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Abstract:

We present multiband ATLAS and ZTF photometry for SN 2019tsf, a Type Ib stripped-envelope supernova (SESN). The slow spectral evolution could be associated with an uncommon explosion mechanism specific to this SN. Possible explanations include fallback accretion onto a compact remnant or a long-lived central engine, both of which could provide extended energy injection responsible for the late-time rebrightening and unusual spectral features. The rebrightening observations represent the latest photometric measurements of a multipeaked Type Ib SN. As late-time photometry and spectroscopy suggest no hydrogen, the potential circumstellar material (CSM) must be H-poor. The absence of a nebular phase and the lack of narrow emission lines in the late-time spectra (>142 days) of the SNe suggest that any CSM interaction is likely asymmetric and enveloped by the SN ejecta. However, an extended CSM structure is evident through a follow-up radio campaign with the Karl G. Jansky Very Large Array (VLA), indicating a source of bright optically thick radio emission at late times, which is highly unusual among H-poor SESNe. We attribute this phenomenology to an interaction of the supernova ejecta with asymmetric CSM, potentially disk-like, and we present several models that may explain the origin of this rare Type Ib supernova. We propose a warped disk model in which a tertiary companion—commonly present around massive stars—perturbs the progenitor’s CSM, producing density enhancements that may explain the observed multipeaked SN 2019tsf light curve. This SN 2019tsf is a unique SN Type Ib among the recently discovered class of SNe that undergo mass transfer at the moment of explosion.

Abstract:

We present the Virtual Research Assistant (VRA) of the ATLAS sky survey, which performs preliminary eyeballing on our clean transient data stream. The VRA uses histogram-based gradient-boosted decision tree classifiers trained on real data to score incoming alerts on two axes: “Real” and “Galactic.” The alerts are then ranked using a geometric distance such that the most “real” and “extragalactic” receive high scores; the scores are updated when new lightcurve data is obtained on subsequent visits. To assess the quality of the training we use the recall at rank K, which is more informative to our science goal than general metrics (e.g., accuracy, F1-scores). We also establish benchmarks for our metric based on the pre-VRA eyeballing strategy, to ensure our models provide notable improvements before being added to the ATLAS pipeline. Then, policies are defined on the ranked list to select the most promising alerts for humans to eyeball and to automatically remove bogus alerts. In production the VRA method has resulted in a reduction in eyeballing workload by 85% with a loss of follow-up opportunity <0.08%. It also allows us to automatically trigger follow-up observations with the Lesedi telescope, paving the way toward automated methods that will be required in the era of LSST. Finally, this is a demonstration that feature-based methods remain extremely relevant in our field, being trainable on only a few thousand samples and highly interpretable; they also offer a direct way to inject expertise into models through feature engineering.

Abstract:

We discuss the results of the spectroscopic and photometric monitoring of the type IIn supernova (SN) 2023ldh. Survey archive data show that the SN progenitor experienced erratic variability in the years before exploding. Beginning May 2023, the source showed a general slow luminosity rise that lasted for over four months, with some superposed luminosity fluctuations. In analogy to SN 2009ip , we call this brightening ‘Event A’. During Event A, SN 2023ldh reached a maximum absolute magnitude of M r = −15.52 ± 0.24 mag. The light curves then decreased by about 1 mag in all filters for about two weeks reaching a relative minimum, which was followed by a steep brightening (Event B) to an absolute peak magnitude of M r = −18.53 ± 0.23 mag, replicating the evolution of SN 2009ip and similar to that of type IIn SNe. The three spectra of SN 2023ldh obtained during Event A show multi-component P Cygni profiles of H I and Fe II lines. During the rise to the Event B peak, the spectrum shows a blue continuum dominated by Balmer lines in emission with Lorentzian profiles, with a full width at half maximum velocity of about 650 km s −1 . Later, in the post-peak phase, the spectrum reddens, and broader wings appear in the H α line profile. Metal lines with P Cygni profiles and velocities of about 2000 km s −1 are clearly visible. Beginning around three months past maximum and until very late phases, the Ca II lines become among the most prominent features, while H α is dominated by an intermediate-width component with a boxy profile. Although SN 2023ldh mimics the evolution of other SN 2009ip -like transients, it is slightly more luminous and has a slower photometric evolution. The surprisingly homogeneous observational properties of SN 2009ip -like events may indicate similar explosion scenarios and similar progenitor parameters.

