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Register a new userGemini Spectroscopy of Supernovae from SNLS: Improving High Redshift SN Selection and Classification
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We present new techiques for improving the efficiency of supernova (SN) classification at high redshift using 64 candidates observed at Gemini North and South during the first year of the Supernova Legacy Survey (SNLS). The SNLS is an ongoing five year project with the goal of measuring the equation of state of Dark Energy by discovering and following over 700 high-redshift SNe Ia using data from the Canada-France-Hawaii Telescope Legacy Survey. We achieve an improvement in the SN Ia spectroscopic confirmation rate: at Gemini 71% of candidates are now confirmed as SNe Ia, compared to 54% using the methods of previous surveys. This is despite the comparatively high redshift of this sample, where the median SN Ia redshift is z=0.81 (0.155 <= z <= 1.01). These improvements were realized because we use the unprecedented color coverage and lightcurve sampling of the SNLS to predict whether a candidate is an SN Ia and estimate its redshift, before obtaining a spectrum, using a new technique called the SN photo-z. In addition, we have improved techniques for galaxy subtraction and SN template chi^2 fitting, allowing us to identify candidates even when they are only 15% as bright as the host galaxy. The largest impediment to SN identification is found to be host galaxy contamination of the spectrum -- when the SN was at least as bright as the underlying host galaxy the target was identified more than 90% of the time. However, even SNe on bright host galaxies can be easily identified in good seeing conditions. When the image quality was better than 0.55 arcsec the candidate was identified 88% of the time. Over the five-year course of the survey, using the selection techniques presented here we will be able to add approximately 170 more confirmed SNe Ia than would be possible using previous methods.
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The Supernova Legacy Survey (SNLS; http://cfht.hawaii.edu/SNLS) will discover and obtain griz lightcurves for more than 700 spectroscopically confirmed SNe Ia (0.3<z<0.9) to differentiate between competing models for Dark Energy. We fit the multicolor lightcurves of the candidates to determine which are likely SNe Ia and send them for follow-up spectroscopy to the Keck, VLT, and Gemini telescopes. Here we show the results from Gemini, where we send most of our highest redshift (0.6<z<0.9) targets.
Aims: We present a quantitative study of a new data set of high redshift Type Ia supernovae spectra, observed at the Gemini telescopes during the first 34 months of the Supernova Legacy Survey. During this time 123 supernovae candidates were observed, of which 87 have been identified as SNe Ia at a median redshift of z=0.720. Spectra from the entire second year of the survey and part of the third year (59 total SNe candidates with 46 confirmed SNe Ia) are published here for the first time. The spectroscopic measurements made on this data set are used determine if these distant SNe comprise a population similar to those observed locally. Methods: Rest-frame equivalent width and ejection velocity measurements are made on four spectroscopic features. Corresponding measurements are presented for a set of 167 spectra from 24 low-z SNe Ia from the literature. Results: We show that there exists a sample at high redshift with properties similar to nearby SNe. No significant difference was found between the distributions of measurements at low and high redsift for three of the features. The fourth feature displays a possible difference that should be investigated further. Correlations between Type Ia SNe properties and host galaxy morphology were also found to be similar at low and high z, and within each host galaxy class we see no evidence for redshift-evolution in SN properties. A new correlation between SNe Ia peak magnitude and the equivalent width of SiII absorption is presented. We demonstrate that this correlation reduces the scatter in SNe Ia luminosity distances in a manner consistent with the lightcurve shape-luminosity corrections that are used for Type Ia SNe cosmology. Conclusions: We show that this new sample of SNLS SNe Ia has spectroscopic properties similar to nearby objects. (Abridged)
Aims. We investigate the degree of improvement in dark energy constraints that can be achieved by extending Type Ia Supernova (SN Ia) samples to redshifts z > 1.5 with the Hubble Space Telescope (HST), particularly in the ongoing CANDELS and CLASH multi-cycle treasury programs. Methods. Using the popular CPL parametrization of the dark energy, w = w0 +wa(1-a), we generate mock SN Ia samples that can be projected out to higher redshifts. The synthetic datasets thus generated are fitted to the CPL model, and we evaluate the improvement that a high-z sample can add in terms of ameliorating the statistical and systematic uncertainties on cosmological parameters. Results. In an optimistic but still very achievable scenario, we find that extending the HST sample beyond CANDELS+CLASH to reach a total of 28 SN Ia at z > 1.0 could improve the uncertainty in the wa parameter by up to 21%. The corresponding improvement in the figure of merit (FoM) would be as high as 28%. Finally, we consider the use of high-redshift SN Ia samples to detect non-cosmological evolution in SN Ia luminosities with redshift, finding that such tests could be undertaken by future spacebased infrared surveys using the James Webb Space Telescope (JWST).
