We present a comprehensive statistical analysis of the properties of Type Ia SN light curves in the near infrared using recent data from PAIRITEL and the literature. We construct a hierarchical Bayesian framework, incorporating several uncertainties
including photometric error, peculiar velocities, dust extinction and intrinsic variations, for coherent statistical inference. SN Ia light curve inferences are drawn from the global posterior probability of parameters describing both individual supernovae and the population conditioned on the entire SN Ia NIR dataset. The logical structure of the hierarchical model is represented by a directed acyclic graph. Fully Bayesian analysis of the model and data is enabled by an efficient MCMC algorithm exploiting the conditional structure using Gibbs sampling. We apply this framework to the JHK_s SN Ia light curve data. A new light curve model captures the observed J-band light curve shape variations. The intrinsic variances in peak absolute magnitudes are: sigma(M_J) = 0.17 +/- 0.03, sigma(M_H) = 0.11 +/- 0.03, and sigma(M_Ks) = 0.19 +/- 0.04. We describe the first quantitative evidence for correlations between the NIR absolute magnitudes and J-band light curve shapes, and demonstrate their utility for distance estimation. The average residual in the Hubble diagram for the training set SN at cz > 2000 km/s is 0.10 mag. The new application of bootstrap cross-validation to SN Ia light curve inference tests the sensitivity of the model fit to the finite sample and estimates the prediction error at 0.15 mag. These results demonstrate that SN Ia NIR light curves are as effective as optical light curves, and, because they are less vulnerable to dust absorption, they have great potential as precise and accurate cosmological distance indicators.
The core of scientific research is turning new ideas into reality. From the school science fair to the search for the secrets of dark energy, high-quality research consists of scientific investigation constrained within the scope of a well-defined pr
oject. Large or small, generously funded or just scraping by,scientific projects use time, money, and information to turn ideas into plans, plans into action, and action into results. While we, as a community, do much to educate students in the techniques of research, we do not systematically train students in the nature and organization of scientific projects or in the techniques of project management. We propose a two-pronged attack to address this issue in the next decade. First, to generate a broad base of future scientists who have a basic familiarity with the ideas of projects, we propose that the community develop standards for the content of a project design and management course in astronomy and astrophysics. Second, to train future scientists to assume leadership roles in new investigations in astronomy and astrophysics, we propose that the community develop standards for graduate programs in the area of research project leadership.
We have obtained 1087 NIR (JHKs) measurements of 21 SNe Ia using PAIRITEL, nearly doubling the number of well-sampled NIR SN Ia light curves. These data strengthen the evidence that SNe Ia are excellent standard candles in the NIR, even without corre
ction for optical light-curve shape. We construct fiducial NIR templates for normal SNe Ia from our sample, excluding only the three known peculiar SNe Ia: SN 2005bl, SN 2005hk, and SN 2005ke. The H-band absolute magnitudes in this sample of 18 SNe Ia have an intrinsic rms of only 0.15 mag with no correction for light-curve shape. We found a relationship between the H-band extinction and optical color excess of AH=0.2E(B-V). This variation is as small as the scatter in distance modulus measurements currently used for cosmology based on optical light curves after corrections for light-curve shape. Combining the homogeneous PAIRITEL measurements with 23 SNe Ia from the literature, these 41 SNe Ia have standard H-band magnitudes with an rms scatter of 0.16 mag. The good match of our sample with the literature sample suggests there are few systematic problems with the photometry. We present a nearby NIR Hubble diagram that shows no correlation of the residuals from the Hubble line with light-curve properties. Future samples that account for optical and NIR light-curve shapes, absorption, spectroscopic variation, or host-galaxy properties may reveal effective ways to improve the use of SNe Ia as distance indicators. Since systematic errors due to dust absorption in optical bands remain the leading difficulty in the cosmological use of supernovae, the good behavior of SN Ia NIR light curves and their relative insensitivity to reddening make these objects attractive candidates for future cosmological work.
We combine the CfA3 supernova Type Ia (SN Ia) sample with samples from the literature to calculate improved constraints on the dark energy equation of state parameter, w. The CfA3 sample is added to the Union set of Kowalski et al. (2008) to form the
Constitution set and, combined with a BAO prior, produces 1+w=0.013 +0.066/-0.068 (0.11 syst), consistent with the cosmological constant. The CfA3 addition makes the cosmologically-useful sample of nearby SN Ia between 2.6 and 2.9 times larger than before, reducing the statistical uncertainty to the point where systematics play the largest role. We use four light curve fitters to test for systematic differences: SALT, SALT2, MLCS2k2 (R_V=3.1), and MLCS2k2 (R_V=1.7). SALT produces high-redshift Hubble residuals with systematic trends versus color and larger scatter than MLCS2k2. MLCS2k2 overestimates the intrinsic luminosity of SN Ia with 0.7 < Delta < 1.2. MLCS2k2 with R_V=3.1 overestimates host-galaxy extinction while R_V=1.7 does not. Our investigation is consistent with no Hubble bubble. We also find that, after light-curve correction, SN Ia in Scd/Sd/Irr hosts are intrinsically fainter than those in E/S0 hosts by 2 sigma, suggesting that they may come from different populations. We also find that SN Ia in Scd/Sd/Irr hosts have low scatter (0.1 mag) and reddening. Current systematic errors can be reduced by improving SN Ia photometric accuracy, by including the CfA3 sample to retrain light-curve fitters, by combining optical SN Ia photometry with near-infrared photometry to understand host-galaxy extinction, and by determining if different environments give rise to different intrinsic SN Ia luminosity after correction for light-curve shape and color.
