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Abstract We present the full Hubble diagram of photometrically classified Type Ia supernovae (SNe Ia) from the Dark Energy Survey supernova program (DES-SN). DES-SN discovered more than 20,000 SN candidates and obtained spectroscopic redshifts of 7000 host galaxies. Based on the light-curve quality, we select 1635 photometrically identified SNe Ia with spectroscopic redshift 0.10 <z< 1.13, which is the largest sample of supernovae from any single survey and increases the number of knownz> 0.5 supernovae by a factor of 5. In a companion paper, we present cosmological results of the DES-SN sample combined with 194 spectroscopically classified SNe Ia at low redshift as an anchor for cosmological fits. Here we present extensive modeling of this combined sample and validate the entire analysis pipeline used to derive distances. We show that the statistical and systematic uncertainties on cosmological parameters are ${\sigma }_{{\mathrm{\Omega }}_M,\mathrm{stat}+\mathrm{sys}}^{\mathrm{\Lambda }\mathrm{CDM}}=$0.017 in a flat ΛCDM model, and $({\sigma }_{{\mathrm{\Omega }}_M},{\sigma }_w{)}_{\mathrm{stat}+\mathrm{sys}}^{w\mathrm{CDM}}$= (0.082, 0.152) in a flatwCDM model. Combining the DES SN data with the highly complementary cosmic microwave background measurements by Planck Collaboration reduces by a factor of 4 uncertainties on cosmological parameters. In all cases, statistical uncertainties dominate over systematics. We show that uncertainties due to photometric classification make up less than 10% of the total systematic uncertainty budget. This result sets the stage for the next generation of SN cosmology surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time. 

ABSTRACT Hydrogen-rich Type II supernovae (SNe II) are the most frequently observed class of core-collapse SNe (CCSNe). However, most studies that analyse large samples of SNe II lack events with absolute peak magnitudes brighter than −18.5 mag at rest-frame optical wavelengths. Thanks to modern surveys, the detected number of such luminous SNe II (LSNe II) is growing. There exist several mechanisms that could produce luminous SNe II. The most popular propose either the presence of a central engine (a magnetar gradually spinning down or a black hole accreting fallback material) or the interaction of supernova ejecta with circumstellar material (CSM) that turns kinetic energy into radiation energy. In this work, we study the light curves and spectral series of a small sample of six LSNe II that show peculiarities in their H α profile, to attempt to understand the underlying powering mechanism. We favour an interaction scenario with CSM that is not dense enough to be optically thick to electron scattering on large scales – thus, no narrow emission lines are observed. This conclusion is based on the observed light curve (higher luminosity, fast decline, blue colours) and spectral features (lack of persistent narrow lines, broad H α emission, lack of H α absorption, weak, or non-existent metal lines) together with comparison to other luminous events available in the literature. We add to the growing evidence that transients powered by ejecta–CSM interaction do not necessarily display persistent narrow emission lines. 

ABSTRACT As part of the cosmology analysis using Type Ia Supernovae (SN Ia) in the Dark Energy Survey (DES), we present photometrically identified SN Ia samples using multiband light curves and host galaxy redshifts. For this analysis, we use the photometric classification framework SuperNNovatrained on realistic DES-like simulations. For reliable classification, we process the DES SN programme (DES-SN) data and introduce improvements to the classifier architecture, obtaining classification accuracies of more than 98 per cent on simulations. This is the first SN classification to make use of ensemble methods, resulting in more robust samples. Using photometry, host galaxy redshifts, and a classification probability requirement, we identify 1863 SNe Ia from which we select 1484 cosmology-grade SNe Ia spanning the redshift range of 0.07 < z < 1.14. We find good agreement between the light-curve properties of the photometrically selected sample and simulations. Additionally, we create similar SN Ia samples using two types of Bayesian Neural Network classifiers that provide uncertainties on the classification probabilities. We test the feasibility of using these uncertainties as indicators for out-of-distribution candidates and model confidence. Finally, we discuss the implications of photometric samples and classification methods for future surveys such as Vera C. Rubin Observatory Legacy Survey of Space and Time. 

ABSTRACT We present multiwavelength spectral and temporal variability analysis of PKS 0027-426 using optical griz observations from Dark Energy Survey between 2013 and 2018 and VEILS Optical Light curves of Extragalactic TransienT Events (VOILETTE) between 2018 and 2019 and near-infrared (NIR) JKs observations from Visible and Infrared Survey Telescope for Astronomy Extragalactic Infrared Legacy Survey (VEILS) between 2017 and 2019. Multiple methods of cross-correlation of each combination of light curve provides measurements of possible lags between optical–optical, optical–NIR, and NIR–NIR emission, for each observation season and for the entire observational period. Inter-band time lag measurements consistently suggest either simultaneous emission or delays between emission regions on time-scales smaller than the cadences of observations. The colour–magnitude relation between each combination of filters was also studied to determine the spectral behaviour of PKS 0027-426. Our results demonstrate complex colour behaviour that changes between bluer when brighter, stable when brighter, and redder when brighter trends over different time-scales and using different combinations of optical filters. Additional analysis of the optical spectra is performed to provide further understanding of this complex spectral behaviour. 

