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For the past decade, SALT2 has been the most common model used to fit Type Ia supernova (SN Ia) light curves for dark energy analyses. Recently, the SALT3 model was released, which upgraded a number of model features but has not yet been used for measurements of dark energy. Here, we evaluate the impact of switching from SALT2 to SALT3 for a SN cosmology analysis. We train SALT2 and SALT3 on an identical training sample of 1083 well-calibrated Type Ia supernovae, ensuring that any differences found come from the underlying model framework. We publicly release the results of this training (the SALT "surfaces"). We then run a cosmology analysis on the public Dark Energy Survey 3-Year Supernova data sample (DES-SN3YR), and on realistic simulations of those data. We provide the first estimate of the SN+CMB systematic uncertainty arising from the choice of SALT model framework (i.e. SALT2 versus SALT3), $\Delta w = +0.001 \pm 0.005$ -- a negligible effect at the current level of dark energy analyses. We also find that the updated surfaces are less sensitive to photometric calibration uncertainties than previous SALT2 surfaces, with the average spectral energy density dispersion reduced by a factor of two over optical wavelengths. This offers an opportunity to reduce the contribution of calibration errors to SN cosmology uncertainty budgets., Comment: 19 pages, 13 figures, accepted by MNRAS

When the light from a distant object passes very near to a foreground galaxy or cluster, gravitational lensing can cause it to appear as multiple images on the sky. If the source is variable, it can be used to constrain the cosmic expansion rate and dark energy models. Achieving these cosmological goals requires many lensed transients with precise time delay measurements. Lensed supernovae (SN) are attractive for this purpose because they have relatively simple photometric behavior, with well-understood light curve shapes and colours $-$ in contrast to the stochastic variation of quasars. Here we report the discovery of a multiply-imaged supernova, AT2016jka ("SN Requiem"). It appeared in an evolved galaxy at $z=1.95$, gravitationally lensed by a foreground galaxy cluster. It is likely a Type Ia supernova $-$ the explosion of a low-mass stellar remnant, whose light curve can be used to measure cosmic distances. In archival Hubble Space Telescope imaging, three lensed images of the supernova are detected with relative time delays of $, Comment: Accepted for publication in a peer-reviewed journal. Main text = 6 pages, 3 figures, 1 table; Full document = 28 pages, 12 figures with Methods, Supplemental Info and references. v2: reformatted; minor corrections in SI

We present panchromatic observations and modeling of calcium-strong supernovae (SNe) 2021gno in the star-forming host-galaxy NGC 4165 and 2021inl in the outskirts of elliptical galaxy NGC 4923, both monitored through the Young Supernova Experiment transient survey. The light curves of both, SNe show two peaks, the former peak being derived from shock cooling emission (SCE) and/or shock interaction with circumstellar material (CSM). The primary peak in SN 2021gno is coincident with luminous, rapidly decaying X-ray emission (L x = 5 × 1041 erg s−1) detected by Swift-XRT at δ t = 1 day after explosion, this observation being the second-ever detection of X-rays from a calcium-strong transient. We interpret the X-ray emission in the context of shock interaction with CSM that extends to r < 3 × 1014 cm. Based on X-ray modeling, we calculate a CSM mass M CSM = (0.3−1.6) × 10−3 M ⊙ and density n = (1−4) × 1010 cm−3. Radio nondetections indicate a low-density environment at larger radii (r > 1016 cm) and mass-loss rate of M ̇ < 10 − 4 M ⊙ yr−1. SCE modeling of both primary light-curve peaks indicates an extended-progenitor envelope mass M e = 0.02−0.05 M ⊙ and radius R e = 30−230 R ⊙. The explosion properties suggest progenitor systems containing either a low-mass massive star or a white dwarf (WD), the former being unlikely given the lack of local star formation. Furthermore, the environments of both SNe are consistent with low-mass hybrid He/C/O WD + C/O WD mergers.

