Separating True V0's from Combinatoric Background with a Neural Network

Abstract

A feedforward multilayered neural network has been trained to "recognize" true V0's in the presence of a large combinatoric background using simulated data for 2 GeV/nucleon Ni + Cu interactions. The resulting neural network filter has been applied to actual data from the EOS TPC experiment. An enhancement of signal to background over more traditional selection mechanisms has been observed.

9 pages LaTeX using elsart.sty and psfig, 5 ps figures. Submitted to NIM

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