Magnetars As Powering Sources of Gamma-Ray Burst Associated Supernovae, and Unsupervized Clustering of Cosmic Explosions

We present the semi-analytical light curve modelling of 13 supernovae associated with gamma-ray bursts (GRB-SNe) along with two relativistic broad-lined (Ic-BL) SNe without GRB association (SNe 2009bb and 2012ap), considering millisecond magnetars as central-engine-based power sources for these events. The bolometric light curves of all 15 SNe in our sample are well-regenerated utilizing a chi(2)-minimization code, MINIM, and numerous parameters are constrained. The median values of ejecta mass (M-ej), magnetar's initial spin period (P-i), and magnetic field (B) for GRB-SNe are determined to be approximate to 5.2 M-circle dot, 20.5 ms, and 20.1 x 10(14) G, respectively. We leverage machine learning (ML) algorithms to comprehensively compare the three-dimensional parameter space encompassing M-ej, P-i, and B for GRB-SNe determined herein to those of H-deficient superluminous SNe (SLSNe-I), fast blue optical transients (FBOTs), long GRBs (LGRBs), and short GRBs (SGRBs) obtained from the literature. The application of unsupervized ML clustering algorithms on the parameters M-ej, P-i, and B for GRB-SNe, SLSNe-I, and FBOTs yields a classification accuracy of similar to 95 per cent. Extending these methods to classify GRB-SNe, SLSNe-I, LGRBs, and SGRBs based on P-i and B values results in an accuracy of similar to 84 per cent. Our investigations show that GRB-SNe and relativistic Ic-BL SNe presented in this study occupy different parameter spaces for M-ej, P-i, and B than those of SLSNe-I, FBOTs, LGRBs, and SGRBs. This indicates that magnetars with different P-i and B can give birth to distinct types of transients.