A Gravitationally Lensed Supernova with an Observable Two-Decade Time Delay

TL;DR

This paper reports the discovery of a gravitationally lensed supernova with multiple images and a predicted fourth image in 2037, offering a unique opportunity to measure cosmic distances and test dark energy models.

Contribution

It presents the first observation of a multiply-imaged supernova with a long-term predicted reappearance, enabling precise time delay measurements for cosmological studies.

Findings

Three images observed with <200 days delay

Fourth image predicted for 2037±2

Potential 7-day time delay measurement

Abstract

When the light from a distant object passes very near to a foreground galaxy or cluster, gravitational lensing can cause it to appear as multiple images on the sky. If the source is variable, it can be used to constrain the cosmic expansion rate and dark energy models. Achieving these cosmological goals requires many lensed transients with precise time delay measurements. Lensed supernovae (SN) are attractive for this purpose because they have relatively simple photometric behavior, with well-understood light curve shapes and colours $-$ in contrast to the stochastic variation of quasars. Here we report the discovery of a multiply-imaged supernova, AT2016jka ("SN Requiem"). It appeared in an evolved galaxy at $z=1.95$, gravitationally lensed by a foreground galaxy cluster. It is likely a Type Ia supernova $-$ the explosion of a low-mass stellar remnant, whose light curve can be used to measure cosmic distances. In archival Hubble Space Telescope imaging, three lensed images of the supernova are detected with relative time delays of $<$200 days. We predict a fourth image will appear close to the cluster core in the year 2037$\pm$2. Observation of the fourth image could provide a time delay precision of $\approx$7 days, $<1\%$ of the extraordinary 20 year baseline. The SN classification and the predicted reappearance time could be improved with further lens modelling and a comprehensive analysis of systematic uncertainties.