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The CHIME/FRB collaboration has recently published a catalog containing abouthalf a thousand fast radio bursts (FRBs) including their spectra and severalreconstructed properties, like signal widths, amplitudes, etc. We havedeveloped a model-independent approach for a classification of these burstsusing cross-correlation and clustering algorithms applied to one-dimensionalintensity profiles of the bursts (i.e., to amplitudes as a function of timeaveraged over the frequency). Using this algorithm we identified two majorclasses of FRBs featuring different waveform morphology, and, simultaneously,different distribution of brightness temperature. Bursts from one of theidentified cluster have lower brightness temperatures and larger widths thanevents from the other cluster. Both groups include bursts from the repeatersand one-off events.

Model-independent classification of events from the first CHIME/FRB Fast Radio Burst catalog