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A Universal Neural Network Representation For Hadron–Hadron Interactions At High Energy

Author

Listed:
  • KHALED. A. EL-METWALLY

    (Faculty of Education, P. O. Box. 2908, Postal Code 211, Salalah, Sultanate of Oman)

  • TAREK I. HAWEEL

    (Faculty of Education, P. O. Box. 2908, Postal Code 211, Salalah, Sultanate of Oman)

  • MAHMOUD Y. EL-BAKRY

    (Faculty of Education, P. O. Box. 2908, Postal Code 211, Salalah, Sultanate of Oman)

Abstract

An efficient neural network (NN) has been designed to simulate the hadron–hadron interaction at high energy. Two cases have been considered simultaneously, the proton–proton (p–p) and the pion–proton (π-p) interactions. The neural network has been trained to produce the charged multiplicity distribution for both cases based on samples from the overlapping functions. The trained NN shows a good performance in matching the trained distributions. The NN is then used to predict the distributions that are not present in the training set and matched them effectively. The robustness of the designed NN in the presence of uncertainties, in the overlapping functions has been demonstrated.

Suggested Citation

  • Khaled. A. El-Metwally & Tarek I. Haweel & Mahmoud Y. El-Bakry, 2000. "A Universal Neural Network Representation For Hadron–Hadron Interactions At High Energy," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 11(03), pages 619-628.
    • Handle: RePEc:wsi:ijmpcx:v:11:y:2000:i:03:n:s0129183100000535
    DOI: 10.1142/S0129183100000535
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