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1. ASAS-SN follow-up of IceCube high-energy neutrino alerts

   https://doi.org/10.1093/mnras/stac2261  

   Necker, Jannis ; de Jaeger, Thomas ; Stein, Robert ; Franckowiak, Anna ; Shappee, Benjamin J. ; Kowalski, Marek ; Kochanek, Christopher S. ; Stanek, Krzysztof Z. ; Beacom, John F. ; Desai, Dhvanil D. ; et al ( August 2022 , Monthly Notices of the Royal Astronomical Society)

   We report on the search for optical counterparts to IceCube neutrino alerts released between 2016 April and 2021 August with the All-Sky Automated Survey for SuperNovae (ASAS-SN). Despite the discovery of a diffuse astrophysical high-energy neutrino flux in 2013, the source of those neutrinos remains largely unknown. Since 2016, IceCube has published likely astrophysical neutrinos as public real-time alerts. Through a combination of normal survey and triggered target-of-opportunity observations, ASAS-SN obtained images within 1 h of the neutrino detection for 20 per cent (11) of all observable IceCube alerts and within one day for another 57 per cent (32). For all observable alerts, we obtained images within at least two weeks from the neutrino alert. ASAS-SN provides the only optical follow-up for about 17 per cent of IceCube’s neutrino alerts. We recover the two previously claimed counterparts to neutrino alerts, the flaring-blazar TXS 0506 + 056 and the tidal disruption event AT2019dsg. We investigate the light curves of previously detected transients in the alert footprints, but do not identify any further candidate neutrino sources. We also analysed the optical light curves of Fermi 4FGL sources coincident with high-energy neutrino alerts, but do not identify any contemporaneous flaring activity. Finally, we derive constraints on the luminosity functions of neutrino sources for a range of assumed evolution models.

    

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2. Photometric Classification of Early-time Supernova Light Curves with SCONE

   https://doi.org/10.3847/1538-3881/ac39a1  

   Qu, Helen ; Sako, Masao ( January 2022 , The Astronomical Journal)

   In this work, we present classification results on early supernova light curves from SCONE, a photometric classifier that uses convolutional neural networks to categorize supernovae (SNe) by type using light-curve data. SCONE is able to identify SN types from light curves at any stage, from the night of initial alert to the end of their lifetimes. Simulated LSST SNe light curves were truncated at 0, 5, 15, 25, and 50 days after the trigger date and used to train Gaussian processes in wavelength and time space to produce wavelength–time heatmaps. SCONE uses these heatmaps to perform six-way classification between SN types Ia, II, Ibc, Ia-91bg, Iax, and SLSN-I. SCONE is able to perform classification with or without redshift, but we show that incorporating redshift information improves performance at each epoch. SCONE achieved 75% overall accuracy at the date of trigger (60% without redshift), and 89% accuracy 50 days after trigger (82% without redshift). SCONE was also tested on bright subsets of SNe (r< 20 mag) and produced 91% accuracy at the date of trigger (83% without redshift) and 95% five days after trigger (94.7% without redshift). SCONE is the first application of convolutional neural networks to the early-time photometric transient classification problem. All of the data processing and model code developed for this paper can be found in the SCONE software package¹1

   github.com/helenqu/scone

   located at github.com/helenqu/scone (Qu 2021).

    

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3. Supernova 2020wnt: An Atypical Superluminous Supernova with a Hidden Central Engine

   https://doi.org/10.3847/1538-4357/acc6c3  

   Tinyanont, Samaporn ; Woosley, Stan E. ; Taggart, Kirsty ; Foley, Ryan J. ; Yan, Lin ; Lunnan, Ragnhild ; Davis, Kyle W. ; Kilpatrick, Charles D. ; Siebert, Matthew R. ; Schulze, Steve ; et al ( June 2023 , The Astrophysical Journal)

   We present observations of a peculiar hydrogen- and helium-poor stripped-envelope (SE) supernova (SN) 2020wnt, primarily in the optical and near-infrared (near-IR). Its peak absolute bolometric magnitude of −20.9 mag (L_{bol, peak}= (6.8 ± 0.3) × 10⁴³erg s⁻¹) and a rise time of 69 days are reminiscent of hydrogen-poor superluminous SNe (SLSNe I), luminous transients potentially powered by spinning-down magnetars. Before the main peak, there is a brief peak lasting <10 days post explosion, likely caused by interaction with circumstellar medium (CSM) ejected ∼years before the SN explosion. The optical spectra near peak lack a hot continuum and Oiiabsorptions, which are signs of heating from a central engine; they quantitatively resemble those of radioactivity-powered hydrogen/helium-poor Type Ic SESNe. At ∼1 yr after peak, nebular spectra reveal a blue pseudo-continuum and narrow Oirecombination lines associated with magnetar heating. Radio observations rule out strong CSM interactions as the dominant energy source at +266 days post peak. Near-IR observations at +200–300 days reveal carbon monoxide and dust formation, which causes a dramatic optical light-curve dip. Pair-instability explosion models predict slow light curve and spectral features incompatible with observations. SN 2020wnt is best explained as a magnetar-powered core-collapse explosion of a 28M_⊙pre-SN star. The explosion kinetic energy is significantly larger than the magnetar energy at peak, effectively concealing the magnetar-heated inner ejecta until well after peak. SN 2020wnt falls into a continuum between normal SNe Ic and SLSNe I, and demonstrates that optical spectra at peak alone cannot rule out the presence of a central engine.

