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Abstract:
In High Energy Physics experiments one has to sort through a
high flux of events, at a rate of tens of MHz, and select the few
that are of interest. In making this decision one relies on the
location of the vertex where the interaction, that led to the
event, took place. Here we present a solution to this problem,
based on two feedforward neural networks with fixed architectures,
whose parameters are chosen so as to obtain a high accuracy. The
system is tested on many data sets, and is shown to perform better
than commonly used algorithms.
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