Charged particle density distributions in Au induced interactions with emulsion nuclei at 10.7 A GeV

Adamovich, M. I.; Aggarwal, M. M.; Alexandrov, Y. A.; Amirikas, R.; Andreeva, N. P.; Anzon, Z.V.; Arora, R.; Avetyan, F. A.; Badyal, S. K.; Bakich, A. M.; Basova, E.S.; Bazarov, I.K.; Bhalla, K. B.; Bhasin, A.; Bhatia, V. S.; Bogdanov, V. G.; Bradnová, V.; Bubnov, V. I.; Burnett, T. H.; Cai, X.; Carshiev, D. A.; Chasnikov, I.Ya.; Chernova, L. P.; Chernyavski, M. M.; Dhamija, S.; Eligbaeva, G. Z.; Eremenko, L.E.; Gaitinov, A. S.; Ganssauge, E.; Garpman, S.; Gerassimov, S.; Graf, Christian; Grote, J.; Gulamov, K. G.; Gupta, S.; Gupta, V. K.; Jakobsson, B.; Just, L.; Kachroo, S.; Kalyachkina, G. S.; Kanygina, É. K.; Karábova, M.; Kitroo, S.; Kharlamov, S. P.; Kovalenko, A. D.; Krasnov, S. A.; Kumar, Vinod; Larionova, V. G.; Li, Y.D.; Liu, L.S.; Lokanatan, S.; Lord, J. J.; Lukicheva, N. S.; Luo, S.; Mangotra, L. K.; Marutyan, N. A.; Mashkov, A.Y.; Maslennikova, N. V.; Mittra, I. S.; Mokerjee, S.; Nasyrov, S.Z.; Navotny, V. S.; Nystrand, J.; Ochs, M.; Orlova, G. I.; Otterlund, I.; Peak, L. S.; Peresadko, N. G.; Petrov, N. V.; Plyushchev, V. A.; Rusakova, V. V.; Qian, W. Y.; Qin, Y.; Raniwala, R.; Rao, N. Kameswara; Roeper, M.; Saidkhanov, N.; Salmanova, N. A.; Sarkisova, L. G.; Sarkisyan, V. R.; Shabratova, G.; Seitimbetov, A.M.; Shakhova, C.I.; Shpilev, S. N.; Skelding, D.; Söderström, K.; Solovjeva, Z. I.; Stenlund, E.; Svechnikova, L. N.; Svensson, Tomas; Tóthová, Monika; Tretyakova, M. I.; Trofimova, T. P.; Tuleeva, U.; Tursunov, B.P.; Vokál, S.; Vrláková, J.; Wang, H.Q.; Weng, Z.; Wilkes, R. J.; Xia, Yin; Yang, C. B.; Zhang, D.H.; Zheng, P. Y.; Zhokhova, S. I.; Zhou, D.

doi:10.1016/0370-2693(95)00521-l

Cited by 29 publications

(9 citation statements)

References 8 publications

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“…which satisfies approximately the Gaussian distribution with the width of σ η ≈ 0.91 [15]. The distribution of y is expected to obey the Gaussian distribution with the width of σ y < σ η .…”

Section: Formalism and Methodsmentioning

confidence: 95%

Comparing a few distributions of transverse momenta in high energy collisions

2019

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Transverse momentum spectra of particles produced in high energy collisions are very important due to their relations to the excitation degree of interacting system. To describe the transverse momentum spectra, one can use more than one probability density functions of transverse momenta, which are simply called the functions or distributions of transverse momenta in some cases. In this paper, a few distributions of transverse momenta in high energy collisions are compared with each other in terms of plots to show some quantitative differences. Meanwhile, in the framework of Tsallis statistics, the distributions of momentum components, transverse momenta, rapidities, and pasudorapidities are obtained according to the analytical and Monte Carlo methods. These analyses are useful to understand carefully different distributions in high energy collisions.

