TYPE Ia SUPERNOVA LIGHT CURVE INFERENCE: HIERARCHICAL MODELS IN THE OPTICAL AND NEAR-INFRARED

By Kaisey S. Mandel, G. Narayan, R. Kirshner. 2010

142 citations recorded by the source corpus.

We have constructed a comprehensive statistical model for Type Ia supernova (SN Ia) light curves spanning optical through near-infrared (NIR) data. A hierarchical framework coherently models multiple random and uncertain effects, including intrinsic supernova (SN) light curve covariances, dust extinction and reddening, and distances. An improved BayeSN Markov Chain Monte Carlo code computes probabilistic inferences for the hierarchical model by sampling the global probability density of parameters describing individual SNe and the population. We have applied this hierarchical model to optical and NIR data of 127 SNe Ia from PAIRITEL, CfA3, Carnegie Supernova Project, and the literature. We find an apparent population correlation between the host galaxy extinction AV and the ratio of total-to-selective dust absorption RV. For SNe with low dust extinction, AV ≲ 0.4, we find RV ≈ 2.5–2.9, while at high extinctions, AV ≳ 1, low values of RV < 2 are favored. The NIR luminosities are excellent standard candles and are less sensitive to dust extinction. They exhibit low correlation with optical peak luminosities, and thus provide independent information on distances. The combination of NIR and optical data constrains the dust extinction and improves the predictive precision of individual SN Ia distances by about 60%. Using cross-validation, we estimate an rms distance modulus prediction error of 0.11 mag for SNe with optical and NIR data versus 0.15 mag for SNe with optical data alone. Continued study of SNe Ia in the NIR is important for improving their utility as precise and accurate cosmological distance indicators.

Subfields: Astronomy and Astrophysics, Electrical and Electronic Engineering, Instrumentation

View Paper: https://www.semanticscholar.org/paper/38bad1e5b9c79f967d75b1d9704927a8f69a2176

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Astronomy and Astrophysics

1. A. Riess
2. A. Filippenko
3. S. Jha
4. R. Kirshner
5. Weidong Li
6. Ryan Chornock
7. S. Smartt
8. N. Smith

In Electrical and Electronic Engineering

1. A. Riess
2. S. Jha
3. Daniel J. Eisenstein
4. B. Leibundgut
5. S. Dhawan
6. Maya Fishbach
7. D. Holz
8. B. Farr

In Instrumentation

1. A. Riess
2. A. Filippenko
3. B. Leibundgut
4. Weidong Li
5. S. Jha
6. Daniel J. Eisenstein
7. N. Smith
8. Ryan Chornock

Citations in the corpus

• Observational probes of cosmic acceleration (2012, methodology): “Bayesian fitting methods (e.g., Mandel et al. 2009, 2011; March et al. 2011) can in principle incorporate a wide variety of parameterized relationships with explicit priors, including dependences on redshift or host galaxy parameters, which are then marginalized over in cosmological fits.”
• THE SPECTROSCOPIC DIVERSITY OF TYPE Ia SUPERNOVAE (2000, methodology): “A key difference in our approach is the use of intrinsic color estimates inferred from the BayeSN statistical model for SN Ia light curves (Mandel et al. 2011), which allows for variations in the host-galaxy dust properties on a SNby-SN basis, as opposed to assuming a single reddening law for all…”
• COSMOLOGICAL CONSTRAINTS FROM MEASUREMENTS OF TYPE Ia SUPERNOVAE DISCOVERED DURING THE FIRST 1.5 yr OF THE Pan-STARRS1 SURVEY (2013, background): “Since then, new approaches and new algorithms have improved lightcurve fitting so that well-observed SN Ia have individual luminosity distances good to 5% (e.g., MLCS2K2, Jha et al. 2007; Stretch, Goldhaber et al. 2001; SALT, Guy et al. 2007; SiFTO, Conley et al. (2008); and BayeSN, Mandel et al. 20”
• REDDENING AND EXTINCTION TOWARD THE GALACTIC BULGE FROM OGLE-III: THE INNER MILKY WAY'S RV ∼ 2.5 EXTINCTION CURVE (2012, methodology): “We note that studies of the extinction in the hosts of type Ia SNe routinely find an RV ≈ 2.5 extinction curve (Guy et al. 2010; Chotard et al. 2011; Mandel et al. 2011), and then subsequently assume the functional dependence on wavelength calibrated in investigations of Milky Way extinction.”
• ON THE SOURCE OF THE DUST EXTINCTION IN TYPE Ia SUPERNOVAE AND THE DISCOVERY OF ANOMALOUSLY STRONG Na i ABSORPTION (2013, unknown): “…for individual SNe Ia indicate that while most heavily-reddened events have RV < 2, the color excesses of many SNe Ia with E(B − V ) < 0.3 are consistent with the standard Galactic value of RV ∼ 3 (Folatelli et al. 2010; Mandel et al. 2011; Phillips 2012; C. Burns et al. 2013, in preparation).”
• Are LIGO's Black Holes Made from Smaller Black Holes? (2017, methodology): “Mixture Model Analysis We apply a hierarchical Bayesian framework (Hogg et al. 2010; Mandel et al. 2011) to analyze a collection of BH spin measurements, where the spin measurement from the ith GW detection takes the form of a two-dimensional posterior for the BBH spin magnitudes p(αi|di), where αi…”
• Measuring the Hubble constant with Type Ia supernovae as near-infrared standard candles (2017, methodology): “Our choice is plausible (Radburn-Smith et al. 2004; Turnbull et al. 2012; Feindt et al. 2013) and previous studies have also used this value for the peculiar velocity uncertainty (Mandel et al. 2009, 2011; Barone-Nugent et al. 2012).”
• The Carnegie Supernova Project. I. Third Photometry Data Release of Low-redshift Type Ia Supernovae and Other White Dwarf Explosions (2017, background): “The combination of optical and NIR photometry also provides invaluable information on the shape of the hostgalaxy dust reddening curve (Folatelli et al. 2010; Mandel et al. 2011; Burns et al. 2014).”
• CfA4: LIGHT CURVES FOR 94 TYPE Ia SUPERNOVAE (2012, methodology): “The current state of the art uses a statistical model for light-curve shapes that predicts distances to 7% for well-observed SNe Ia using optical data and 5% when NIR photometry is added (Mandel et al. 2011).”
• The Complete Light-curve Sample of Spectroscopically Confirmed SNe Ia from Pan-STARRS1 and Cosmological Constraints from the Combined Pantheon Sample (2017, methodology): “While multiple light-curve fitters can be used to determine accurate distances (e.g., Jha et al. 2007; Guy et al. 2010; Burns et al. 2011; Mandel et al. 2011), we use SALT2 (Guy et al. 2010) for this analysis, as it has been trained on the JLA sample (B14) and it is easy to assess various…”