More Like this

1. Cosmological Results from the RAISIN Survey: Using Type Ia Supernovae in the Near Infrared as a Novel Path to Measure the Dark Energy Equation of State

   https://doi.org/10.3847/1538-4357/ac755b  

   Jones, D. O.; Mandel, K. S.; Kirshner, R. P.; Thorp, S.; Challis, P. M.; Avelino, A.; Brout, D.; Burns, C.; Foley, R. J.; Pan, Y.-C.; et al (July 2022, The Astrophysical Journal)

   Abstract Type Ia supernovae (SNe Ia) are more precise standardizable candles when measured in the near-infrared (NIR) than in the optical. With this motivation, from 2012 to 2017 we embarked on the RAISIN program with the Hubble Space Telescope (HST) to obtain rest-frame NIR light curves for a cosmologically distant sample of 37 SNe Ia (0.2 ≲ z ≲ 0.6) discovered by Pan-STARRS and the Dark Energy Survey. By comparing higher- z HST data with 42 SNe Ia at z < 0.1 observed in the NIR by the Carnegie Supernova Project, we construct a Hubble diagram from NIR observations (with only time of maximum light and some selection cuts from optical photometry) to pursue a unique avenue to constrain the dark energy equation-of-state parameter, w . We analyze the dependence of the full set of Hubble residuals on the SN Ia host galaxy mass and find Hubble residual steps of size ∼0.06-0.1 mag with 1.5 σ −2.5 σ significance depending on the method and step location used. Combining our NIR sample with cosmic microwave background constraints, we find 1 + w = −0.17 ± 0.12 (statistical + systematic errors). The largest systematic errors are the redshift-dependent SN selection biases and the properties of the NIR mass step. We also use these data to measure H 0 = 75.9 ± 2.2 km s −1 Mpc −1 from stars with geometric distance calibration in the hosts of eight SNe Ia observed in the NIR versus H 0 = 71.2 ± 3.8 km s −1 Mpc −1 using an inverse distance ladder approach tied to Planck. Using optical data, we find 1 + w = −0.10 ± 0.09, and with optical and NIR data combined, we find 1 + w = −0.06 ± 0.07; these shifts of up to ∼0.11 in w could point to inconsistency in the optical versus NIR SN models. There will be many opportunities to improve this NIR measurement and better understand systematic uncertainties through larger low- z samples, new light-curve models, calibration improvements, and eventually by building high- z samples from the Roman Space Telescope. 

   more » « less
2. SALT3-NIR: Taking the Open-source Type Ia Supernova Model to Longer Wavelengths for Next-generation Cosmological Measurements

   https://doi.org/10.3847/1538-4357/ac93f9  

   Pierel, J. D.; Jones, D. O.; Kenworthy, W. D.; Dai, M.; Kessler, R.; Ashall, C.; Do, A.; Peterson, E. R.; Shappee, B. J.; Siebert, M. R.; et al (October 2022, The Astrophysical Journal)

   Abstract A large fraction of Type Ia supernova (SN Ia) observations over the next decade will be in the near-infrared (NIR), at wavelengths beyond the reach of the current standard light-curve model for SN Ia cosmology, SALT3 (∼2800–8700 Å central filter wavelength). To harness this new SN Ia sample and reduce future light-curve standardization systematic uncertainties, we train SALT3 at NIR wavelengths (SALT3-NIR) up to 2 μ m with the open-source model-training software SALTshaker , which can easily accommodate future observations. Using simulated data, we show that the training process constrains the NIR model to ∼2%–3% across the phase range (−20 to 50 days). We find that Hubble residual (HR) scatter is smaller using the NIR alone or optical+NIR compared to optical alone, by up to ∼30% depending on filter choice (95% confidence). There is significant correlation between NIR light-curve stretch measurements and luminosity, with stretch and color corrections often improving HR scatter by up to ∼20%. For SN Ia observations expected from the Roman Space Telescope, SALT3-NIR increases the amount of usable data in the SALT framework by ∼20% at redshift z ≲ 0.4 and by ∼50% at z ≲ 0.15. The SALT3-NIR model is part of the open-source SNCosmo and SNANA SN Ia cosmology packages. 

