Insights from Modeling Magnetar-driven Light Curves of Stripped-envelope Supernovae

TL;DR

This study models the light curves of 11 stripped-envelope supernovae using magnetar central engines, constraining physical parameters and revealing correlations, thus advancing understanding of their explosion mechanisms.

Contribution

It introduces a semi-analytical magnetar-based light curve modeling approach for SESNe and analyzes parameter correlations, providing new insights into their physical properties.

Findings

Magnetar model successfully reproduces all SESNe light curves.

Identifies correlations between physical parameters such as spin period and magnetic field.

Suggests a possible jet-driven explosion mechanism for most SESNe.

Abstract

This work presents the semi-analytical light curve modelling results of 11 stripped-envelope SNe (SESNe), where millisecond magnetars potentially drive their light curves. The light-curve modelling is performed utilizing the $\chi^2$-minimisation code $\texttt{MINIM}$ considering millisecond magnetar as a central engine powering source. The magnetar model well regenerates the bolometric light curves of all the SESNe in the sample and constrains numerous physical parameters, including magnetar's initial spin period ($P_\textrm{i}$) and magnetic field ($B$), explosion energy of supernova ($E_\textrm{exp}$), progenitor radius ($R_\textrm{p}$), etc. Within the sample, the superluminous SNe 2010kd and 2020ank exhibit the lowest $B$ and $P_\textrm{i}$ values, while the relativistic Ic broad-line SN 2012ap shows the highest values for both parameters. The explosion energy for all SESNe in the sample (except SN 2019cad), exceeding $\gtrsim$2 $\times$ 10$^{51}$ erg, indicates there is a possibility of a jittering jet explosion mechanism driving these events. Additionally, a correlation analysis identifies linear dependencies among parameters derived from light curve analysis, revealing positive correlations between rise and decay times, $P_\textrm{i}$ and $B$, $P_\textrm{i}$ and $R_\textrm{p}$, and $E_\textrm{exp}$ and $R_\textrm{p}$, as well as strong anti-correlations of $P_\textrm{i}$ and $B$ with the peak luminosity. Principal Component Analysis is also applied to key parameters to reduce dimensionality, allowing a clearer visualization of SESNe distribution in a lower-dimensional space. This approach highlights the diversity in SESNe characteristics, underscoring unique physical properties and behaviour across different events in the sample. This study motivates further study on a more extended sample of SESNe to look for millisecond magnetars as their powering source.