SN2017jgh - A high-cadence complete shock cooling lightcurve of a SN IIb with the Kepler telescope

TL;DR

This paper presents high-cadence observations of SN 2017jgh, a Type IIb supernova, capturing shock cooling with Kepler/K2, and uses these data to infer properties of its progenitor star, highlighting the importance of early observations.

Contribution

It provides the first detailed shock cooling lightcurve of SN 2017jgh with Kepler/K2, enabling refined estimates of the progenitor's radius, mass, and shock velocity, and discusses systematic uncertainties in such modeling.

Findings

Progenitor was likely a yellow supergiant with radius 50-290 R_sun.

Shock velocity estimated between 7500-10300 km/s.

Early observations are crucial for constraining progenitor properties.

Abstract

SN 2017jgh is a type IIb supernova discovered by Pan-STARRS during the C16/C17 campaigns of the Kepler/K2 mission. Here we present the Kepler/K2 and ground based observations of SN 2017jgh, which captured the shock cooling of the progenitor shock breakout with an unprecedented cadence. This event presents a unique opportunity to investigate the progenitors of stripped envelope supernovae. By fitting analytical models to the SN 2017jgh lightcurve, we find that the progenitor of SN 2017jgh was likely a yellow supergiant with an envelope radius of $\sim50-290~R_{\odot}$, and an envelope mass of $\sim0-1.7~M_{\odot}$. SN 2017jgh likely had a shock velocity of $\sim7500-10300$ km s$^{-1}$. Additionally, we use the lightcurve of SN 2017jgh to investigate how early observations of the rise contribute to constraints on progenitor models. Fitting just the ground based observations, we find an envelope radius of $\sim50-330~R_{\odot}$, an envelope mass of $\sim0.3-1.7~M_{\odot}$ and a shock velocity of $\sim9,000-15,000$ km s$^{-1}$. Without the rise, the explosion time can not be well constrained which leads to a systematic offset in the velocity parameter and larger uncertainties in the mass and radius. Therefore, it is likely that progenitor property estimates through these models may have larger systematic uncertainties than previously calculated.