The Quadruply Lensed Supernova SN 2025wny: Implications for LSST

TL;DR

This paper proposes a protocol for rapid follow-up and modeling of quadruply lensed supernovae detected by LSST, emphasizing immediate observations and on-the-fly analysis to maximize scientific returns.

Contribution

It introduces a detailed protocol and software tools for exploiting quadruply lensed supernova alerts, including pre-coverage and real-time modeling strategies.

Findings

Preliminary data for SN 2025wny demonstrate the protocol's potential.

Software based on Witt-Wynne lens model supports on-the-fly analysis.

Identifies challenges and potential improvements in rapid follow-up.

Abstract

Lensed supernovae (SNae) are among the most eagerly anticipated transients expected from the Legacy Survey of Space and Time (LSST). Quadruply lensed SNae permit more highly constrained models than "mere" doubles. The quadruply lensed SN 2025wny offers multiple lessons on how one might respond to an alert. The full benefits of such rare events are best achieved with immediate spectroscopic and photometric followup, within hours rather than days. This in turn requires on-the-fly modeling to predict the position(s) and magnitudes of trailing images and to "pre-cover" any leading images that might have been too faint to trigger an alert and that cannot be detected in the triggering exposure. This paper sets out a proposed protocol for exploiting similar alerts. A list of quadruply lensed candidate hosts must first be supplied in advance to one or more brokers, along with on-the-fly software (an example of which is given) to determine whether an SN near an incipient host is strongly lensed, and whether quadruply or doubly. The brokers would then broadcast the positions and time delays (or "pre-lays") that permit "pre-covery'' of leading images, "re-covery'' of trailing images, and possibly, extraction of a rough lightcurve from prior LSST exposures. The scheme is illustrated (and some potential problems identified) using preliminary data for SN 2025wny presented by three independent teams. It employs software based on the geometric Witt-Wynne lens model and Falor's exact, forward, differentiable solution thereof.