; Pavlinov, A. I.; Pawlak, T.; Perevoztchikov, V.; Peryt, W.; Петров, В. А.; Platner, E.D.; Pluta, J.; Porile, N.T.; Porter, J.; Poskanzer, A. M.; Potrebenikova, E.; Prindle, D.; Pruneau, C.; Radomski, S.; Rai, G.; Ravel, O.; Ray, R. L.; Razin, S. V.; Reichhold, D.; Reid, J. G.; Retière, F.; Ridiger, A.; Ritter, H. G.; Roberts, J.; Rogachevski, O. V.; Romero, J. L.; Roy, C.; Russ, D.; Rykov, VL; Sakreida, I.; Sandweiss, J.; Saulys, A. C.; Savin, I.; Schambach, Johann Joachim; Scharenberg, R. P.; Schmitz, N.; Schroeder, L. S.; Schüttauf, A.; Schweda, K.; Seger, J.; Seliverstov, D. M.; Seyboth, P.; Shahaliev, E.; Shestermanov, K. E.; Shimanskii, S. S.; Shvetcov, V. S.; Škoro, G.; Smirnov, N.; Snellings, Raimond; Sowiński, J.; Spinka, H. M.; Srivastava, B.; Stephenson, E. J.; Stock, R.; Stolpovsky, A.; Strikhanov, M.; Stringfellow, B.; Struck, C.; Suaide, A. A. P.; Sugarbaker, E.; Suire, C.; Šumbera, M.; Symons, T. J. M.; Toledo, A. Szanto de; Szarwas, P.; Takahashi, J.; Tang, A. H.; Thomas, J. H.; Tikhomirov, V. O.; Trainor, T. A.; Trentalange, S.; Tokarev, M.; Tonjes, M. B.; Trofimov, V.; Tsai, O. D.; Turner, K.; Ullrich, T.; Underwood, D. G.; Buren, G. Van; VanderMolen, A. M.; Vanyashin, A.; Vasilevski, I. M.; Vasiliev, A. N.; Vigdor, S. E.; Voloshin, S. A.; Wang, F.; Ward, H.; Watson, J. W.; Wells, R.; Wenaus, T.; Westfall, G. D.; Whitten, C.; Wieman, H.; Wilson, R. J.; Wissink, S. W.; Witt, R.; Xu, N.; Xu, Z.; Yakutin, A. E.; Yamamoto, E.; Yang, Jing; Yepes, P.; Yokosawa, A.; Yurevich, V. I.; Zanevski, Y. V.; Zborovský, I.; Zhang, H.; Zhang, W. M.; Zoulkarneev, R.; Zubarev, A. N.

doi:10.1103/physrevlett.87.279902

Cited by 161 publications

(255 citation statements)

References 0 publications

Supporting

Mentioning

235

Contrasting

Order By: Relevance

“…As mentioned above, a redistribution of the momentum anisotropy will then built up due to a mass-dependent flattening of the p T spectra caused by a radial flow generated during the hadronization process, thus resulting in the mass splitting. Similar mass ordering has been reported in RHIC [3,16,49] and LHC experiments [18], and also in AMPT simulation of AB collisions at RHIC and FAIR energies [31,43]. It is perhaps due to the quark coalescence mechanism there is a tendency, that the differential flow parameters pertaining to a particular hadron species (meson or baryon) group together.…”

Section: Species Dependence and Ncq Scalingsupporting

confidence: 73%

“…Amongst all the second harmonic coefficient, also known as the elliptic flow parameter (v 2 ), is of special interest [1]. Large v 2 values observed in Relativistic Heavy-ion Collider (RHIC) [2][3][4][5] and Large Hadron Collider (LHC) [6][7][8][9] experiments are understood to be due to a strongly interacting nature of the extended QCD state composed of loosely coupled quarks and gluons. The v 2 parameter is sensitive to the equation of state, transport properties of the medium, degree of thermalization achieved by the system, and also to the initial conditions of a collision [10][11][12][13][14].…”

Section: Introductionmentioning

confidence: 99%

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Azimuthal anisotropy in particle distribution in a multiphase transport model