We present observations of SN 2020fqv, a Virgo-cluster Type II core-collapse supernova (CCSN) with a high temporal resolution light curve from the Transiting Exoplanet Survey Satellite (TESS) covering the time of explosion; ultraviolet (UV) spectroscopy from the Hubble Space Telescope (HST) starting 3.3 days post-explosion; ground-based spectroscopic observations starting 1.1~days post-explosion; along with extensive photometric observations. Massive stars have complicated mass-loss histories leading up to their death as CCSNe, creating circumstellar medium (CSM) with which the SNe interact. Observations during the first few days post-explosion can provide important information about the mass-loss rate during the late stages of stellar evolution. Model fits to the quasi-bolometric light curve of SN 2020fqv reveal ~0.23 $M_{\odot}$ of CSM confined within ~1450 $R_{\odot}$ ($10^{14}$ cm) from its progenitor star. Early spectra (, Published in MNRAS

Supernovae (SNe) that have been multiply imaged by gravitational lensing are rare and powerful probes for cosmology. Each detection is an opportunity to develop the critical tools and methodologies needed as the sample of lensed SNe increases by orders of magnitude with the upcoming Vera C. Rubin Observatory and Nancy Grace Roman Space Telescope. The latest such discovery is of the quadruply imaged Type Ia SN 2022qmx (aka, “SN Zwicky”) at z = 0.3544. SN Zwicky was discovered by the Zwicky Transient Facility in spatially unresolved data. Here we present follow-up Hubble Space Telescope observations of SN Zwicky, the first from the multicycle “LensWatch (www.lenswatch.org)” program. We measure photometry for each of the four images of SN Zwicky, which are resolved in three WFC3/UVIS filters (F475W, F625W, and F814W) but unresolved with WFC3/IR F160W, and present an analysis of the lensing system using a variety of independent lens modeling methods. We find consistency between lens-model-predicted time delays (≲1 day), and delays estimated with the single epoch of Hubble Space Telescope colors (≲3.5 days), including the uncertainty from chromatic microlensing (∼1–1.5 days). Our lens models converge to an Einstein radius of θ E = ( 0.168 − 0.005 + 0.009 ) ″ , the smallest yet seen in a lensed SN system. The “standard candle” nature of SN Zwicky provides magnification estimates independent of the lens modeling that are brighter than predicted by ∼ 1.7 − 0.6 + 0.8 mag and ∼ 0.9 − 0.6 + 0.8 mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

In the next decade, transient searches from the Vera C. Rubin Observatory and the Nancy Grace Roman Space Telescope will increase the sample of known Type Ia supernovae (SNe Ia) from ∼103 to 105. With this reduction of statistical uncertainties on cosmological measurements, new methods are needed to reduce systematic uncertainties. Characterizing the underlying spectroscopic evolution of SN Ia remains a major systematic uncertainty in current cosmological analyses, motivating a new simulation tool for the next era of SN Ia cosmology: Build Your Own Spectral Energy Distribution (byosed). byosed is used within the SNANA framework to simulate light curves by applying spectral variations to model SEDs, enabling flexible testing of possible systematic shifts in SN Ia distance measurements. We test the framework by comparing a nominal Roman SN Ia survey simulation using a baseline SED model to simulations using SEDs perturbed with byosed, and investigating the impact of ignoring specific SED features in the analysis. These features include semiempirical models of two possible, predicted relationships: between SN ejecta velocity and light-curve observables, and a redshift-dependent relationship between SN Hubble residuals and host-galaxy mass. We analyze each byosed simulation using the SALT2 and BEAMS with Bias Corrections framework, and estimate changes in the measured value of the dark-energy equation-of-state parameter, w. We find a difference of Δw = −0.023 for SN velocity and Δw = 0.021 for redshift-evolving host mass when compared to simulations without these features. By using byosed for SN Ia cosmology simulations, future analyses (e.g., the Rubin and Roman SN Ia samples) will have greater flexibility to constrain or reduce such SN Ia modeling uncertainties.

One of the primary mission objectives for the Roman Space Telescope is to investigate the nature of dark energy with a variety of methods. Observations of Type Ia supernovae (SNIa) will be one of the principal anchors of the Roman cosmology program, through traditional luminosity distance measurements. This SNIa cosmology program can provide another valuable cosmological probe, without altering the mission strategy: time delay cosmography with gravitationally lensed SN. In this work, we forecast lensed SN cosmology constraints with the Roman Space Telescope, while providing useful tools for future work. Using anticipated characteristics of the Roman SNIa survey, we have constructed mock catalogs of expected resolved lensing systems, as well as strongly lensed Type Ia and core-collapse (CC) SN light curves, including microlensing effects. We predict Roman will find ~11 lensed SNIa and ~20 CCSN, dependent on the survey strategy. Next, we estimate the time delay precision obtainable with Roman (Ia: ~2 days, CC: ~3 days), and use a Fisher matrix analysis to derive projected constraints on $H_0$,$\Omega_m$, and the dark energy Equation of State (EOS), $w$, for each SNIa survey strategy. A strategy optimized for high-redshift SNIa discovery is preferred when considering the constraints possible from both SNIa and lensed SN cosmology, also delivering ~1.5 times more lensed SN than other proposed survey strategies., Comment: Accepted Version (ApJ, 1/4/21)

