Unveiling the spectral morphological division of fast radio bursts with CHIME/FRB Catalog 2
Using unsupervised machine learning on the CHIME/FRB Catalog 2, this study reveals that fast radio bursts naturally divide into two spectral morphology-based clusters, suggesting that the observed differences between repeating and nonrepeating sources arise from selection effects rather than distinct physical populations.