A wavelet-based multifractal separation technique for extensive air showers

Separating extensive air showers (EAS) initiated by gamma-rays and different cosmic rays is not only important in establishing gamma-ray astronomy at ultra-high energies on firmer grounds, but it is also of utmost importance in determining the elemental mass composition of cosmic rays at these energies. In this work, based on a thorough analysis of multifractal behaviour of secondary particle distributions of Monte Carlo simulated EASs using wavelet transforms, we have introduced a separation technique. The general characteristics of the multifractal behaviour of these distributions, and the separation technique based on these general characteristics, are discussed and the results of applying the separation technique to simulated showers are presented. (author)