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Context.Type Ia supernovae (SNe Ia) are a key probe in modern cosmology, as they can be used to measure luminosity distances at gigaparsec scales. Models of their light curves are used to project heterogeneous observed data onto a common basis for analysis. Aims.The SALT model currently used for SN Ia cosmology describes SNe as having two sources of variability, accounted for by a color parameterc, and a “stretch” parameterx₁. We extend the model to include an additional parameter we labelx₂, to investigate the cosmological impact of currently unaddressed light-curve variability. Methods.We constructed a new SALT model, that we dub “SALT3+”. This model was trained by an improved version of theSALTshakercode, using training data combining a selection of the second data release of cosmological SNe Ia from the Zwicky Transient Facility and the existing SALT3 training compilation. Results.We find additional, coherent variability in supernova light curves beyond SALT3. Most of this variation can be described as phase-dependent variation ing − randr − icolor curves, correlated with a boost in the height of the secondary maximum ini-band. These behaviors correlate with spectral differences, particularly in line velocity. We find that fits with the existing SALT3 model tend to address this excess variation with the color parameter, leading to less informative measurements of supernova color. We find that neglecting the new parameter in light-curve fits leads to a trend in Hubble residuals withx₂of 0.039 ± 0.005 mag, representing a potential systematic uncertainty. However, we find no evidence of a bias in current cosmological measurements. Conclusions.We conclude that extended SN Ia light-curve models promise mild improvement in the accuracy of color measurements, and corresponding cosmological precision. However, models with more parameters are unlikely to substantially affect current cosmological results. 

Abstract We present an ultraviolet to infrared search for the electromagnetic (EM) counterpart to GW190425, the second ever binary neutron star merger discovered by the LIGO-Virgo-KAGRA Collaboration. GW190425 was more distant and had a larger localization area than GW170817, so we use a new tool,Teglon, to redistribute the GW190425 localization probability in the context of galaxy catalogs within the final localization volume. We derive a 90th percentile area of 6688 deg², a ∼1.5× improvement relative to the LIGO/Virgo map, and show howTeglonprovides an order-of-magnitude boost to the search efficiency of small (≤1 deg²) field-of-view instruments. We combine our data with a large, publicly reported imaging data set, covering 9078.59 deg²of unique area and 48.13% of the LIGO/Virgo-assigned localization probability, to calculate the most comprehensive kilonova (KN), short gamma-ray burst (sGRB) afterglow, and model-independent constraints on the EM emission from a hypothetical counterpart to GW190425 to date under the assumption that no counterpart was found in these data. If the counterpart were similar to AT 2017gfo, there would be a 28.4% chance of it being detected in the combined data set. We are relatively insensitive to an on-axis sGRB, and rule out a generic transient with a similar peak luminosity and decline rate as AT 2017gfo to 30% confidence. Finally, across our new imaging and publicly reported data, we find 28 candidate optical counterparts that we cannot rule out as being associated with GW190425, finding that four such counterparts discovered within the localization volume and within 5 days of merger exhibit luminosities consistent with a KN. 

Abstract We present analysis of the plateau and late-time phase properties of a sample of 39 Type II supernovae (SNe II) that show narrow, transient, high-ionization emission lines (i.e., “IIn-like”) in their early-time spectra from interaction with confined, dense circumstellar material (CSM). Originally presented by W. V. Jacobson-Galán et al., this sample also includes multicolor light curves and spectra extending to late-time phases of 35 SNe with no evidence for IIn-like features at <2 days after first light. We measure photospheric phase light-curve properties for the distance-corrected sample and find that SNe II with IIn-like features have significantly higher luminosities and decline rates at +50 days than the comparison sample, which could be connected to inflated progenitor radii, lower ejecta mass, and/or persistent CSM interaction. However, we find no statistical evidence that the measured plateau durations and⁵⁶Ni masses of SNe II with and without IIn-like features arise from different distributions. We estimate progenitor zero-age main-sequence (ZAMS) masses for all SNe with nebular spectroscopy through spectral model comparisons and find that most objects, both with and without IIn-like features, are consistent with progenitor masses ≤12.5M_⊙. Combining progenitor ZAMS masses with CSM densities inferred from early-time spectra suggests multiple channels for enhanced mass loss in the final years before core collapse, such as a convection-driven chromosphere or binary interaction. Finally, we find spectroscopic evidence for ongoing ejecta-CSM interaction at radii >10¹⁶cm, consistent with substantial progenitor mass-loss rates of ∼10⁻⁴–10⁻⁵M_⊙yr⁻¹(v_w < 50 km s⁻¹) in the final centuries to millennia before explosion. 

