Using a neural network approach for muon reconstruction and triggering

E. Etzion*, H. Abramowicz, Y. Benhammou, G. Dror, D. Horn, L. Levinson, R. Livneh

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review


The extremely high rate of events that will be produced in the future Large Hadron Collider requires the triggering mechanism to take precise decisions in a few nano-seconds. We present a study which used an artificial neural network triggering algorithm and compared it to the performance of a dedicated electronic muon triggering system. Relatively simple architecture was used to solve a complicated inverse problem. A comparison with a realistic example of the ATLAS first level trigger simulation was in favour of the neural network. A similar architecture trained after the simulation of the electronics first trigger stage showed a further background rejection.

Original languageEnglish
Pages (from-to)222-227
Number of pages6
JournalNuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment
Issue number1-2
StatePublished - 21 Nov 2004
EventProceedings of the IXth International Workshop - Tsukuba, Japan
Duration: 1 Dec 20035 Dec 2003


  • HEP
  • Neural network
  • Trigger


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