We present the results of spectroscopic observations from the ESSENCE high-redshift supernova (SN) survey during its first four years of operation. This sample includes spectra of all SNe Ia whose light curves were presented by Miknaitis et al. (2007) and used in the cosmological analyses of Davis et al. (2007) and Wood-Vasey et al. (2007). The sample represents 273 hours of spectroscopic observations with 6.5 - 10-m-class telescopes of objects detected and selected for spectroscopy by the ESSENCE team. We present 174 spectra of 156 objects. Combining this sample with that of Matheson et al. (2005), we have a total sample of 329 spectra of 274 objects. From this, we are able to spectroscopically classify 118 Type Ia SNe. As the survey has matured, the efficiency of classifying SNe Ia has remained constant while we have observed both higher-redshift SNe Ia and SNe Ia farther from maximum brightness. Examining the subsample of SNe Ia with host-galaxy redshifts shows that redshifts derived from only the SN Ia spectra are consistent with redshifts found from host-galaxy spectra. Moreover, the phases derived from only the SN Ia spectra are consistent with those derived from light-curve fits. By comparing our spectra to local templates, we find that the rate of objects similar to the overluminous SN 1991T and the underluminous SN 1991bg in our sample are consistent with that of the local sample. We do note, however, that we detect no object spectroscopically or photometrically similar to SN 1991bg. Although systematic effects could reduce the high-redshift rate we expect based on the low-redshift surveys, it is possible that SN 1991bg-like SNe Ia are less prevalent at high redshift.
Supernova (SN) classification and redshift estimation using photometric data only have become very important for the Large Synoptic Survey Telescope (LSST), given the large number of SNe that LSST will observe and the impossibility of spectroscopically following up all the SNe. We investigate the performance of a SN classifier that uses SN colors to classify LSST SNe with the Random Forest classification algorithm. Our classifier results in an AUC of 0.98 which represents excellent classification. We are able to obtain a photometric SN sample containing 99$%$ SNe Ia by choosing a probability threshold. We estimate the photometric redshifts (photo-z) of SNe in our sample by fitting the SN light curves using the SALT2 model with nested sampling. We obtain a mean bias ($left<z_mathrm{phot}-z_mathrm{spec}right>$) of 0.012 with $sigmaleft( frac{z_mathrm{phot}-z_mathrm{spec}}{1+z_mathrm{spec}}right) = 0.0294$ without using a host-galaxy photo-z prior, and a mean bias ($left<z_mathrm{phot}-z_mathrm{spec}right>$) of 0.0017 with $sigmaleft( frac{z_mathrm{phot}-z_mathrm{spec}}{1+z_mathrm{spec}}right) = 0.0116$ using a host-galaxy photo-z prior. Assuming a flat $Lambda CDM$ model with $Omega_m=0.3$, we obtain $Omega_m$ of $0.305pm0.008$ (statistical errors only), using the simulated LSST sample of photometric SNe Ia (with intrinsic scatter $sigma_mathrm{int}=0.11$) derived using our methodology without using host-galaxy photo-z prior. Our method will help boost the power of SNe from the LSST as cosmological probes.
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