Neural nets for ground-based /γ-ray astronomy

Details Neural nets for ground-based /γ-ray astronomy Neural nets for ground-based /γ-ray astronomy

Apr 2003

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2003nimpa.502..789m&link_type=abstract

Nuclear Instruments and Methods in Physics Research Section A, Volume 502, Issue 2-3, p. 789-791.

Physics

Scientific paper

The application of the artificial neural networks to data processing in the domain of the atmospheric Cherenkov /γ-ray telescopes is considered. The main problems arising from the specifics of these experiments, such as low signal, pairs of ON-OFF observations, instability of the background events, and their influence on the analysis are discussed. A method for discriminating the /γ-induced atmospheric showers from the large hadronic background is proposed.

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