   more » « less
3. The Hourglass Simulation: A Catalog for the Roman High-latitude Time-domain Core Community Survey

   https://doi.org/10.3847/1538-4357/ade1d6  

   Rose, B M; Vincenzi, M; Hounsell, R; Qu, H; Aldoroty, L; Scolnic, D; Kessler, R; Macias, P; Brout, D; Acevedo, M; et al (July 2025, The Astrophysical Journal)

   Abstract We present a simulation of the time-domain catalog for the Nancy Grace Roman Space Telescope’s High-Latitude Time-Domain Core Community Survey. This simulation, called the Hourglass simulation, uses the most up-to-date spectral energy distribution models and rate measurements for 10 extragalactic time-domain sources. We simulate these models through the design reference Roman Space Telescope survey: four filters per tier, a five-day cadence, over 2 yr, a wide tier of 19 deg², and a deep tier of 4.2 deg², with ∼20% of those areas also covered with prism observations. We find that a science-independent Roman time-domain catalog, assuming a signal-to-noise ratio at a max of >5, would have approximately 21,000 Type Ia supernovae, 40,000 core-collapse supernovae, around 70 superluminous supernovae, ∼35 tidal disruption events, three kilonovae, and possibly pair-instability supernovae. In total, Hourglass has over 64,000 transient objects, 11,000,000 photometric observations, and 500,000 spectra. Additionally, Hourglass is a useful data set to train machine learning classification algorithms. We show that SCONE is able to photometrically classify Type Ia supernovae with high precision (∼95%) to az> 2. Finally, we present the first realistic simulations of non-Type Ia supernovae spectral time series data from Roman’s prism. 

   more » « less
4. Hawai‘i Supernova Flows: a peculiar velocity survey using over a Thousand Supernovae in the near-infrared

   https://doi.org/10.1093/mnras/stae2501  

   Do, Aaron; Shappee, Benjamin J; Tonry, John L; Tully, R Brent; de Jaeger, Thomas; Rubin, David; Ashall, Chris; Burns, Christopher R; Desai, Dhvanil D; Hinkle, Jason T; et al (December 2024, Monthly Notices of the Royal Astronomical Society)

   ABSTRACT We introduce the Hawai‘i Supernova Flows project and present summary statistics of the first 1217 astronomical transients observed, 668 of which are spectroscopically classified Type Ia Supernovae (SNe Ia). Our project is designed to obtain systematics-limited distances to SNe Ia while consuming minimal dedicated observational resources. To date, we have performed almost 5000 near-infrared (NIR) observations of astronomical transients and have obtained spectra for over 200 host galaxies lacking published spectroscopic redshifts. In this survey paper, we describe the methodology used to select targets, collect/reduce data, calculate distances, and perform quality cuts. We compare our methods to those used in similar studies, finding general agreement or mild improvement. Our summary statistics include various parametrizations of dispersion in the Hubble diagrams produced using fits to several commonly used SN Ia models. We find the lowest dispersions using the SNooPy package’s EBV_model2, with a root mean square deviation of 0.165 mag and a normalized median absolute deviation of 0.123 mag. The full utility of the Hawai‘i Supernova Flows data set far exceeds the analyses presented in this paper. Our photometry will provide a valuable test bed for models of SN Ia incorporating NIR data. Differential cosmological studies comparing optical samples and combined optical and NIR samples will have increased leverage for constraining chromatic effects like dust extinction. We invite the community to explore our data by making the light curves, fits, and host galaxy redshifts publicly accessible. 

   more » « less
5. The Young Supernova Experiment Data Release 1 (YSE DR1): Light Curves and Photometric Classification of 1975 Supernovae

   https://doi.org/10.3847/1538-4365/acbfba  

   Aleo, P. D.; Malanchev, K.; Sharief, S.; Jones, D. O.; Narayan, G.; Foley, R. J.; Villar, V. A.; Angus, C. R.; Baldassare, V. F.; Bustamante-Rosell, M. J.; et al (May 2023, The Astrophysical Journal Supplement Series)

   Abstract 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. 

   more » « less