Search

We present James Webb Space Telescope (JWST) NIRCam and NIRSpec observations of a Type Ic supernova (SN Ic) and its host galaxy (JADES-GS+53.13533-27.81457) at z = 2.83. This SN (named SN 2023adta) was identified in deep JWST/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Follow-up observations with JWST/NIRSpec provided a spectroscopic redshift of z = 2.83 and the classification as an SN Ic-BL. The light curve of SN 2023adta matches well with other stripped-envelope SNe, and we find a high peak luminosity, M _V = −19.0 ± 0.2 mag, based on the distribution of best-fit SNe. The broad absorption features in its spectrum are consistent with other SNe Ic-BL 1–3 weeks after peak brightness. We measure a Ca ii near-IR triplet expansion velocity of 29,000 ± 2000 km s ^−1 . The host galaxy of SN 2023adta is irregular, and modeling of its spectral energy distribution indicates a metallicity of $Z={0.35}_{-0.08}^{+0.16}{Z}_{\odot }$ . This environment is consistent with the population of low- z SNe Ic-BL that prefer lower metallicities relative to other stripped-envelope SNe and track long-duration γ -ray burst environments. We do not identify any γ -ray bursts that are coincident with SN 2023adta. Given the rarity of SNe Ic-BL in the local Universe, the detection of an SN Ic-BL at z = 2.83 could indicate that their rates are enhanced at high redshift.

We present the James Webb Space Telescope (JWST) discovery of SN 2023adsy, a transient object located in a host galaxy JADES-GS+53.13485−27.82088 with a host spectroscopic redshift of 2.903 ± 0.007. The transient was identified in deep (JWST)/NIRCam imaging from the JWST Advanced Deep Extragalactic Survey (JADES) program. Photometric and spectroscopic follow-up with NIRCam and NIRSpec, respectively, confirm the redshift and yield UV-NIR light-curve, NIR color, and spectroscopic information all consistent with a Type Ia classification. Despite its classification as a likely SN Ia, SN 2023adsy is both fairly red ( c ∼ 0.9) despite a host galaxy with low extinction and has a high Ca ii velocity (19,000 ± 2000 km s ^−1 ) compared to the general population of SNe Ia. While these characteristics are consistent with some Ca-rich SNe Ia, particularly SN 2016hnk, SN 2023adsy is intrinsically brighter than the low- z Ca-rich population. Although such an object is too red for any low- z cosmological sample, we apply a fiducial standardization approach to SN 2023adsy and find that the SN 2023adsy luminosity distance measurement is in excellent agreement (≲1 σ ) with ΛCDM. Therefore unlike low- z Ca-rich SNe Ia, SN 2023adsy is standardizable and gives no indication that SN Ia standardized luminosities change significantly with redshift. A larger sample of distant SNe Ia is required to determine if SN Ia population characteristics at high z truly diverge from their low- z counterparts and to confirm that standardized luminosities nevertheless remain constant with redshift.

A bright ( m _F150W,AB = 24 mag), z = 1.95 supernova (SN) candidate was discovered in JWST/NIRCam imaging acquired on 2023 November 17. The SN is quintuply imaged as a result of strong gravitational lensing by a foreground galaxy cluster, detected in three locations, and remarkably is the second lensed SN found in the same host galaxy. The previous lensed SN was called “Requiem,” and therefore the new SN is named “Encore.” This makes the MACS J0138.0−2155 cluster the first known system to produce more than one multiply imaged SN. Moreover, both SN Requiem and SN Encore are Type Ia SNe (SNe Ia), making this the most distant case of a galaxy hosting two SNe Ia. Using parametric host fitting, we determine the probability of detecting two SNe Ia in this host galaxy over a ∼10 yr window to be ≈3%. These observations have the potential to yield a Hubble constant ( H _0 ) measurement with ∼10% precision, only the third lensed SN capable of such a result, using the three visible images of the SN. Both SN Requiem and SN Encore have a fourth image that is expected to appear within a few years of ∼2030, providing an unprecedented baseline for time-delay cosmography.

Supernova (SN) SN H0pe is a gravitationally lensed, triply imaged, Type Ia SN (SN Ia) discovered in James Webb Space Telescope imaging of the PLCK G165.7+67.0 cluster of galaxies. Well-observed multiply imaged SNe provide a rare opportunity to constrain the Hubble constant ( H _0 ), by measuring the relative time delay between the images and modeling the foreground mass distribution. SN H0pe is located at z = 1.783 and is the first SN Ia with sufficient light-curve sampling and long enough time delays for an H _0 inference. Here we present photometric time-delay measurements and SN properties of SN H0pe. Using JWST/NIRCam photometry, we measure time delays of Δ t _ab = $-{116.6}_{-9.3}^{+10.8}$ observer-frame days and Δ t _cb = $-{48.6}_{-4.0}^{+3.6}$ observer-frame days relative to the last image to arrive (image 2b; all uncertainties are 1 σ ), which corresponds to a ∼5.6% uncertainty contribution for H _0 assuming 70 km s ^−1 Mpc ^−1 . We also constrain the absolute magnification of each image to μ _a = ${4.3}_{-1.8}^{+1.6}$ , μ _b = ${7.6}_{-2.6}^{+3.6}$ , μ _c = ${6.4}_{-1.5}^{+1.6}$ by comparing the observed peak near-IR magnitude of SN H0pe to the nonlensed population of SNe Ia.

