Dijet imbalance measurements in 
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Adamczyk, L.; Adkins, J. K.; Agakishiev, G.; Aggarwal, M. M.; Ahammed, Z.; Alekseev, I.; Anderson, D. M.; Aoyama, R.; Aparin, A.; Arkhipkin, D.; Aschenauer, E. C.; Ashraf, M. U.; 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.; Brown, D. S.; Bunzarov, I.; Butterworth, J.; Caines, H.; Sánchez, M. Calderón De La Barca; Campbell, John 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.; Didenko, L.; Dilks, C.; Dong, X.; Drachenberg, J. L.; Draper, J. E.; Du, C. M.; Dunkelberger, L. E.; Dunlop, J. C.; Efimov, L. G.; Elsey, N.; Engelage, J.; Eppley, G.; Esha, R.; Esumi, S.; Evdokimov, O.; Ewigleben, J.; Eyser, O.; Fatemi, R.; Fazio, S.; Federic, P.; Fedorišin, J.; Feng, Z.; Filip, P.; Finch, E.; 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, A.; Gupta, S.; Guryn, W.; Hamad, A. I.; Hamed, A.; Haque, R.; Harris, J. W.; He, L.; Heppelmann, S.; Hirsch, A.; Hoffmann, G. W.; Horvat, S.; Huang, X.; Huang, B.; Huang, H. Z.; Huang, T.; Huck, P.; Humanic, T. J.; Igo, G.; Jacobs, W. W.; Jentsch, A.; Jia, J.; Jiang, K.; Jowzaee, S.; 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, W.; Li, X.; Li, Y.; Li, C.; Lin, T.; Lisa, M. A.; Liu, Y.; Liu, F.; Ljubičić, T.; Llope, W. J.; Lomnitz, M.; Longacre, R. S.; Luo, X.; Luo, S.; L., G.; Ma, L.; Ma, R.; G., Y.; Magdy, N.; Majka, R.; Manion, A.; Margetis, S.; Markert, C.; Matis, H. S.; McDonald, D.; McKinzie, S.; Meehan, K.; Mei, J. C.; Miller, Z. W.; Minaev, N. G.; Mioduszewski, S.; Mishra, D.; Mohanty, B.; Mondal, M. M.; Морозов, Д. А.; Mustafa, M. K.; Nasim, Md.; Nayak, T. K.; Nigmatkulov, G.; Niida, T.; Nogach, L. V.; Nonaka, T.; Novák, J.; Nurushev, S. B.; Odyniec, G.; Ogawa, A.; Oh, K.; Окороков, В. А.; 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.; Przybycień, M.; Putschke, J.; Qiu, H.; Quintero, A.; Ramachandran, S.; Ray, R. L.; Reed, R.; Rehbein, M. J.; Ritter, H. G.; Roberts, J.; Rogachevskiy, O. V.; Romero, J. L.; Roth, J. D.; Ruan, L.; Rusňák, J.; Rusnakova, O.; Sahoo, N.; Sahu, P. K.; Sakrejda, I.; Salur, S.; Sandweiss, J.; 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, Meenakshi; Sharma, A.; Sharma, B.; Shen, W. Q.; Shi, S. S.; Shi, Z.; Shou, Q.; Sichtermann, E. P.; Sikora, R.; Simko, M.; Singha, S.; Skoby, M. J.; Smirnov, D.; Smirnov, N.; Solyst, W.; Song, L.; Sorensen, P.; Spinka, H. M.; Srivastava, B.; Stanislaus, T. D. S.; Stepanov, M.; Stock, R.; Strikhanov, M.; Stringfellow, B.; Sugiura, T.; Šumbera, M.; Summa, B.; Sun, X. M.; Sun, Z. J.; 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; Vasiliev, A. N.; Vértesi, R.; Videbæk, F.; Vokál, S.; Voloshin, S. A.; Vossen, A.; Wang, F.; Wang, J. S.; Wang, G.; Wang, Y.; Webb, G.; Webb, J. C.; Wen, L.; Westfall, G. D.; Wieman, H.; Wissink, S. W.; Witt, R.; Wu, Y.; Zhang, Xiao; Xie, G.; Xie, W.; Xin, K.; Xu, Q. H.; Xu, H.; Xu, Y.; Xu, Z.; Xu, Jun; Xu, N.; Yang, S.; Yang, Q.; Yang, Yi; Yang, C.; Ye, Z.; Yi, L.; Yip, K.; Yoo, I. K.; Yu, N.; Zbroszczyk, H.; Zha, W.; Zhang, X. P.; Zhang, J.; Zhang, Z.; Zhang, S.; Zhang, J. B.; Zhang, Y.; Zhao, J.; Chen, Zhong; Zhou, Long; Zhu, X.; Zoulkarneeva, Y.; Zyzak, M.

