3–7 Oct 2022
Gran Sasso Science Institute, L'Aquila, Italy
Europe/Rome timezone

A machine learning approach for mass composition analysis with TALE-SD data

3 Oct 2022, 17:00
20m
Gran Sasso Science Institute, L'Aquila, Italy

Gran Sasso Science Institute, L'Aquila, Italy

Via Michele Iacobucci, 2 L'Aquila, Italy
Talk

Speaker

Ryuhei Arimura (Osaka Metropolitan University and Telescope Array Group)

Description

The TALE experiment is a TA low-energy extension to observe cosmic rays with energies down to 1016.5 to clarify the origin of the second knee and the energy of a galatic-to-extragalactic transition. TALE consists of 10 high-elevation fluorescence detectors and 80 scintillation counters in an area of 21km . The key of data interpretation is the mass composition of cosmic rays, and we will report on a machine learning approach of mass composition analysis that usilizes waveform data of TALE scintillation counters.

Primary author

Ryuhei Arimura (Osaka Metropolitan University and Telescope Array Group)

Co-authors

Presentation materials