Abstract:

Context. Type IIb supernovae (SNe IIb) often exhibit an early light curve excess (EE) preceding the main peak powered by 56 Ni decay. The physical origin of this early emission remains an open question. Among the proposed scenarios, shock cooling (SC) emission, resulting from the interaction of the shock wave with extended envelopes, is considered the most plausible mechanism. However, the occurrence rate of such events has yet to be reliably constrained. Aims. This study aims to quantify the frequency of EE in SNe IIb and investigate its physical origin by analysing optical light curves from the Asteroid Terrestrial-impact Last Alert System (ATLAS) survey, ultimately providing qualitative constraints on their progenitor systems. Methods. We identified 74 potential SNe IIb from 153 spectroscopically classified events reported in the Transient Name Server (TNS), observed by ATLAS with peak fluxes exceeding 150 μJy (18.46 mag) and explosion epoch uncertainties below six days. Using a spectral reclassification method, we selected a sample of 66 SNe IIb and a cleaned sample of 59 SNe IIb for analysis. We then applied light curve model fitting and outlier analysis to identify objects exhibiting EE emission and studied their photometric properties. Results. We identify 20 SNe IIb with EE, corresponding to a frequency of approximately 30.5% to 50%, the higher value being obtained under the most stringent observational data-quality cuts. The duration and colour evolution of the early excess 91̽�� its interpretation as shock cooling in extended envelopes. We also find that EE SNe IIb exhibit faster post-peak declines than non-EE events, while both groups show similar peak absolute magnitudes and rise-time distributions. Conclusions. Our findings suggest that EE and non-EE SNe IIb likely share similar initial progenitor masses but differ in their ejecta properties, potentially due to varying degrees of binary interaction. This study constrains EE SNe frequency and photometric properties, paving the way for future theoretical work, such as hydrodynamical modelling of EE SNe light curves, which could corroborate these results and contribute to constraining the evolutionary pathways of SNe IIb progenitor systems.

Abstract:

With the 4-metre Multi-Object Spectroscopic Telescope (4MOST) expected to provide an influx of transient spectra when it begins observations in early 2026 we consider the potential for real-time classification of these spectra. We investigate three extant spectroscopic transient classifiers: the Deep Automated Supernova and Host classifier (dash), Next Generation SuperFit (ngsf), and SuperNova IDentification (snid), with a focus on comparing the completeness and purity of the transient samples they produce. We manually simulate fibre losses critical for accurately determining host contamination and use the 4MOST Exposure Time Calculator to produce realistic, 4MOST-like, host-galaxy contaminated spectra. We investigate the three classifiers individually and in all possible combinations. We find that a combination of dash and ngsf can produce a supernova (SN) Ia sample with a purity of 99.9 per cent, while successfully classifying 70 per cent of SNe Ia. However, it struggles to classify non-SN Ia transients. We investigate photometric cuts to transient magnitude and the transient’s fraction of total fibre flux, finding that both can be used to improve non-SN Ia transient classification completeness by 8–44 per cent with SNe Ibc benefitting the most and superluminous (SL) SNe the least. Finally, we present an example classification plan for live classification and the predicted purities and completeness across five transient classes: Ia, Ibc, II, SL, and non-SN transients. We find that it is possible to classify 75 per cent of input spectra with 70 per cent purity in all classes except non-SN transients. Precise values can be varied using different classifiers and photometric cuts to suit the needs of a given study.