Physical properties of long-rising type II supernovae

Context. The supernova (SN) 1987A, with its long-rising (≳40 days) light curve, defines a rare subclass of type II SNe known as 1987A-like events. Representing only ∼1–3% of all core-collapse SNe and often found in low-metallicity environments, their large diversity suggests a wide range of progenitor and explosion properties. Aims. Our aim with this study is to improve the understanding of 1987A-like SNe by characterizing their explosion parameters, including kinetic energy, ejected mass, progenitor radius at the explosion, and synthesized 56Ni mass. Additionally, we seek to identify systematic trends in both the physical properties and the observed spectrophotometric features of these peculiar events. Methods. A new Bayesian parameter estimation method based on our 56Ni-dependent analytical model for hydrogen-rich SNe is applied to derive explosion parameters from the light curves and expansion velocities of one of the largest and most comprehensive 1987A-like SN samples to date. These data are measured through a consistent analysis of observations available in the literature. Results. The analysis reveals a heterogeneous population that nevertheless clusters into two main groups: (i) lower-energy explosions with modest 56Ni yields (∼0.07 M⊙), similar to SN 1987A, and (ii) more energetic events (up to ∼5 foe) with larger nickel production and, in some cases, unusually extended progenitors. We confirm a robust correlation between 56Ni mass, peak luminosity, and explosion energy, as well as between ejecta mass and the recombination timescale. An anticorrelation between Ba II line strength and photospheric velocity indicates that stronger Ba II absorptions in 1987A-like SNe arise from more compact, slowly expanding ejecta. Conclusions. Our findings indicate that 87A-like SNe populate a continuous distribution of explosion energies and progenitor radii. The study underscores the need to extend analytical frameworks to include additional power sources that will enable scalable and accurate modeling of the growing number of peculiar transients that will be discovered by current and upcoming surveys (e.g., ZTF and LSST).