Measurements of Cosmic Proton Flux through Neutron Monitors Using Deep Networks and Imputation Techniques in the AMS-02 Era

Abstract

Accurate measurements of cosmic proton flux are essential for studying the modulation processes of cosmic rays during the solar activity cycle. A proton flux measurement method, based on ground-based neutron monitor (NM) data and deep learning techniques, is presented. After the necessary pre-processing of ground-based NM data using a convolutional neural network (CNN) model, we model the relationship between NM observations and proton flux measured by the Alpha Magnetic Spectrometer (AMS). The daily cosmic proton flux, ranging from 1 GV to 100 GV, is obtained for the period from 2011 to 2024, showing strong agreement with the observed values. In addition, daily proton flux is computed for periods when AMS measurements were unavailable due to operational reasons. For the first time, hourly proton flux as a function of rigidity are calculated for the study of the short-time solar activities.

15 pages, 8 figures

References in corpus (3)

• SAITS: Self-Attention-based Imputation for Time Series
• Time dependence of the electron and positron components of the cosmic radiation measured by the PAMELA experiment between July 2006 and December 2015
• Observations of Forbush Decreases of cosmic ray electrons and positrons with the Dark Matter Particle Explorer