A Systematic Study of Superluminous Supernova Light-curve Models Using Clustering

Abstract

Abstract Superluminous supernova (SLSN) light curves exhibit superior diversity compared to their regular-luminosity counterparts in terms of rise and decline timescales, peak luminosities, and overall shapes. It remains unclear whether this striking variety arises due to a dominant power input mechanism involving many underlying parameters or due to contributions by different progenitor channels. In this work, we propose that a systematic quantitative study of SLSN light-curve timescales and shape properties, such as symmetry around peak luminosity, can be used to characterize these enthralling stellar explosions. We find that applying clustering analysis to the properties of model SLSN light curves, powered by either a magnetar spindown or a supernova ejecta–circumstellar matter interaction mechanism, can yield a distinction between the two, especially in terms of light-curve symmetry. We show that most events in the observed SLSN sample with well-constrained light curves and early detections are strongly associated with clusters dominated by circumstellar interaction models. Magnetar spindown models also show association at a lower degree but have difficulty in reproducing fast evolving and fully symmetric light curves. We believe this is due to the truncated nature of the circumstellar interaction shock energy input compared to decreasing but continuous power input sources like magnetar spindown and radioactive 56Ni decay. Our study demonstrates the importance of clustering analysis in characterizing SLSNe based on high-cadence photometric observations that will be made available in the near future by surveys like the Large Synoptic Survey Telescope, Zwicky Transient Facility, and Panoramic Survey Telescope and Rapid Response System.