The James Webb Space Telescope (JWST) North Ecliptic Pole (NEP) Time-domain Field (TDF) is a >14′ diameter field optimized for multiwavelength time-domain science with JWST. It has been observed across the electromagnetic spectrum both from the ground and from space, including with the Hubble Space Telescope (HST). As part of HST observations over three cycles (the “TREASUREHUNT” program), deep images were obtained with the Wide Field Camera on the Advanced Camera for Surveys in F435W and F606W that cover almost the entire JWST NEP TDF. Many of the individual pointings of these programs partially overlap, allowing an initial assessment of the potential of this field for time-domain science with HST and JWST. The cumulative area of overlapping pointings is ∼88 arcmin ^2 , with time intervals between individual epochs that range between 1 day and 4+ yr. To a depth of m _AB ≃ 29.5 mag (F606W), we present the discovery of 12 transients and 190 variable candidates. For the variable candidates, we demonstrate that Gaussian statistics are applicable and estimate that ∼80 are false positives. The majority of the transients will be supernovae, although at least two are likely quasars. Most variable candidates are active galactic nuclei (AGNs), where we find 0.42% of the general z ≲ 6 field galaxy population to vary at the ∼3 σ level. Based on a 5 yr time frame, this translates into a random supernova areal density of up to ∼0.07 transients arcmin ^−2 (∼245 deg ^−2 ) per epoch and a variable AGN areal density of ∼1.25 variables arcmin ^−2 (∼4500 deg ^−2 ) to these depths.

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 Ca ii H and K, Ca ii near-infrared triplet, and Si ii equivalent widths for SNe in low-mass host galaxies at 2.2–2.7 σ significance; 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.

Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low- z or poorly calibrated U -band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U -band data, and can be shifted by ∼5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low- z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data—the resulting w measurement can be biased by ∼2% if the color distribution is not sufficiently wide. Future low- z data, particularly u -band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

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 ( http://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 ${\theta }_{{\rm{E}}}=({0.168}_{-0.005}^{+0.009})^{\prime\prime} $ , 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 $\sim {1.7}_{-0.6}^{+0.8}$ mag and $\sim {0.9}_{-0.6}^{+0.8}$ mag for two of the four images, suggesting significant microlensing and/or additional substructure beyond the flexibility of our image-position mass models.

We present the Young Supernova Experiment Data Release 1 (YSE DR1), comprised of processed multicolor PanSTARRS1 griz and Zwicky Transient Facility (ZTF) gr photometry of 1975 transients with host–galaxy associations, redshifts, spectroscopic and/or photometric classifications, and additional data products from 2019 November 24 to 2021 December 20. YSE DR1 spans discoveries and observations from young and fast-rising supernovae (SNe) to transients that persist for over a year, with a redshift distribution reaching z ≈ 0.5. We present relative SN rates from YSE’s magnitude- and volume-limited surveys, which are consistent with previously published values within estimated uncertainties for untargeted surveys. We combine YSE and ZTF data, and create multisurvey SN simulations to train the ParSNIP and SuperRAENN photometric classification algorithms; when validating our ParSNIP classifier on 472 spectroscopically classified YSE DR1 SNe, we achieve 82% accuracy across three SN classes (SNe Ia, II, Ib/Ic) and 90% accuracy across two SN classes (SNe Ia, core-collapse SNe). Our classifier performs particularly well on SNe Ia, with high (>90%) individual completeness and purity, which will help build an anchor photometric SNe Ia sample for cosmology. We then use our photometric classifier to characterize our photometric sample of 1483 SNe, labeling 1048 (∼71%) SNe Ia, 339 (∼23%) SNe II, and 96 (∼6%) SNe Ib/Ic. YSE DR1 provides a training ground for building discovery, anomaly detection, and classification algorithms, performing cosmological analyses, understanding the nature of red and rare transients, exploring tidal disruption events and nuclear variability, and preparing for the forthcoming Vera C. Rubin Observatory Legacy Survey of Space and Time.

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 and the Wide-Field Infrared Survey Telescope. 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 users to generate their own extrapolated SEDs. [ABSTRACT FROM AUTHOR]