Abstract We present UV–optical–near-infrared observations and modeling of supernova (SN) 2024ggi, a type II supernova (SN II) located in NGC 3621 at 7.2 Mpc. Early-time (“flash”) spectroscopy of SN 2024ggi within +0.8 days of discovery shows emission lines of Hi, Hei, Ciii, and Niiiwith a narrow core and broad, symmetric wings (i.e., “IIn-like”) arising from the photoionized, optically thick, unshocked circumstellar material (CSM) that surrounded the progenitor star at shock breakout (SBO). By the next spectral epoch at +1.5 days, SN 2024ggi showed a rise in ionization as emission lines of Heii, Civ, Niv/v, and Ovbecame visible. This phenomenon is temporally consistent with a blueward shift in the UV–optical colors, both likely the result of SBO in an extended, dense CSM. The IIn-like features in SN 2024ggi persist on a timescale oft_IIn= 3.8 ± 1.6 days, at which time a reduction in CSM density allows the detection of Doppler-broadened features from the fastest SN material. SN 2024ggi has peak UV–optical absolute magnitudes ofM_w2= −18.7 mag andM_g= −18.1 mag, respectively, that are consistent with the known population of CSM-interacting SNe II. Comparison of SN 2024ggi with a grid of radiation hydrodynamics and non–local thermodynamic equilibrium radiative-transfer simulations suggests a progenitor mass-loss rate of $\dot{M}={10}^{-2}{M}_{\odot }$yr⁻¹(v_w= 50 km s⁻¹), confined to a distance ofr< 5 × 10¹⁴cm. Assuming a wind velocity ofv_w= 50 km s⁻¹, the progenitor star underwent an enhanced mass-loss episode in the last ∼3 yr before explosion. 

Abstract We present ultraviolet to infrared observations of the extraordinary Type IIn supernova 2023zkd (SN 2023zkd). Photometrically, it exhibits persistent and luminous precursor emission spanning ∼4 yr preceding discovery (M_r ≈ −15 mag, 1500 days in the observer frame), followed by a secondary stage of gradual brightening in its final year. Post-discovery, it exhibits two photometric peaks of comparable brightness (M_r ≲ −18.7 mag andM_r ≈ −18.4 mag, respectively) separated by 240 days. Spectroscopically, SN 2023zkd exhibits highly asymmetric and multicomponent Balmer and HeIprofiles that we attribute to ejecta interaction with fast-moving (1000–2000 km s⁻¹) He-rich polar material and slow-moving (∼400 km s⁻¹) equatorially distributed H-rich material. HeIIfeatures also appear during the second light curve peak and evolve rapidly. Shock-driven models fit to the multiband photometry suggest that the event is powered by interaction with ∼5–6M_⊙of CSM, with 2–3M_⊙associated with each light curve peak, expelled during mass-loss episodes ∼3–4 yr and ∼1–2 yr prior to explosion. The observed precursor emission, combined with the extreme mass-loss rates required to power each light curve peak, favors either super-Eddington accretion onto a black hole or multiple long-lived eruptions from a massive star to luminosities that have not been previously observed. We consider multiple progenitor scenarios for SN 2023zkd, and find that the brightening optical precursor and inferred explosion properties are most consistent with a massive (M_ZAMS≥ 30M_⊙) and partially stripped He star undergoing an instability-induced merger with a black hole companion. 

Abstract The modern study of astrophysical transients has been transformed by an exponentially growing volume of data. Within the last decade, the transient discovery rate has increased by a factor of ∼20, with associated survey data, archival data, and metadata also increasing with the number of discoveries. To manage the data at this increased rate, we require new tools. Here we presentYSE-PZ, a transient survey management platform that ingests multiple live streams of transient discovery alerts, identifies the host galaxies of those transients, downloads coincident archival data, and retrieves photometry and spectra from ongoing surveys.YSE-PZalso presents a user with a range of tools to make and support timely and informed transient follow-up decisions. Those subsequent observations enhance transient science and can reveal physics only accessible with rapid follow-up observations. Rather than automating out human interaction,YSE-PZfocuses on accelerating and enhancing human decision making, a role we describe as empowering the human-in-the-loop. Finally,YSE-PZis built to be flexibly used and deployed;YSE-PZcan support multiple, simultaneous, and independent transient collaborations through group-level data permissions, allowing a user to view the data associated with the union of all groups in which they are a member.YSE-PZcan be used as a local instance installed via Docker or deployed as a service hosted in the cloud. We provideYSE-PZas an open-source tool for the community. 

