Development of a pattern recognition algorithm for particle identification on the SciCRT in the Sierra Negra Volcano Summit
R. García Gínez, J.F. Valdés-Galicia, M.A. Anzorena Méndez, E. Ortiz, L.X. Gónzalez, O. Musalem, A. Hurtado, M. Barrantes, R. Taylor, Y. Matsubara, Y. Sasai, Y. Itow, T. Sako, T. Kawabata, A. Tsuchiya, K. Munakata, C. Kato, Y. Nakamura, T. Oshima, T. Koike, S. Shibata, A. Oshima, H. Takamaru, H. Kojima, H. Tsuchiya, K. Watanabe, M. Kozai, T. Koi
At the top of the Sierra Negra volcano in eastern México($19.0^\circ$N,$97.3^\circ$W) the SciBar Cosmic Ray Telescope (SciCRT) is installed, one of its main purposes is to detect solar neutrons to investigate the ion acceleration process during intense solar flares. Furthermore, thanks to the design and construction of the SciCRT in the form of small and long scintillation bars, large active volume, high energy resolution, and a fast electronics for data processing, particle identification is possible through the analysis of tracks. Considering these properties, species identification of secondary cosmic ray inside the Earth's atmosphere, at a depth about $600g/cm^2$ is possible.
In this work, we present an ad-hoc algorithm constructed to distinguish between particle species that cross the active volume of the detector. The aim is to use pattern recognition methods and event reconstruction to achieve this goal.