2017

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Anisotropic flow of hadronic matter is considered as a sensitive tool to detect the early stage dynamics of high-energy heavy-ion collisions. Taking the event by event fluctuations of the collision geometry into account, the elliptic flow parameter and the triangular flow parameter derived from the azimuthal distribution of produced hadrons, are investigated within the framework of a multiphase transport (AMPT) model, at a collision energy that in near future will typically be available at the Facility for Antiproton and Ion Research. The dependence of elliptic and triangular flow parameters on initial fluctuations, on parton scattering cross-sections, their mass ordering on different hadron species and on the constituent quark number scaling are examined. The AMPT simulation can not exactly match the elliptic flow results on Pb + Pb collision at 40A GeV of the NA49 experiment. The simulation results presented in this work are expected to provide us with an insight to study flow properties at high baryonic density but moderate temperature, and also with an opportunity to compare similar results available from RHIC and LHC experiments.PACS number(s): 25.75.Nq, 24.10.Lx, 25.75.Ld, 25.75.Gz

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Section: Species Dependence and Ncq Scalingsupporting

confidence: 73%

Section: Introductionmentioning

confidence: 99%

Azimuthal anisotropy in particle distribution in a multiphase transport model

2017

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“…The deconfined phase of QCD matter, the quark-gluon plasma, was first discovered in collisions of heavy nuclei at the Relativistic Heavy Ion Collider [1][2][3][4][5] and confirmed at the Large Hadron Collider [6][7][8]. As in high-energy proton-proton collisions, heavy-ion collisions produce collimated sprays of particles, called jets, from highly energetic scatterings of quarks and gluons.…”

mentioning

confidence: 99%

Sorting Out Quenched Jets

2019

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We introduce a new "quantile" analysis strategy to study the modification of jets as they traverse through a droplet of quark-gluon plasma. To date, most jet modification studies have been based on comparing the jet properties measured in heavy-ion collisions to a proton-proton baseline at the same reconstructed jet transverse momentum (pT ). It is well known, however, that the quenching of jets from their interaction with the medium leads to a migration of jets from higher to lower pT , making it challenging to directly infer the degree and mechanism of jet energy loss. Our proposed quantile matching procedure is inspired by (but not reliant on) the approximate monotonicity of energy loss in the jet pT . In this strategy, jets in heavy-ion collisions ordered by pT are viewed as modified versions of the same number of highest-energy jets in proton-proton collisions, and the fractional energy loss as a function of jet pT is a natural observable (QAA). Furthermore, despite non-monotonic fluctuations in the energy loss, we use an event generator to validate the strong correlation between the pT of the parton that initiates a heavy-ion jet and the pT of the vacuum jet which corresponds to it via the quantile procedure (p quant T ). We demonstrate that this strategy both provides a complementary way to study jet modification and mitigates the effect of pT migration in heavy-ion collisions.

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“…The enhancement in v 2 in hybrid mode compared to cascade mode can be attributed to the smaller mean free path in the previous case, generating larger pressure gradients due to the assumption of mean-field approximation in the former case. Similar v 2 [52][53][54]. NCQ scaling is a natural outcome of the hadronization models based on coalescence and recombination of partons [55,56] and indicates that the collectivity developed in the early stage of the collisions is of partonic origin.…”

Section: Resultsmentioning

confidence: 86%

Anisotropic flow of charged and identified hadrons at FAIR energies and its dependence on the nuclear equation of state

2019

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In this article, we examine the equation of state (EoS) dependence of the anisotropic flow parameters (v1, v2 and v4) of charged and identified hadrons, as a function of transverse momentum (pT), rapidity (yc.m.) and the incident beam energy (E Lab ) in mid-central Au + Au collisions in the energy range E Lab = 6 − 25 A GeV. Simulations are carried out by employing different variants of the Ultra-relativistic Quantum Molecular Dynamics (UrQMD) model, namely the pure transport (cascade) mode and the hybrid mode. In the hybrid mode, transport calculations are coupled with the ideal hydrodynamical evolution. Within the hydrodynamic scenario, two different equations of state (EoS) viz. Hadron gas and Chiral + deconfinement EoS have been employed separately to possibly mimic the hadronic and partonic scenarios, respectively. It is observed that the flow parameters are sensitive to the onset of hydrodynamic expansion of the fireball in comparison to the pure transport approach. The results would be useful as predictions for the upcoming low energy experiments at Facility for Antiproton and Ion Research (FAIR) and Nuclotron-based Ion Collider fAcility (NICA).

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Publisher's Note:d¯and3He

Cited by 161 publications

References 0 publications

Azimuthal anisotropy in particle distribution in a multiphase transport model

Azimuthal anisotropy in particle distribution in a multiphase transport model

Sorting Out Quenched Jets

Anisotropic flow of charged and identified hadrons at FAIR energies and its dependence on the nuclear equation of state

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