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Il Nuovo Cimento A (1965-1970)

, Volume 107, Issue 1, pp 129–141 | Cite as

Neural networks for Higgs search

  • F. Anselmo
  • F. Block
  • G. Brugnola
  • L. Cifarelli
  • D. Hatzifotiadou
  • G. La Commare
  • M. Marino
Article

Summary

We describe an approach to the heavy-Higgs (mH=750 GeV) search by means of a neural network (NN) in pp collisions at \( \sqrt s = 16 \), TeV (LHC), 40 TeV (SSC) and 200 TeV (ELN/Eloisatron). The mechanisms we considered for Higgs production are gluon fusion and vector boson fusion, letting the H0 decay through the channel H0→Z0Z0→μ+μ-μ+μ-. The overall background to the Higgs signal was assumed to consist of the QCD continuum production of Z0 pairs, where each Z0 was forced to decay into muons. Using Monte Carlo simulated events at each energy, we trained a neural network to distinguish signal from background and evaluated its performances as an event classifier. The results are promising and indicate that neural networks could be efficiently used for event selection in future experiments at super-high energy.

PACS 14.80.Gt

Higgs bosons and related particles 

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Copyright information

© Società Italiana di Fisica 1994

Authors and Affiliations

  • F. Anselmo
    • 1
  • F. Block
    • 1
    • 2
    • 5
  • G. Brugnola
    • 1
    • 3
  • L. Cifarelli
    • 1
    • 2
    • 4
  • D. Hatzifotiadou
    • 1
    • 6
  • G. La Commare
    • 1
  • M. Marino
    • 1
    • 6
  1. 1.LAA ProjectCERNGenevaSwitzerland
  2. 2.INFNSezione di BolognaBolognaItaly
  3. 3.Eloisatron ProjectINFNEriceItaly
  4. 4.Physics DepartmentUniversity of PisaPisaItaly
  5. 5.Physics DepartmentUniversity of WuppertalWuppertalGermany
  6. 6.World LaboratoryLausanneSwitzerland

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