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Current issue   Ukr. J. Phys. 2014, Vol. 58, N 8, p.709-718
https://doi.org/10.15407/ujpe58.08.0709    Paper

El-Bakry M.Y.1,2, El-Sayed A. El-Dahshan 3,4, Abd El-Hamied E.F.1

1 Department of Physics, Faculty of Education, Ain Shams University
(Roxy, Cairo, Egypt)
2 Buraydah Tabouk University, Faculty of Science, Department of Physics
(Tabouk, KSA)
3 Dept. of Phys., Faculty of Science, Ain Shams University
(Abbasia, Cairo, Egypt; e-mail: esldahshan@eelu.edu.eg)
4 Egyptian E-Learning University
(33, El-Mesah Str., El-Dokki-Giza-Postal code 1261, Egypt)

Charged Particle Pseudorapidity Distributions for Pb?Pb and Au?Au Collisions Using Neural Network Model

Section: Nuclei and nuclear reactions
Original Author's Text: English

Abstract: The artificial neural network (ANN) approach is used to model the Pb–Pb and Au–Au collisions on the basis of the Levenberg–Marquardt learning algorithm. We simulate the rapidity distribution for ? ? and ? ± produced in Pb–Pb collisions at different energies and the pseudorapidity distribution of charged particles in Au–Au collisions. Our functions obtained within the ANN model show a very good agreement with the experimental data for both types of collisions, which indicates that the trained network takes on the optimal generalization performance. Thus, the ANN model can be widely applied to the modeling of heavy-ion collisions

Key words: charged particles, neural network, pseudorapidity distribution, Pb–Pb and Au– Au collisions, simulation.

References:

