**7. Discussion**

Studies of GRB pulses at early times have revealed that the dominant radiation process is usually photospheric emission [136–141]. These thermal pulses exhibit significant spectral evolution, with bursts usually evolving to be dominated by synchrotron emission [137,139,142]. If this is the case, the first second of all GRBs should be dominated by thermal pulses; therefore, the radiation process is unlikely to be the driver of the observed differences in light curves that appear at early times.

The feature extraction algorithm may identify differences in the spectral evolution and pulse shapes of the two burst groups. The spectral lags of long and short bursts are different, with many short bursts exhibiting zero lag [18,63]. The minimum variability timescales for short and long bursts have also been found to be different [44–46]. For example Golkhou et al. [46] found median minimum variability timescales of 10 ms and 45 ms for short and long bursts, respectively. Hakkila and Preece [64] found that pulses in short GRBs are shorter and harder than those in long GRBs, and exhibit more rapid spectral evolution. Coupled with the observation that shorter pulses have a higher peak flux and ∼90% of short GRBs consist of a single pulse, compared to 25–40% for long GRBs, pulse properties are likely to be a distinguishing feature in the first pulses and first seconds of a burst. Short GRBs have shorter pulse durations and their triple peaked substructure shows more intense precursor and decay peaks (on either side of the central peak) than long GRBs Hakkila et al. [56].

The magnitude of the PCA components in the different *Swift*/BAT energy bands indicate that Bands 2 and 3 contain the most variance; therefore, they are the most important for the 4 ms light curves. Figure 10 shows that the results of the feature extraction algorithm only applied to Band 3 data, showing that some segregation of the bursts into two groups is evident using light curves in one energy band. Thus, energy-dependent pulse characteristics are not the sole driver of the classification.

**Figure 10.** 2D t-SNE representation of the wavelet coefficients and PCA features extracted from the light curves measured in Band 3 for *Swift*/BAT (50–100 keV). The plot is coloured by burst duration T90.
