Spectral statistics applied to TeV cosmic gamma/proton discrimination

Spectral statistics techniques based on random matrix theory are applied to study the correlations at ground level among secondary particle density distributions of simulated extensive air showers. High-energy interactions of TeV cosmic γ-rays and protons with Earth atmosphere and the resulting extensive air showers have been simulated by means of the CORSIKA Monte Carlo code. The statistical description of shower fronts provided by this new type of analysis allows to distinguish events generated by primary protons from those initiated by primary γ-rays, and leads to a powerful discrimination method whose efficiency is evaluated using the standard quality factors.