Magnetar Models of Superluminous Supernovae from the Dark Energy Survey: Exploring Redshift Evolution

TL;DR

This study models 21 high-redshift superluminous supernovae from the Dark Energy Survey using magnetar engines, finding no evidence of evolution in their physical properties across cosmic time.

Contribution

It provides the first comprehensive analysis of high-redshift SLSNe with magnetar models, extending previous low-redshift studies and testing for redshift evolution.

Findings

DES SLSNe have similar engine parameters to lower-redshift samples.

A negative correlation between ejecta mass and spin period is confirmed.

No evidence of evolution in key physical parameters with redshift.

Abstract

Superluminous supernovae (SLSNe) are luminous transients that can be detected to high redshifts with upcoming optical time-domain surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). An interesting open question is whether the properties of SLSNe evolve through cosmic time. To address this question, in this paper we model the multi-color light curves of all 21 Type I SLSNe from the Dark Energy Survey (DES) with a magnetar spin-down engine, implemented in the Modular Open Source Fitter for Transients (MOSFiT). With redshifts up to $z\approx 2$, this sample includes some of the highest-redshift SLSNe. We find that the DES SLSNe span a similar range of ejecta and magnetar engine parameters to previous samples of mostly lower-redshift SLSNe (spin period $P\approx 0.79-13.61$ ms, magnetic field $B\approx (0.03-7.33)\times10^{14}$ G, ejecta mass $M_{\rm ej}\approx 1.54-30.32$ M$_{\odot}$, and ejecta velocity $v_{\rm ej}\approx (0.55-1.45)\times 10^4$ km s$^{-1}$). The DES SLSN sample by itself exhibits the previously found negative correlation between $M_{\rm ej}$ and $P$, with a pronounced absence of SLSNe with low ejecta mass and rapid spin. Combining our results for the DES SLSNe with 60 previous SLSNe modeled in the same way, we find no evidence for redshift evolution in any of the key physical parameters.