doi:10.1103/physrevlett.119.062301

Cited by 49 publications

(57 citation statements)

References 47 publications

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“…Still, both the Taylor and the sector methods can be systematically improved to cover more of the range of interest for the Beam Energy Scan II program. Given the high chemical freeze-out temperatures for |S| = 1 particles -see Section VII -that emerge from STAR data ( [56] and preliminary [57]), the use of continuum extrapolated lattice simulations to calculate the grand canonical features of QCD is highly motivated.…”

Section: B Sector Methodsmentioning

confidence: 99%

“…4 is also monotonic, converging to 1/3 at high T , which is the electric charge of the strange quark. At low temperatures this quantity is dominated by the charged kaons, which were in the focus of recent experimental investigations [56].…”

Section: Lattice Qcd and The Grand Canonical Ensemblementioning

confidence: 99%

“…(30) and (35), along the same freeze-out lines used in Fig. 16, and compare them to available experimental results from the STAR Collaboration [56,57]. The important difference is that now the experimental cuts are the ones taken from the actual measurements, and namely they are not the same for the different species.…”

Section: Bsssmentioning

confidence: 99%

“…16 the same cuts are applied to both Λ and K, while in Fig. 17 the cuts utilized are those from the experimental analyses, namely 0.9 < p T < 2.0 GeV, |y| < 0.5 for net-Λ [57] and 0.4 < p T < 1.6 GeV, |y| < 0.5 for net-kaon [56]. Due to this difference in the applied kinematic cuts, more than for χ B 2 /χ Q 2 .…”

Section: Bsssmentioning

confidence: 99%

“…Previous studies found that, for certain particle species, fluctuations are more sensitive to the freeze-out parameters than yields [53]. In recent years, the STAR Collaboration has published results for the fluctuations of net-proton [54], net-charge [55], net-kaon [56], and more recently net-Λ [57] and for correlators between different hadronic species [57,58]. From the analysis of netproton and net-charge fluctuations in the HRG model, it was found that the obtained freeze-out temperatures are lower than the corresponding ones from fits of the yields [52].…”

Section: Introductionmentioning

confidence: 99%

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Off-diagonal correlators of conserved charges from lattice QCD and how to relate them to experiment

et al. 2020

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Like fluctuations, non-diagonal correlators of conserved charges provide a tool for the study of chemical freeze-out in heavy ion collisions. They can be calculated in thermal equilibrium using lattice simulations, and be connected to moments of event-by-event net-particle multiplicity distributions. We calculate them from continuum extrapolated lattice simulations at µB = 0, and present a finite-µB extrapolation, comparing two different methods. In order to relate the grand canonical observables to the experimentally available net-particle fluctuations and correlations, we perform a Hadron Resonance Gas (HRG) model analysis, which allows us to completely break down the contributions from different hadrons. We then construct suitable hadronic proxies for fluctuations ratios, and study their behavior at finite chemical potentials. We also study the effect of introducing acceptance cuts, and argue that the small dependence of certain ratios on the latter allows for a direct comparison with lattice QCD results, provided that the same cuts are applied to all hadronic species. Finally, we perform a comparison for the constructed quantities for experimentally available measurements from the STAR Collaboration. Thus, we estimate the chemical freeze-out temperature to 165 MeV using a strangeness-related proxy. This is a rather high temperature for the use of the Hadron Resonance Gas, thus, further lattice studies are necessary to provide first principle results at intermediate µB.Hadron Collider (LHC) have been able to create the Quark Gluon Plasma (QGP) in the laboratory, and explore the low-to-moderate baryon density region of the QCD phase diagram.At low baryon density, the transition from a hadron gas to a deconfined QGP was shown by lattice QCD calculations to be a broad crossover [1] at T 155 MeV [1][2][3][4]. At large baryon densities, the nature of the phase transition is expected to change into first order, thus implying the presence of a critical end point. A strong experimental effort is currently in place through the second Beam

