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 ≲
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Abstract z ≲ 0.6) discovered by Pan-STARRS and the Dark Energy Survey. By comparing higher-z HST data with 42 SNe Ia atz < 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 1.5σ −2.5σ 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 measureH 0= 75.9 ± 2.2 km s−1Mpc−1from stars with geometric distance calibration in the hosts of eight SNe Ia observed in the NIR versusH 0= 71.2 ± 3.8 km s−1Mpc−1using 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 inw 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. -
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 softwareSALTshaker , 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 redshiftz ≲ 0.4 and by ∼50% atz ≲ 0.15. The SALT3-NIR model is part of the open-sourceSNCosmo andSNANA SN Ia cosmology packages.