Kilonova ejecta morphology is distinguishable only when late-time JWST mid-infrared data are added to Rubin optical data, and AT2017gfo is best matched by the SuperNu TP2 (toroidal plus peanut wind) model.
An Online Framework for Fitting Fast Transient Lightcurves
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abstract
The identification of extragalactic fast optical transients (eFOTs) as potential multi-messenger sources is one of the main challenges in time-domain astronomy. However, recent developments have allowed for probes of rapidly-evolving transients. With the increasing number of alert streams from optical time-domain surveys, the next paradigm is building technologies to rapidly identify the most interesting transients for follow-up. One effort to make this possible is the fitting of objects to a variety of eFOT lightcurve models such as kilonovae and $\gamma$-ray burst (GRB) afterglows. In this work, we describe a new framework designed to efficiently fit transients to light curve models and flag them for further follow-up. We describe the pipeline's workflow and a handful of performance metrics, including the nominal sampling time for each model. We highlight as examples ZTF20abwysqy, the shortest long gamma ray burst discovered to date, and ZTF21abotose, a core-collapse supernova initially identified as a potential kilonova candidate.
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Inferring neutron star merger ejecta morphologies with kilonovae
Kilonova ejecta morphology is distinguishable only when late-time JWST mid-infrared data are added to Rubin optical data, and AT2017gfo is best matched by the SuperNu TP2 (toroidal plus peanut wind) model.