Improving the Čerenkov imaging technique with neural networks

Details Improving the Čerenkov imaging technique with neural networks Improving the Čerenkov imaging technique with neural networks

Jan 1992

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1992phrvd..45..356v&link_type=abstract

Physical Review D (Particles and Fields), Volume 45, Issue 1, 1 January 1992, pp.356-361

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Mathematical Procedures And Computer Techniques

Scientific paper

We have performed a systematic study in space and time of air Čerenkov images of photon and proton showers generated by Bartol-Haleakala simulation programs. The rejection power of the azwidth parameter exploited in the TeV discovery of the Crab Nebula is confirmed. We have used a neural net to search for other features discriminating the Čerenkov images of photons and protons and demonstrate how the efficiency of the imaging method can be improved. We also identified differences in (nanosecond) time-image correlations. We have found that the rejection of proton showers based on timing is not competitive with imaging. Our analysis and the associated programs are sufficiently general and flexible to be used for computer simulation of the threshold and photon recognition capability of any existing, projected, or conceived Čerenkov telescope.

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