Probing parton dynamics of QCD matter with<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi mathvariant="normal">Ω</mml:mi></mml:math>and<mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:mi>ϕ</mml:mi></mml:math>production

Adamczyk, L.; Adkins, J. K.; Agakishiev, G.; Aggarwal, M. M.; Ahammed, Z.; Alekseev, I.; Aparin, A.; Arkhipkin, D.; Aschenauer, E. C.; Attri, A.; Averichev, G. S.; Bai, Xiaozhi; Bairathi, V.; Bellwied, R.; Bhasin, A.; Bhati, A. K.; Bhattarai, P.; Bielčík, J.; Bielčíková, J.; Bland, L. C.; Bordyuzhin, I. G.; Bouchet, J.; Brandenburg, J. D.; Brandin, A. V.; Bunzarov, I.; Butterworth, J. M.; Caines, H.; Sánchez, M. Calderón De La Barca; Campbell, J. M.; Cebra, D.; Chakaberia, I.; Chaloupka, P.; Chang, Z.; Chatterjee, A.; Chattopadhyay, S.; Chen, J. H.; Chen, X.; Cheng, J.; Cherney, M.; Christie, W.; Contin, G.; Crawford, H. J.; Das, S.; Silva, L. C. De; Debbe, R.; Dedovich, T. G.; Deng, J.; Derevschikov, A. A.; Ruzza, B. Di; Didenko, L.; Dilks, C.; Dong, X.; Drachenberg, J. L.; Draper, J. E.; Du, C. M.; Dunkelberger, L. E.; Dunlop, J. C.; Efimov, L. G.; Engelage, J.; Eppley, G.; Esha, R.; Evdokimov, O.; Eyser, O.; Fatemi, R.; Fazio, S.; Federic, P.; Fedorišin, J.; Feng, Z.; Filip, P.; Fisyak, Y.; Flores, C.; Fulek, Ł.; Gagliardi, C. A.; Garand, D.; Geurts, F. J. M.; Gibson, A.; Girard, Martin; Greiner, L.; Grosnick, D.; Gunarathne, D. S.; Guo, Y.; Gupta, S.; Gupta, A.; Guryn, W.; Hamad, A. I.; Hamed, A.; Haque, R.; Harris, J. W.; He, L.; Heppelmann, S.; Hirsch, A.; Hoffmann, G. W.; Horvat, S.; Huang, T.; Huang, X.; Huang, B.; Huang, H. Z.; Huck, P.; Humanic, T. J.; Igo, G.; Jacobs, W. W.; Jang, H. J.; Jentsch, A.; Jia, J.; Jiang, K.; Judd, E. G.; Kabana, S.; Kalinkin, D.; Kang, K.; Kauder, K.; Ke, H. W.; Keane, D.; Kechechyan, A.; Khan, Z. H.; Kikoła, D. P.; Kisel, I.; Kisiel, A.; Kochenda, L.; Koetke, D. D.; Kosarzewski, L. K.; Kraishan, A. F.; Кравцов, П.; Krueger, K.; Kumar, L.; Lamont, M. A.C.; Landgraf, J. M.; Landry, K. D.; Lauret, J.; Lebedev, A.; Lednický, R.; Lee, J. H.; Li, X.; Li, C.; Li, Y.; Li, W.; Lin, T.; Lisa, M. A.; Liu, F.; Ljubičić, T.; Llope, W. J.; Lomnitz, M.; Longacre, R. S.; Luo, X.; Ma, R.; L., G.; G., Y.; Ma, L.; Magdy, N.; Majka, R.; Manion, A.; Margetis, S.; Markert, C.; Matis, H. S.; McDonald, D.; McKinzie, S.; Meehan, K.; Mei, J. C.; Minaev, N. G.; Mioduszewski, S.; Mishra, D.; Mohanty, B.; Mondal, M. M.; Morozov, D. A.; Mustafa, M. K.; Nandi, B. K.; Nasim, Md.; Nayak, T. K.; Nigmatkulov, G.; Niida, T.; Nogach, L. V.; Noh, S. Y.; Novák, J.; Nurushev, S. B.; Odyniec, G.; Ogawa, A.; Oh, K.; Okorokov, V.; Olvitt, D.; Page, B. S.; Pak, R.; Pan, Y. X.; Pandit, Y.; Panebratsev, Y.; Pawlik, B.; Pei, H.; Perkins, C.; Pile, P.; Pluta, J.; Poniatowska, K.; Porter, J.; Posik, M.; Poskanzer, A. M.; Pruthi, N. K.; Putschke, J.; Qiu, H.; Quintero, A.; Ramachandran, S.; Raniwala, S.; Raniwala, R.; Ray, R. L.; Ritter, H. G.; Roberts, J.; Rogachevskiy, O. V.; Romero, J. L.; Ruan, L.; Rusňák, J.; Rusnakova, O.; Sahoo, N.; Sahu, P. K.; Sakrejda, I.; Salur, S.; Sandweiss, J.; Sarkar, A.; Schambach, J.; Scharenberg, R. P.; Schmah, A.; Schmidke, W. B.; Schmitz, N.; Seger, J.; Seyboth, P.; Shah, N.; Shahaliev, E.; Shanmuganathan, P. V.; Shao, M.; Sharma, A.; Sharma, B.; Sharma, Meenakshi; Shen, W. Q.; Shi, Z.; Shi, S. S.; Shou, Q.; Sichtermann, E. P.; Sikora, R.; Simko, M.; Singha, S.; Skoby, M. J.; Smirnov, N.; Smirnov, D.; Solyst, W.; Song, L.; Sorensen, P.; Spinka, H. M.; Srivastava, B.; Stanislaus, T. D. S.; Stepanov, M.; Stock, R.; Strikhanov, M.; Stringfellow, B.; Šumbera, M.; Summa, B.; Sun, Zhi‐Wei; Sun, X. M.; Sun, Y. J.; Surrow, B.; Svirida, D. N.; Tang, Z.; Tang, A. H.; Tarnowsky, T.; Tawfik, A.; Thäder, J.; Thomas, J. H.; Timmins, A. R.; Tlusty, D.; Todoroki, T.; Tokarev, M.; Trentalange, S.; Tribble, R. E.; Tribedy, P.; Tripathy, S. K.; Tsai, O. D.; Ullrich, T.; Underwood, D. G.; Upsal, I.; Buren, G. Van; Nieuwenhuizen, G. van; Vandenbroucke, M.; Varma, R.; Vasiliev, A.; Vértesi, R.; Videbæk, F.; Vokál, S.; Voloshin, S. A.; Vossen, A.; Wang, F.; Wang, G.; Wang, J. S.; Wang, H.; Wang, Y.; Webb, G.; Webb, J. C.; Wen, L.; Westfall, G. D.; Wieman, H.; Wissink, S. W.; Witt, R.; Wu, Y.; Zhang, Xiao; Xie, W.; Xie, G.; Xin, K.; Xu, Y.; Xu, Q. H.; Xu, N.; Xu, H. S.; Xu, Z.; Xu, Jun; Yang, S.; Yang, Yi; Yang, C.; Yang, Q.; Ye, Z.; Yepes, P.; Yi, L.; Yip, K.; Yoo, I. K.; Yu, N.; Zbroszczyk, H.; Zha, W.; Zhang, X. P.; Zhang, Y.; Zhang, J.; Zhang, S.; Zhang, Z.; Zhang, J. B.; Zhao, Feng; Zhao, J.; Chen, Zhong; Zhou, Long; Zhu, X.; Zoulkarneeva, Y.; Zyzak, M.

doi:10.1103/physrevc.93.021903

Cited by 57 publications

(66 citation statements)