    

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4. Keck Infrared Transient Survey. I. Survey Description and Data Release 1

   https://doi.org/10.1088/1538-3873/ad1b39  

   Tinyanont, S. ; Foley, R. J. ; Taggart, K. ; Davis, K. W. ; LeBaron, N. ; Andrews, J. E. ; Bustamante-Rosell, M. J. ; Camacho-Neves, Y. ; Chornock, R. ; Coulter, D. A. ; et al ( January 2024 , Publications of the Astronomical Society of the Pacific)

   We present the Keck Infrared Transient Survey, a NASA Key Strategic Mission Support program to obtain near-infrared (NIR) spectra of astrophysical transients of all types, and its first data release, consisting of 105 NIR spectra of 50 transients. Such a data set is essential as we enter a new era of IR astronomy with the James Webb Space Telescope (JWST) and the upcoming Nancy Grace Roman Space Telescope (Roman). NIR spectral templates will be essential to search JWST images for stellar explosions of the first stars and to plan an effective Roman SN Ia cosmology survey, both key science objectives for mission success. Between 2022 February and 2023 July, we systematically obtained 274 NIR spectra of 146 astronomical transients, representing a significant increase in the number of available NIR spectra in the literature. Here, we describe the first release of data from the 2022A semester. We systematically observed three samples: a flux-limited sample that includes all transients <17 mag in a red optical band (usually ZTFror ATLASobands); a volume-limited sample including all transients within redshiftz< 0.01 (D≈ 50 Mpc); and an SN Ia sample targeting objects at phases and light-curve parameters that had scant existing NIR data in the literature. The flux-limited sample is 39% complete (60% excluding SNe Ia), while the volume-limited sample is 54% complete and is 79% complete toz= 0.005. Transient classes observed include common Type Ia and core-collapse supernovae, tidal disruption events, luminous red novae, and the newly categorized hydrogen-free/helium-poor interacting Type Icn supernovae. We describe our observing procedures and data reduction usingPypeIt, which requires minimal human interaction to ensure reproducibility.

    

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5. A Spectroscopic Model of the Type Ia Supernova–Host-galaxy Mass Correlation from SALT3

   https://doi.org/10.3847/1538-4357/acd195  

   Jones, D. O. ; Kenworthy, W. D. ; Dai, M. ; Foley, R. J. ; Kessler, R. ; Pierel, J. D. R. ; Siebert, M. R. ( June 2023 , The Astrophysical Journal)

   The unknown cause of the correlation between Type Ia supernova (SN Ia) Hubble residuals and their host-galaxy masses (the “mass step”) may bias cosmological parameter measurements. To better understand the mass step, we develop a SALT3 light-curve model for SN cosmology that uses the host-galaxy masses of 296 low-redshift SNe Ia to derive a spectral energy distribution–host-galaxy mass relationship. The resulting model has larger CaiiH and K, Caiinear-infrared triplet, and Siiiequivalent widths for SNe in low-mass host galaxies at 2.2–2.7σsignificance; this indicates higher explosion energies per unit mass in low-mass-hosted SNe. The model has phase-dependent changes in SN Ia colors as a function of host mass, indicating intrinsic differences in mean broadband light curves. Although the model provides a better fit to the SN data overall, it does not substantially reduce data–model residuals for a typical light curve in our sample nor does it significantly reduce Hubble residual dispersion. This is because we find that previous SALT models parameterized most host-galaxy dependencies with their first principal component, although they failed to model some significant spectral variations. Our new model is luminosity and cosmology independent, and applying it to data reduces the mass step by 0.021 ± 0.002 mag (uncertainty accounts for correlated data sets); these results indicate that ∼35% of the mass step can be attributed to luminosity-independent effects. This SALT model version could be trained using alternative host-galaxy properties and at different redshifts, and therefore will be a tool for understanding redshift-dependent correlations between SNe Ia and their host properties as well as their impact on cosmological parameter measurements.

    

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