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An Online Framework for Fitting Fast Transient Lightcurves

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arxiv 2404.17515 v1 pith:FHHZVFIF submitted 2024-04-26 astro-ph.HE astro-ph.CO

classification astro-ph.HEastro-ph.CO
keywords transientsburstdescribefastfittingfollow-upframeworkgamma
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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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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Binary neutron stars in the next-generation era: Multi-messenger detection prospects and constraints on the equation of state, mass distribution, and cosmology

    astro-ph.HE 2026-07 conditional novelty 6.0 of 10

    With ET (and ET+CE), mock multi-messenger BNS catalogues yield ~40–500 EM counterparts per year and, under ideal recovery, constrain R1.4 to ~0.2 km and H0 to ~1 km s−1 Mpc−1.

  2. Inferring neutron star merger ejecta morphologies with kilonovae

    astro-ph.HE 2025-05 conditional novelty 6.0 of 10

    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.

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