References 135 publications

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“…In such a program, the energy dependence of φ(ss) meson production plays a crucial role, since it has small hadronic interaction cross-section and freeze-out early compared to other non-strange hadrons [3,4,5]. The first phase of the beam energy scan program has been completed and the results are being available to understand the properties of produced matter created in heavy-ion collisions [6,7,8,9,10,11,12,13,14,15,16]. Various observables are compared to theoretical calculations to understand the physical mechanism behind the measurements [17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35].…”

Section: Introductionmentioning

confidence: 99%

“…and (b) φ at mid-rapidity as a function of transverse momentum in Au+Au collisions at √ s NN = 11.5 GeV for 0-5%, 20-30% and 60-70% (40-60% for φ) centralities. Solid star marker represents experimentally measured values[12,11] and open circle represents AMPT model calculation using parameters set 1 (a=0.55 and b =0.15) and set 2 (a=2.2 and b =0.15) (Color online) Invariant yield of (a) π − and (b) φ at mid-rapidity as a function of transverse momentum in U+U collisions at √ s NN = 196 GeV for 0-5%, 20-30% and 60-70% centralities. The AMPT model calculation using parameters set 1 (a=0.55 and b =0.15) which explains data for Au+Au collisions at √ s NN = 200 GeV.…”

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Constraining input parameters of AMPT model with ϕ meson production

Tiwari

Nasim

2020

Nuclear Physics A

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A Multi-Phase Transport Model (AMPT) has been extensively used to understand the physics behind the experimental observation. Like other models, the outcome of the AMPT model depends on the initial parameters. Therefore, one needs to choose suitable initial parameters before using the model. Lund string fragmentation function has been used to create quark-antiquarks pairs in the AMPT model. The Lund string fragmentation parameters determine the yields and transverse momentum (p T ) spectra of particles produced in nucleus-nucleus collisions. The values of Lund string fragmentation parameters were determined by fitting the charged particle yield and p T spectra measured in the experiment. In this paper, we have shown the yield of strange quarks carrying hadrons, e.g. φ mesons, are more sensitive to Lund string fragmentation parameters compared to non-strange pions. Using φ meson spectra measured at RHIC, we have obtained new sets of Lund parameters for Au+Au collisions at √ s NN = 11.5, 39, and 200 GeV. We have found that using the same set of parameters, we can explain φ-meson yield at √ s NN = 39 and 200 GeV, however, we need a different set of parameters for √ s NN = 11.5 GeV. This suggests that at low energy, √ s NN = 11.5 GeV, the underlying mechanism for particle production is different compared to top RHIC energies. We have also predicted invariant yield of π and φ mesons as a function of p T in U+U collisions at √ s NN = 196 GeV to be measured by STAR experiment.

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Section: Introductionmentioning

confidence: 99%

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confidence: 99%

Constraining input parameters of AMPT model with ϕ meson production

Tiwari

Nasim

2020

Nuclear Physics A

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“…The experimental programs of heavy ion collisions which are planned at RHIC (BNL) [1], NICA (JINR) [2] and FAIR (GSI) [3] are aimed to study the phase diagram of strongly interacting matter. The major tasks of these experiments are a determination of the threshold collision energies of two phase transitions (PTs) expected to exist in quantum chromodynamics (QCD) and a location of their tricritical (or two critical endpoints).…”

Section: Introductionmentioning

confidence: 99%

Possible signals of two QCD phase transitions at NICA-FAIR energies

et al. 2019

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“…Comprehensive v 1 measurement from STAR [15] supports the coalescence mechanism as the dominant process in particle formation dynamics. There are several studies in heavy-ion collisions to understand the hadron and nuclei formation via coalescence and also hadronization of quarks in heavy-ion collisions [23][24][25][26][27][28][29][30]. In recent articles the importance of coalescence mechanism and energy dependence directed flow are discussed [31][32][33][34][35] and an experimental review of v 1 can be found in Ref.…”

Section: Introductionmentioning

confidence: 99%