SALT2: using distant supernovae to improve the use of type Ia supernovae as distance indicators

By J. Guy, P. Astier, S. Baumont, D. Hardin, R. Pain, N. Regnault, S. Basa, R. Carlberg, A. Conley, S. Fabbro and 15 more. 2007

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We present an empirical model of Type Ia supernovae spectro-photometric evolution with time. The model is built using a large data set including light-curves and spectra of both nearby and distant supernovae, the latter being observed by the SNLS collaboration. We derive the average spectral sequence of Type Ia supernovae and their main variability components including a color variation law. The model allows us to measure distance moduli in the spectral range 2500-8000 A with calculable uncertainties, including those arising from variability of spectral features. Thanks to the use of high-redshift SNe to model the rest-frame UV spectral energy distribution, we are able to derive improved distance estimates for SNe Ia in the redshift range 0.8

Subfields: Astronomy and Astrophysics, Nuclear and High Energy Physics

View Paper: https://www.semanticscholar.org/paper/301eb1c83dcf4e3ca2fab9731c9ee09746c5b4ca

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Citations in the corpus

THE SPECTROSCOPIC DIVERSITY OF TYPE Ia SUPERNOVAE (2000, methodology): “Since the SALT2 color parameter does not distinguish between intrinsic color and extinction by dust, we re-ran this analysis using the intrinsic B−V color at B-band maximum and ∆m15(B) values from BayeSN.”
The dependence of Type Ia Supernovae luminosities on their host galaxies (2010, background): “Explicitly, MB = MB+5 log10(c/H0)+25, where MB is the absolute magnitude of a SN Ia in the B-band (for SALT2 fits, MB refers to an x1 = 0, C = 0 event).”
FIRST-YEAR SLOAN DIGITAL SKY SURVEY-II (SDSS-II) SUPERNOVA RESULTS: CONSTRAINTS ON NONSTANDARD COSMOLOGICAL MODELS (2009, methodology): “A similar intrinsic dispersion (we use 0.14 mag) gives a χ2d.o.f.=1 for the global SALTII fit.”
THE HUBBLE SPACE TELESCOPE CLUSTER SUPERNOVA SURVEY. V. IMPROVING THE DARK-ENERGY CONSTRAINTS ABOVE z > 1 AND BUILDING AN EARLY-TYPE-HOSTED SUPERNOVA SAMPLE (2011, methodology): “We then run SALT2 using the counts in a fixed aperture, the modified filter response and the adjusted zeropoint.”
SUPERNOVA SIMULATIONS AND STRATEGIES FOR THE DARK ENERGY SURVEY (2011, methodology): “In this work, we use the optical (λ < 1 µm) MLCS2k2 (Jha et al. 2007) and SALT2 (Guy et al. 2007) models and the optical+infrared SNooPy model (Burns et al. 2011).”
COSMOLOGICAL CONSTRAINTS FROM MEASUREMENTS OF TYPE Ia SUPERNOVAE DISCOVERED DURING THE FIRST 1.5 yr OF THE Pan-STARRS1 SURVEY (2013, methodology): “…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. 2009, 2011).”
CfA4: LIGHT CURVES FOR 94 TYPE Ia SUPERNOVAE (2012, background): “SALT2 (Guy et al. 2007) and SiFTO (Conley et al. 2008) are other popular light-curve fitters.”
TYPE Ia SUPERNOVA LIGHT CURVE INFERENCE: HIERARCHICAL MODELS IN THE OPTICAL AND NEAR-INFRARED (2010, methodology): “Methods include Δm15(B) (Phillips 1993; Hamuy et al. 1996b; Phillips et al. 1999; Prieto et al. 2006), multicolor light curve shapes (MLCS; Riess et al. 1996a, 1998; Jha et al. 2007), “stretch” (Goldhaber et al. 2001), CMAGIC (Wang et al. 2003), SALT (Guy et al. 2005, 2007), and SiFTO (Conley et al.”
CONFIRMATION OF A STAR FORMATION BIAS IN TYPE Ia SUPERNOVA DISTANCES AND ITS EFFECT ON THE MEASUREMENT OF THE HUBBLE CONSTANT (2014, methodology): “The result using MLCS2k2 strongly favors the R13 bimodal model, but the evidence for bimodality using the H09 SALT2 Hubble residuals is weaker than found in R13.”
CfA3: 185 TYPE Ia SUPERNOVA LIGHT CURVES FROM THE CfA (2009, background): “The other fitters, SALT2 (Guy et al. 2007), MLCS2k2 (Jha et al. 2007) with RV = 3.1 and MLCS2k2 with RV = 1.7 were found to reduce the statistical uncertainty by a factor of ∼ 1.2–1.3, slightly less than the rough statistical expectation.”
The Carnegie Supernova Project: Absolute Calibration and the Hubble Constant (2018, background): “However, the assumption of constant RV (also labeled β in other analyses (e.g. Guy et al. 2007)) is demonstrably not correct in our own MilkyWay galaxy (Cardelli et al. 1989; Fitzpatrick 1999; Nataf 2015), as well as in the host galaxies of SNe Ia (Riess et al. 1996; Mandel et al. 2011; Burns et…”
SNLS3: CONSTRAINTS ON DARK ENERGY COMBINING THE SUPERNOVA LEGACY SURVEY THREE-YEAR DATA WITH OTHER PROBES (2011, methodology): “0.06 SNe Ia for the training, and therefore cannot be supplemented with SNLS/SDSS SN data sampling the rest-frame U -band as is the case with SALT2 and SiFTO.”
IMPROVED DARK ENERGY CONSTRAINTS FROM ∼100 NEW CfA SUPERNOVA TYPE Ia LIGHT CURVES (2009, methodology): “…candles and the most useful distance indicators at cosmological scales (e.g., Phillips 1993; Hamuy et al. 1996a; Riess, Press, & Kirshner 1996; Perlmutter et al. 1997; Jha et al. 1999; Goldhaber et al. 2001; Guy et al. 2005; Jha, Riess, & Kirshner 2007; Guy et al. 2007; Conley et al. 2008).”
SiFTO: An Empirical Method for Fitting SN Ia Light Curves (2008, neutral): “…2007), stretch (Perlmutter et al. 1997; Goldhaber et al. 2001; Knop et al. 2003), super stretch (Wang et al. 2006), ∆m15 (Hamuy et al. 1996b; Prieto, Rest, & Suntzeff 2006), BATM (Tonry et al. 2003), CMAGIC (Wang et al. 2003), SALT (Guy et al. 2005), and SALT2 (Guy et al. 2007, hereafter G07).”
THE CARNEGIE SUPERNOVA PROJECT: LIGHT-CURVE FITTING WITH SNooPy (2010, methodology): “…in the literature all use different parameters to describe the shape: MLCS2k2 uses a luminosity parameter ∆ (Riess et al. 1996; Jha et al. 2007), while SALT2 uses a stretchlike parameter x1 to describe a sequence of SEDs of SN Ia further modified by a color-like parameter c (Guy et al. 2007).”
Clarifying the Hubble constant tension with a Bayesian hierarchical model of the local distance ladder (2017, methodology): “The final simulated SN catalogue is produced by generating correlated Gaussian uncertainties on the SN apparent magnitudes, colours and stretches using the average correlations of the R16 SN dataset, mimicking the effects of estimating these parameters from SN lightcurves with using SALT-2 (Guy et a”