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Section: B Sector Methodsmentioning

confidence: 99%

Section: Lattice Qcd and The Grand Canonical Ensemblementioning

confidence: 99%

Section: Bsssmentioning

confidence: 99%

Section: Bsssmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Off-diagonal correlators of conserved charges from lattice QCD and how to relate them to experiment

et al. 2020

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Evolution of the mean jet shape and dijet asymmetry distribution of an ensemble of holographic jets in strongly coupled plasma

Brewer

Rajagopal

Sadofyev

et al. 2018

J. High Energ. Phys.

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Some of the most important experimentally accessible probes of the quarkgluon plasma (QGP) produced in heavy ion collisions come from the analysis of how the shape and energy of sprays of energetic particles produced within a cone with a specified opening angle (jets) in a hard scattering are modified by their passage through the strongly coupled, liquid, QGP. We model an ensemble of back-to-back dijets for the purpose of gaining a qualitative understanding of how the shapes of the individual jets and the asymmetry in the energy of the pairs of jets in the ensemble are modified by their passage through an expanding cooling droplet of strongly coupled plasma, in the model in a holographic gauge theory that is dual to a 4+1-dimensional black-hole spacetime that is asymptotically anti-de Sitter (AdS). We build our model by constructing an ensemble of strings in the dual gravitational description of the gauge theory. We model QCD jets in vacuum using strings whose endpoints are moving "downward" into the gravitational bulk spacetime with some fixed small angle, an angle that represents the opening angle (ratio of jet mass to jet energy) that the QCD jet would have in vacuum. Such strings must be moving through the gravitational bulk at (close to) the speed of light; they must be (close to) null. This condition does not specify the energy distribution along the string, meaning that it does not specify the shape of the jet being modeled. We study the dynamics of strings that are initially not null and show that strings with a wide range of initial conditions rapidly accelerate and become null and, as they do, develop a similar distribution of their energy density. We use this distribution of the energy density along the string, choose an ensemble of strings whose opening angles and energies are distributed as in perturbative QCD, and Open Access, c The Authors. Article funded by SCOAP 3 .https://doi.org/10.1007/JHEP02 (2018)015 JHEP02 (2018)015 show that we can then fix one of the two model parameters such that the mean jet shape for the jets in the ensemble that we have built matches that measured in proton-proton collisions reasonably well. This is a novel way for hybridizing relevant inputs from perturbative QCD and a strongly coupled holographic gauge theory in the service of modeling jets in QGP. We send our ensemble of strings through an expanding cooling droplet of strongly coupled plasma, choosing the second model parameter so as to get a reasonable value for R jet AA , the suppression in the number of jets, and study how the mean jet shape and the dijet asymmetry are modified, comparing both to measurements from heavy ion collisions at the LHC.

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First measurement of large area jet transverse momentum spectra in heavy-ion collisions

Sirunyan

Tumasyan²,

Adam³

et al. 2021

J. High Energ. Phys.

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Jet production in lead-lead (PbPb) and proton-proton (pp) collisions at a nucleon-nucleon center-of-mass energy of 5.02 TeV is studied with the CMS detector at the LHC, using PbPb and pp data samples corresponding to integrated luminosities of 404 μb−1 and 27.4 pb−1, respectively. Jets with different areas are reconstructed using the anti-kT algorithm by varying the distance parameter R. The measurements are performed using jets with transverse momenta (pT) greater than 200 GeV and in a pseudorapidity range of |η| < 2. To reveal the medium modification of the jet spectra in PbPb collisions, the properly normalized ratio of spectra from PbPb and pp data is used to extract jet nuclear modification factors as functions of the PbPb collision centrality, pT and, for the first time, as a function of R up to 1.0. For the most central collisions, a strong suppression is observed for high-pT jets reconstructed with all distance parameters, implying that a significant amount of jet energy is scattered to large angles. The dependence of jet suppression on R is expected to be sensitive to both the jet energy loss mechanism and the medium response, and so the data are compared to several modern event generators and analytic calculations. The models considered do not fully reproduce the data.

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Dijet imbalance measurements in Au+Au and pp collisions at sNN

Cited by 49 publications

References 47 publications

Off-diagonal correlators of conserved charges from lattice QCD and how to relate them to experiment

Off-diagonal correlators of conserved charges from lattice QCD and how to relate them to experiment

Evolution of the mean jet shape and dijet asymmetry distribution of an ensemble of holographic jets in strongly coupled plasma

First measurement of large area jet transverse momentum spectra in heavy-ion collisions

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