Inverting Cosmic Ray Propagation by Convolutional Neural Networks
Speaker: Dr. CAI Yuelin
Affiliation: THU
Title: "Inverting cosmic ray propagation by Convolutional Neural Networks"
Date: 16th September (Wednesday) 2020
Time: 10:30 a.m
Tencent meeting：5032471346
Abstract: We propose a machine learning method to investigate the propagation of cosmic rays, based on the precisely measured spectra of primary and secondary nuclei Li, Be, B, C, and O by AMS-02, ACE, and Voyager-1. We train two Convolutional Neural Network machines: one learns how to invert the spectra of cosmic rays to the propagation and source parameters, and the other one is similar to the former but with an additional denoising. Together with the mock data generating by GALPROP, we found that both machines can properly invert the propagation process and infer the propagation and source parameters reasonably well. This approach can be much more efficient than the traditional Markov Chain Monte Carlo fitting method in deriving the propagation parameters.