Abstract We present ultraviolet/optical/near-infrared observations and modeling of Type II supernovae (SNe II) whose early time (δt< 2 days) spectra show transient, narrow emission lines from shock ionization of confined (r< 10¹⁵cm) circumstellar material (CSM). The observed electron-scattering broadened line profiles (i.e., IIn-like) of Hi, Hei/ii, Civ, and Niii/iv/vfrom the CSM persist on a characteristic timescale (t_IIn) that marks a transition to a lower-density CSM and the emergence of Doppler-broadened features from the fast-moving SN ejecta. Our sample, the largest to date, consists of 39 SNe with early time IIn-like features in addition to 35 “comparison” SNe with no evidence of early time IIn-like features, all with ultraviolet observations. The total sample includes 50 unpublished objects with a total of 474 previously unpublished spectra and 50 multiband light curves, collected primarily through the Young Supernova Experiment and Global Supernova Project collaborations. For all sample objects, we find a significant correlation between peak ultraviolet brightness and botht_IInand the rise time, as well as evidence for enhanced peak luminosities in SNe II with IIn-like features. We quantify mass-loss rates and CSM density for the sample through the matching of peak multiband absolute magnitudes, rise times,t_IIn, and optical SN spectra with a grid of radiation hydrodynamics and non-local thermodynamic equilibrium radiative-transfer simulations. For our grid of models, all with the same underlying explosion, there is a trend between the duration of the electron-scattering broadened line profiles and inferred mass-loss rate: $t_{\mathrm{IIn}}\approx 3.8[\dot{M}/$(0.01M_⊙yr⁻¹)] days. 

ABSTRACT After correcting for their light-curve shape and colour, Type Ia supernovae (SNe Ia) are precise cosmological distance indicators. However, there remains a non-zero intrinsic scatter in the differences between measured distance and that inferred from a cosmological model (i.e. Hubble residuals or HRs), indicating that SN Ia distances can potentially be further improved. We use the open-source relational data base kaepora to generate composite spectra with desired average properties of phase, light-curve shape, and HR. At many phases, the composite spectra from two subsamples with positive and negative average HRs are significantly different. In particular, in all spectra from 9 d before to 15 d after peak brightness, we find that SNe with negative HRs have, on average, higher ejecta velocities (as seen in nearly every optical spectral feature) than SNe with positive HRs. At +4 d relative to B-band maximum, using a sample of 62 SNe Ia, we measure a 0.091 ± 0.035 mag (2.7σ) HR step between SNe with Si ii λ6355 line velocities ($$v_{Si\, rm{\small II}}$$) higher/lower than −11 000 km s−1 (the median velocity). After light-curve shape and colour correction, SNe with higher velocities tend to have underestimated distance moduli relative to a cosmological model. The intrinsic scatter in our sample reduces from 0.094 to 0.082 mag after making this correction. Using the Si ii λ6355 velocity evolution of 115 SNe Ia, we estimate that a velocity difference >500 km s−1 exists at each epoch between the positive-HR and negative-HR samples with 99.4 per cent confidence. Finally at epochs later than +37 d, we observe that negative-HR composite spectra tend to have weaker spectral features in comparison to positive-HR composite spectra. 

Abstract Next-generation surveys like the Legacy Survey of Space and Time (LSST) on the Vera C. Rubin Observatory (Rubin) will generate orders of magnitude more discoveries of transients and variable stars than previous surveys. To prepare for this data deluge, we developed the Photometric LSST Astronomical Time-series Classification Challenge (PLAsTiCC), a competition that aimed to catalyze the development of robust classifiers under LSST-like conditions of a nonrepresentative training set for a large photometric test set of imbalanced classes. Over 1000 teams participated in PLAsTiCC, which was hosted in the Kaggle data science competition platform between 2018 September 28 and 2018 December 17, ultimately identifying three winners in 2019 February. Participants produced classifiers employing a diverse set of machine-learning techniques including hybrid combinations and ensemble averages of a range of approaches, among them boosted decision trees, neural networks, and multilayer perceptrons. The strong performance of the top three classifiers on Type Ia supernovae and kilonovae represent a major improvement over the current state of the art within astronomy. This paper summarizes the most promising methods and evaluates their results in detail, highlighting future directions both for classifier development and simulation needs for a next-generation PLAsTiCC data set.