Estimation of temporal and spatial distributions of high-energy cosmic-ray electron sources using genetic algorithms

Over the last decade, precise high-energy cosmic-ray electron + positron energy spectra have been obtained with superior instruments such as CALET. Their energy spectra, which exhibit characteristic structures, have the potential to reveal the origin of cosmic-ray electrons. Although supernova remnants (SNRs) are the most likely candidates for high-energy cosmic-ray electrons, the locations of the acceleration sources of observed cosmic-ray electrons, as well as the epoch of their emission from these sources, remain undetermined. In this work, we estimate the temporal and spatial distributions of SNRs in the Galaxy from the observed CALET electron + positron spectrum. We apply genetic algorithms to represent the observed electron + positron spectrum with the calculated flux of high-energy electrons from SNRs distributed in the Galaxy. We identified the clustering features of the estimated SNR distribution as a function of age and distance, not only including the ages and distances of the known nearby SNRs but also extending beyond these known SNRs. Our results are consistent with the SNR origin hypothesis of high-energy cosmic ray electrons, and they also predict that several unknown SNRs are likely to be located in the clustering regions.