ABSTRACT Reverberation mapping is a robust method to measure the masses of supermassive black holes outside of the local Universe. Measurements of the radius–luminosity (R−L) relation using the Mg ii emission line are critical for determining these masses near the peak of quasar activity at z ≈ 1−2, and for calibrating secondary mass estimators based on Mg ii that can be applied to large samples with only single-epoch spectroscopy. We present the first nine Mg ii lags from our 5-yr Australian Dark Energy Survey reverberation mapping programme, which substantially improves the number and quality of Mg ii lag measurements. As the Mg ii feature is somewhat blended with iron emission, we model and subtract both the continuum and iron contamination from the multiepoch spectra before analysing the Mg ii line. We also develop a new method of quantifying correlated spectroscopic calibration errors based on our numerous, contemporaneous observations of F-stars. The lag measurements for seven of our nine sources are consistent with both the H β and Mg ii R−L relations reported by previous studies. Our simulations verify the lag reliability of our nine measurements, and we estimate that the median false positive rate of the lag measurements is $$4{{\ \rm per\ cent}}$$. 

Abstract SN 2017jgh is a type IIb supernova discovered by Pan-STARRS during the C16/C17 campaigns of the Kepler/K2 mission. Here we present the Kepler/K2 and ground based observations of SN 2017jgh, which captured the shock cooling of the progenitor shock breakout with an unprecedented cadence. This event presents a unique opportunity to investigate the progenitors of stripped envelope supernovae. By fitting analytical models to the SN 2017jgh lightcurve, we find that the progenitor of SN 2017jgh was likely a yellow supergiant with an envelope radius of ∼50 − 290 R⊙, and an envelope mass of ∼0 − 1.7 M⊙. SN 2017jgh likely had a shock velocity of ∼7500 − 10300 km s−1. Additionally, we use the lightcurve of SN 2017jgh to investigate how early observations of the rise contribute to constraints on progenitor models. Fitting just the ground based observations, we find an envelope radius of ∼50 − 330 R⊙, an envelope mass of ∼0.3 − 1.7 M⊙ and a shock velocity of ∼9, 000 − 15, 000 km s−1. Without the rise, the explosion time can not be well constrained which leads to a systematic offset in the velocity parameter and larger uncertainties in the mass and radius. Therefore, it is likely that progenitor property estimates through these models may have larger systematic uncertainties than previously calculated. 

ABSTRACT Cosmological analyses of samples of photometrically identified type Ia supernovae (SNe Ia) depend on understanding the effects of ‘contamination’ from core-collapse and peculiar SN Ia events. We employ a rigorous analysis using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark energy equation-of-state, w. Assuming a flat universe with Gaussian ΩM prior of 0.311 ± 0.010, we show that biases on w are <0.008 when using SuperNNova, with systematic uncertainties associated with contamination around 10 per cent of the statistical uncertainty on w for the DES-SN sample. An alternative approach of discarding contaminants using outlier rejection techniques (e.g. Chauvenet’s criterion) in place of SuperNNova leads to biases on w that are larger but still modest (0.015–0.03). Finally, we measure biases due to contamination on w0 and wa (assuming a flat universe), and find these to be <0.009 in w0 and <0.108 in wa, 5 to 10 times smaller than the statistical uncertainties for the DES-SN sample. 

ABSTRACT We present the results from a high-cadence, multiwavelength observation campaign of AT 2016jbu (aka Gaia16cfr), an interacting transient. This data set complements the current literature by adding higher cadence as well as extended coverage of the light-curve evolution and late-time spectroscopic evolution. Photometric coverage reveals that AT 2016jbu underwent significant photometric variability followed by two luminous events, the latter of which reached an absolute magnitude of MV ∼ −18.5 mag. This is similar to the transient SN 2009ip whose nature is still debated. Spectra are dominated by narrow emission lines and show a blue continuum during the peak of the second event. AT 2016jbu shows signatures of a complex, non-homogeneous circumstellar material (CSM). We see slowly evolving asymmetric hydrogen line profiles, with velocities of 500 km s−1 seen in narrow emission features from a slow-moving CSM, and up to 10 000 km s−1 seen in broad absorption from some high-velocity material. Late-time spectra (∼+1 yr) show a lack of forbidden emission lines expected from a core-collapse supernova and are dominated by strong emission from H, He i, and Ca ii. Strong asymmetric emission features, a bumpy light curve, and continually evolving spectra suggest an inhibit nebular phase. We compare the evolution of H α among SN 2009ip-like transients and find possible evidence for orientation angle effects. The light-curve evolution of AT 2016jbu suggests similar, but not identical, circumstellar environments to other SN 2009ip-like transients.