Neural networks technique based signal-from-background separation and design optimization for a W/quartz fiber calorimeter

Details Neural networks technique based signal-from-background separation and design optimization for a W/quartz fiber calorimeter Neural networks technique based signal-from-background separation and design optimization for a W/quartz fiber calorimeter

2003-03-14

arxiv.org/abs/hep-ex/0303021v2

Physics

High Energy Physics

High Energy Physics - Experiment

LaTeX 22 pages, 4 tables, 15 figures

Scientific paper

We present a signal-from-background separation study based on neural networks technique applied to a W/quartz fiber calorimeter. Performance results in terms of signal efficiency and improvement of the signal-to-background ratio are presented. We conclude that by using neural networks we can efficiently separate signal from background and achieve a signal enhancement over the background of the order of several thousands at high efficiency.

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