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.
@article{arxiv.physics/0402070,
title = {Using a neural network approach for muon reconstruction and triggering},
author = {E. Etzion and H. Abramowicz and Y. Benhammou and D. Horn and L. Levinson and R. Livneh},
journal= {arXiv preprint arXiv:physics/0402070},
year = {2009}
}
Comments
A talk given at ACAT03, KEK, Japan, November 2003. Submitted to Nuclear Instruments and Methods in Physics Research, Section A