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Section: Formalism and Methodsmentioning

confidence: 95%

Comparing a few distributions of transverse momenta in high energy collisions

2019

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“…In the figure 3, we have plotted the interaction mean free path of different projectiles ( 16 O, 40 Ar, 12 C, 14 C, 24 Mg, 28 Si, 32…”

Section: Nucleon-nucleon Interaction (mentioning

confidence: 99%

“…For the protonnucleus/proton collisions: (27) From the nucleusnucleus collisions: (29) From the equation (27), one can understand that the average multiplicity of singly charged relativistic particles in the protonemulsion interactions (<n s > P-Em ), linearly depends on the charged particle multiplicity in the case of protonproton interaction (<n s > PP ), at the same energy [22][23][24][25][26]. Addition of the resultant values of equation (28) and (29), one can get the average multiplicity of singly charged relativistic particles for 84 Kr-Em interaction at ~1GeV/n.…”

Section: Nucleon-nucleon Interaction (mentioning

confidence: 99%

“…The participant's nucleons and binary collision involved in the collision lead to the calculation of nuclear matter effects. According to the Adamovich [22][23][24][25][26] empirical formula, one can easily calculate the average number of shower particles (<N S >) value using the total number of participants and binary collision. Here we have calculated the average number of shower particles value and are compared with corresponding experimental results.…”

Section: Introductionmentioning

confidence: 99%

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Analysis of Various Projectile Interactions with Nuclear Emulsion Detector Nuclei at ~1 GeV per Nucleon Using Coulomb Modified Glauber Model

Marimuthu

Singh

Inbanathan

2017

Advances in High Energy Physics

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The total nuclear reaction cross section is calculated considering the cases with and without medium effect by employing Coulomb modified Glauber model (CMGM) , and 238 U 92 with nuclear emulsion detector (NED) nuclei at around 1 GeV per nucleon incident kinetic energy. These calculated nuclear reaction cross sections are correlated with the different target groups of the NED nuclei. The average value of various parameters is also calculated and compared with the corresponding experimental results. The number of shower particles emitted in an interaction is also calculated and showed good agreement with the experimental result. We observed that the total nuclear reaction cross section increases with increasing the target mass number in case of all the considered projectiles. In addition, it is shown that the average value of reaction cross section with nuclear medium effect is in good agreement with the experimental results for projectiles 56 Fe, 84 Kr, and 132 Xe, although results of projectiles 197 Au and 238 U are not in agreement with the experimental observations. This study sheds some light on the energy dependence of the nuclear reaction cross section.

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“…These results mainly belong to the interactions of hadrons and light nuclei. We have used the experimental data of Kr+Em -reaction at 0.95 A GeV [6] and Au+Em -reaction at 10.7 A GeV [7] to analyze angular distribution of secondary slow particles as a function of centrality [8].…”

Section: Introductionmentioning

confidence: 99%

Search for a signal on intermediate baryon systems formation in hadron-nuclear and nuclear-nuclear interactions at high energies

Huseynaliyev

Suleymanov

Khan

et al. 2008

J. Phys.: Conf. Ser.

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We have analyzed the behavior of different characteristics of hadron-nuclear and nuclear-nuclear interactions as a function of centrality to get a signal on the formation of intermediate baryon systems. We observed that the data demonstrate the regime change and saturation. The angular distributions of slow particles exhibit some structure in the above mentioned reactions at low energy. We believe that the structure could be connected with the formation and decay of the percolation cluster. With increasing the mass of colliding nuclei, the structure starts to become weak and almost disappears ultimately. This shows that the number of secondary internuclear interactions increases with increasing the mass of the colliding nuclei. The latter could be a reason of the disintegration of any intermediate formations as well as clusters, which decrease their influence on the angular distribution of the emitted particles.

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Charged particle density distributions in Au induced interactions with emulsion nuclei at 10.7 A GeV

Cited by 29 publications

References 8 publications

Comparing a few distributions of transverse momenta in high energy collisions

Comparing a few distributions of transverse momenta in high energy collisions

Analysis of Various Projectile Interactions with Nuclear Emulsion Detector Nuclei at ~1 GeV per Nucleon Using Coulomb Modified Glauber Model

Search for a signal on intermediate baryon systems formation in hadron-nuclear and nuclear-nuclear interactions at high energies

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