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We present a photometric and spectroscopic analysis of the ultraluminous and slowly evolving 03fg-like Type Ia SN 2021zny. Our observational campaign starts from ∼5.3 h after explosion (making SN 2021zny one of the earliest observed members of its class), with dense multiwavelength coverage from a variety of ground- and space-based telescopes, and is concluded with a nebular spectrum ∼10 months after peak brightness. SN 2021zny displayed several characteristics of its class, such as the peak brightness (MB = −19.95 mag), the slow decline (Δm15(B) = 0.62 mag), the blue early-time colours, the low ejecta velocities, and the presence of significant unburned material above the photosphere. However, a flux excess for the first ∼1.5 d after explosion is observed in four photometric bands, making SN 2021zny the third 03fg-like event with this distinct behaviour, while its +313 d spectrum shows prominent [O i] lines, a very unusual characteristic of thermonuclear SNe. The early flux excess can be explained as the outcome of the interaction of the ejecta with $\sim 0.04\, \mathrm{M_{\odot }}$ of H/He-poor circumstellar material at a distance of ∼1012 cm, while the low ionization state of the late-time spectrum reveals low abundances of stable iron-peak elements. All our observations are in accordance with a progenitor system ofmore »two carbon/oxygen white dwarfs that undergo a merger event, with the disrupted white dwarf ejecting carbon-rich circumstellar material prior to the primary white dwarf detonation.

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We present a comprehensive optical and near-infrared census of the fields of 90 short gamma-ray bursts (GRBs) discovered in 2005–2021, constituting all short GRBs for which host galaxy associations are feasible (≈60% of the total Swift short GRB population). We contribute 274 new multi-band imaging observations across 58 distinct GRBs and 26 spectra of their host galaxies. Supplemented by literature and archival survey data, the catalog contains 542 photometric and 42 spectroscopic data sets. The photometric catalog reaches 3σdepths of ≳24–27 mag and ≳23–26 mag for the optical and near-infrared bands, respectively. We identify host galaxies for 84 bursts, in which the most robust associations make up 56% (50/90) of events, while only a small fraction, 6.7%, have inconclusive host associations. Based on new spectroscopy, we determine 18 host spectroscopic redshifts with a range ofz≈ 0.15–1.5 and find that ≈23%–41% of Swift short GRBs originate fromz> 1. We also present the galactocentric offset catalog for 84 short GRBs. Taking into account the large range of individual measurement uncertainties, we find a median of projected offset of ≈7.7 kpc, for which the bursts with the most robust associations have a smaller median of ≈4.8 kpc. Our catalog captures more high-redshiftmore »and low-luminosity hosts, and more highly offset bursts than previously found, thereby diversifying the population of known short GRB hosts and properties. In terms of locations and host luminosities, the populations of short GRBs with and without detectable extended emission are statistically indistinguishable. This suggests that they arise from the same progenitors, or from multiple progenitors, which form and evolve in similar environments. All of the data products are available on the Broadband Repository for Investigating Gamma-Ray Burst Host Traits website.

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Supernova (SN) siblings – two or more SNe in the same parent galaxy – are useful tools for exploring progenitor stellar populations as well as properties of the host galaxies such as distance, star-formation rate, dust extinction, and metallicity. Since the average SN rate for a Milky Way-type galaxy is just one per century, a large imaging survey is required to discover an appreciable sample of SN siblings. From the wide-field Zwicky Transient Facility (ZTF) Bright Transient Survey (which aims for spectroscopic completeness for all transients which peak brighter than r < 18.5 mag) we present 10 SN siblings in five parent galaxies. For each of these families, we analyse the SN’s location within the host and its underlying stellar population, finding agreement with expectations that SNe from more massive progenitors are found nearer to their host core and in regions of more active star formation. We also present an analysis of the relative rates of core collapse and thermonuclear SN siblings, finding a significantly lower ratio than past SN sibling samples due to the unbiased nature of the ZTF.

We present SNIascore, a deep-learning based method for spectroscopic classification of thermonuclear supernovae (SNe Ia) based on very low-resolution (R ∼100) data. The goal of SNIascore is fully automated classification of SNe Ia with a very low false-positive rate (FPR) so that human intervention can be greatly reduced in large-scale SN classification efforts, such as that undertaken by the public Zwicky Transient Facility (ZTF) Bright Transient Survey (BTS). We utilize a recurrent neural network (RNN) architecture with a combination of bidirectional long short-term memory and gated recurrent unit layers. SNIascore achieves a <0.6% FPR while classifying up to 90% of the low-resolution SN Ia spectra obtained by the BTS. SNIascore simultaneously performs binary classification and predicts the redshifts of secure SNe Ia via regression (with a typical uncertainty of <0.005 in the range from z=0.01 to z=0.12). For the magnitude-limited ZTF BTS survey (≈70% SNe Ia), deploying SNIascore reduces the amount of spectra in need of human classification or confirmation by ≈60%. Furthermore, SNIascore allows SN Ia classifications to be automatically announced in real-time to the public immediately following a finished observation during the night.