International audience; We describe the simulated data sample for the Photometric Large Synoptic Survey Telescope (LSST) Astronomical Time Series Classification Challenge (PLAsTiCC), a publicly available challenge to classify transient and variable events that will be observed by the LSST, a new facility expected to start in the early 2020s. The challenge was hosted by Kaggle, ran from 2018 September 28 to December 17, and included 1094 teams competing for prizes. Here we provide details of the 18 transient and variable source models, which were not revealed until after the challenge, and release the model libraries at https://doi.org/10.5281/zenodo.2612896. We describe the LSST Operations Simulator used to predict realistic observing conditions, and we describe the publicly available SNANA simulation code used to transform the models into observed fluxes and uncertainties in the LSST passbands (ugrizy). Although PLAsTiCC has finished, the publicly available models and simulation tools are being used within the astronomy community to further improve classification, and to study contamination in photometrically identified samples of SN Ia used to measure properties of dark energy. Our simulation framework will continue serving as a platform to improve the PLAsTiCC models, and to develop new models.

Empirical models of supernova (SN) spectral energy distributions (SEDs) are widely used for SN survey simulations and photometric classifications. The existing library of SED models has excellent optical templates but limited, poorly constrained coverage of ultraviolet (UV) and infrared (IR) wavelengths. However, both regimes are critical for the design and operation of future SN surveys, particularly at IR wavelengths that will be accessible with the James Webb Space Telescope (JWST) and the Wide-Field Infrared Survey Telescope (WFIRST). We create a public repository of improved empirical SED templates using a sampling of Type Ia and core-collapse (CC) photometric light curves to extend the Type Ia parameterized SALT2 model and a set of SN Ib, SN Ic, and SN II SED templates into the UV and near-IR. We apply this new repository of extrapolated SN SED models to examine how future surveys can discriminate between CC and Type Ia SNe at UV and IR wavelengths, and present an open-source software package written in Python, SNSEDextend, that enables a user to generate their own extrapolated SEDs.

We present new measurements of the deuterium abundance on Jupiter and Saturn, showing evidence that Saturn's atmosphere contains less deuterium than Jupiter's. We analyzed far-infrared spectra from theCassiniComposite Infrared Spectrometer to measure the abundance of HD on both giant planets. Our estimate of the Jovian D/H = (2.95 ± 0.55)×10−5is in agreement with previous measurements byISO/SWS: (2.25 ± 0.35)×10−5, and the Galileo probe: (2.6 ± 0.7)×10−5. In contrast, our estimate of the Saturn value of (2.10 ± 0.13)×10−5is somewhat lower than on Jupiter (by a factor of), contrary to model predictions of a higher ratio: Saturn/Jupiter = 1.05–1.20. The Saturn D/H value is consistent with estimates for hydrogen in the protosolar nebula (2.1 ± 0.5)×10−5, but its apparent divergence from the Jovian value suggests that our understanding of planetary formation and evolution is incomplete, which is in agreement with previous work.

Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, "Refsdal", and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the separate images. These measurements provide precise tests of lens models or constraints on the Hubble constant and other cosmological parameters that are independent of the local distance ladder. Over the next decade, accurate time delay measurements will be needed for the tens to hundreds of lensed SNe to be found by wide-field time-domain surveys such as LSST and WFIRST. We have developed an open source software package for simulations and time delay measurements of multiply-imaged SNe, including an improved characterization of the uncertainty caused by microlensing. We describe simulations using the package that suggest a before-peak detection of the leading image enables a more accurate and precise time delay measurement (by ~1 and ~2 days, respectively), when compared to an after-peak detection. We also conclude that fitting the effects of microlensing without an accurate prior often leads to biases in the time delay measurement and over-fitting to the data, but that employing a Gaussian Process Regression (GPR) technique is sufficient for determining the uncertainty due to microlensing., Comment: Accepted 4/3 to ApJ