Using a neural network approach for muon reconstruction and triggering

E. Etzion; H. Abramowicz; Y. Benhammou; D. Horn; L. Levinson; R. Livneh

doi:10.1016/j.nima.2004.07.091

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Using a neural network approach for muon reconstruction and triggering

E. Etzion·H. Abramowicz·Y. Benhammou·D. Horn·L. Levinson·R. Livneh

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Abstract

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.

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BibTeX RIS

E. Etzion, H. Abramowicz, Y. Benhammou, D. Horn, L. Levinson, R. Livneh. 2004-02-16. Using a neural network approach for muon reconstruction and triggering. https://doi.org/10.1016/j.nima.2004.07.091

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