  1. M. Mitrovski, T. Schuster, G. Gr¨af, H. Petersen, and M. Bleicher, arXiv: nucl-th/ 08122041.
  2. F.H. Liu, Chin. J. Phys. 38, 42 (2000).
  3. C.R. Meng, Chin. Phys. Lett. 26, 102501 (2009).
     https://doi.org/10.1088/0256-307X/26/1/018501
  4. F.H. Liu, Jain-Xin Sun, and Er-Qin Wang, Chin. Phys. Lett. 27, 032503 (2010).
  5. K. Werner, Phys. Rep. 232, 87 (1995).
     https://doi.org/10.1016/0370-1573(93)90078-R
  6. G.D. Westfall et al., Phys. Rev. Lett. 37, 1202 (1976).
     https://doi.org/10.1103/PhysRevLett.37.1202
  7. F.H. Liu, Acta Phys. Sin. 7, 321 (1998).
  8. F.H. Liu and Y.A. Panebratsev, Nucl. Phys. A 641, 379 (1998).
     https://doi.org/10.1016/S0375-9474(98)00475-8
  9. F.H. Liu and Y.A. Panebratsev, Phys. Rev. C 59, 1193 (1999).
     https://doi.org/10.1103/PhysRevC.59.1193
  10. F.H. Liu and Y.A. Panebratsev, Phys. Rev. C textbf59, 1798 (1999).
  11. F.H. Liu, Phys. Lett. B 583, 68 (2004).
     https://doi.org/10.1016/j.physletb.2003.12.059
  12. F.H. Liu, D.H. Zhang, and M.Y. Duan, Europhys. Lett. 61, 736 (2003).
     https://doi.org/10.1209/epl/i2003-00290-6
  13. F.H. Liu, X.Y. Yin, J.L. Tian, and N.N. Abd Allah, Phys. Rev. C 69, 034905 (2004).
     https://doi.org/10.1103/PhysRevC.69.034905
  14. A.B. Kaidalov, Phys. Lett. B 116, 459 (1982).
     https://doi.org/10.1016/0370-2693(82)90168-X
  15. A.B. Kaidalov and K.A. Ter-Martirosyan, Phys. Lett. B 117, 247 (1982).
     https://doi.org/10.1016/0370-2693(82)90556-1
  16. N.S. Amelin et al., Phys. Rev. C47, 2299 (1993).
     https://doi.org/10.1103/PhysRevC.47.2299
  17. G. Burau et al., Phys. Rev. C 71, 054905 (2005).
     https://doi.org/10.1103/PhysRevC.71.054905
  18. E.E. Zabrodin et al., J. Phys. G 31, S995 (2005).
     https://doi.org/10.1088/0954-3899/31/6/045
  19. J. Dias de Deus and J.G. Milhano, Nucl. Phys. A 795, 8 (2007).
     https://doi.org/10.1016/j.nuclphysa.2007.08.007
  20. X.N. Wang, Phys. Rev. D 43, 104 (1991).
     https://doi.org/10.1103/PhysRevD.43.104
  21. X.N. Wang and M. Gyulassy, Phys. Rev. D 44, 3501 (1991).
     https://doi.org/10.1103/PhysRevD.44.3501
  22. X.N. Wang and M. Gyulassy, Phys. Rev. Lett. 68, 1480 (1992).
     https://doi.org/10.1103/PhysRevLett.68.1480
  23. B.A. Li and C.M. Ko, Phys. Rev. C 52, 2037 (1995).
     https://doi.org/10.1103/PhysRevC.52.2037
  24. B. Zhang, Comput. Phys. Commun. 109, 193 (1998).
     https://doi.org/10.1016/S0010-4655(98)00010-1
  25. D. Kharzeev, E. Levin, and L. McLerran, Phys. Lett. B 561, 93 (2003).
     https://doi.org/10.1016/S0370-2693(03)00420-9
  26. H. Sorge, H. Stocker, and W. Greiner, Nucl. Phys. A 498, 567 (1989).
     https://doi.org/10.1016/0375-9474(89)90641-6
  27. H. Sorge, A. von Keitz, R. Mattiello, H. Stocker, and W. Greiner, Nucl. Phys. A 525, 95 (1991).
     https://doi.org/10.1016/0375-9474(91)90317-Y
  28. A. Jahns et al., Nucl. Phys. A 566, 483 (1994).
     https://doi.org/10.1016/0375-9474(94)90674-2
  29. K. Tywoniuk et al., Phys. Lett. B 657, 170 (2007).
     https://doi.org/10.1016/j.physletb.2007.09.065
  30. R.B. Clare and D. Strottmann, hys. Rep. 141, 177 (1986).
     https://doi.org/10.1016/0370-1573(86)90090-6
  31. U. Ornik, R.M. Weiner, and G. Wilk, Nucl. Phys. A 566, 469 (1994).
     https://doi.org/10.1016/0375-9474(94)90671-8
  32. Y. Pang, T.J. Schlagel, and S.H. Kahana, Nucl. Phys. A 544, 453 (1992).
     https://doi.org/10.1016/0375-9474(92)90592-8
  33. Y. Pang, T.J. Schlagel, and S.H. Kahana, Phys. Rev. Lett. 68, 2743 (1992).
     https://doi.org/10.1103/PhysRevLett.68.2743
  34. S.H. Kahana, T.J. Schlagel, and Y. Pang, Nucl. Phys. A 566, 465 (1994).
     https://doi.org/10.1016/0375-9474(94)90670-X
  35. A.K. Hamid, Can J. Phys. 76-63-7 (1998).
  36. P. Bhatet et al., Proceedings of the Summer Study on HEP, Snowmass, Colorado, 1990.
  37. R.P. Lippman, IEEE Acoust. Speech Signal Process. Mag., No. 4, 4-22 (1987).
  38. M.Y. El-Bakry and K.A. El-Metwally, Solit. Fract. 16, 279 (2003).
     https://doi.org/10.1016/S0960-0779(02)00318-1
  39. S.V. Afanasiev et al., Phys. Rev. C 66, 054902 (2002); [arXiv:nucl-ex/0205002].
     https://doi.org/10.1103/PhysRevC.66.054902
  40. M. Ga'zdzicki, C. Alt et al., J. Phys. G 30, S119 (2004); [arXiv:nucl-ex/0403023].
     https://doi.org/10.1088/0954-3899/30/1/011
  41. C. Alt et al., [NA49 Collaboration], Phys. Rev. C 77, 024903 (2008).
     https://doi.org/10.1103/PhysRevC.77.024903
  42. B. Alver et al., arXiv: 0709.4008 [nucl-ex].
  43. B.B. Back et al., Phys. Rev. C 74, 021901 (2006).
     https://doi.org/10.1103/PhysRevC.74.021901
  44. M.C. Abreu et al., Phys. Lett. B 530, 43 (2002).
     https://doi.org/10.1016/S0370-2693(02)01353-9
  45. K. Metaxiotis, Intelligent Information Systems and Knowledge Management for Energy: Applications for Decision Support, Usage, and Environmental Protection (Nat. Techn. Univ. of Athens, Athens, 2010).
     https://doi.org/10.4018/978-1-60566-737-9
  46. M.Y. El-Bakry, A.M. Basha, N. Rashed, A. Radi, and M.A. Mahmoud, 6 th Conference on Nuclear and Particle Physics, Luxor, Egypt, November 17–21, 2007.
  47. S. Haykin, Neural Network: A Comprehensive Foundation (Pearson Education, Upper Saddle River, NJ, 2005).
  48. E. El-Dahshan, A. Radi, M. Y. El-Bakry, and M. ElMashad, 6th Conference on Nuclear Particle Physics, Luxor, Egypt, November 17–21, 2007.
  49. F.M. Dias et al., Eng. App. of Artif. Intell. 19, 1 (2006).
     https://doi.org/10.1016/j.engappai.2005.03.005
  50. M.T. Hagan and M.B. Menhaj, IEEE Trans. on Neural Networks 6, 861 (1994).