First-Year Spectroscopy for the Sloan Digital Sky Survey-Ii Supernova Survey

Zheng, C.; Romani, Roger W.; Šako, M.; Marriner, J.; Bassett, Bruce A.; Becker, A. C.; Choi, Changsu; Cinabro, D.; DeJongh, F.; DePoy, D. L.; Dilday, Benjamin; Doi, Mamoru; Frieman, Joshua A.; Garnavich, P.; Hogan, Craig J.; Holtzman, Jon A.; Im, Myungshin; Jha, Saurabh W.; Keßler, R.; Konishi, K.; Lampeitl, H.; Marshall, J. L.; McGinnis, David; Miknaitis, G.; Nichol, R. C.; Prieto, J. L.; Riess, Adam G.; Richmond, M.; Schneider, Donald P.; Smith, M.; Takanashi, N.; Tokita, K.; Heyden, K. J. van der; Yasuda, Naoki; Assef, Roberto J.; Barentine, John C.; Bender, Ralf; Blandford, R. D.; Bremer, M. N.; Brewington, H.; Collins, Chris; Crotts, Arlin; Dembicky, J.; Eastman, Jason D.; Edge, A. C.; Elson, Edward C.; Eyler, Michael E.; Filippenko, A. V.; Foley, R. J.; Stephan, F.; Goobar, A.; Harvanek, Michael; Hopp, U.; Ihara, Y.; Kahn, S. M.; Ketzeback, William; Kleinman, S. J.; Kollatschny, W.; Krzesiński, Jurek; Leloudas, G.; Long, Daniel C.; Lucey, J. R.; Malanushenko, Elena; Malanushenko, Viktor; McMillan, R.; Morgan, Christopher W.; Morokuma, Tomoki; Nitta, A.; Östman, L.; Pan, Kaike; Romer, A. K.; Saurage, Gabrelle; Schlesinger, Katharine J.; Snedden, Stephanie A.; Sollerman, J.; Stritzinger, M. D.; Watson, Linda C.; Watters, S.; Wheeler, J. C.; York, Donald G.

doi:10.1088/0004-6256/135/5/1766

Cited by 58 publications

(62 citation statements)

References 76 publications

(52 reference statements)

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“…We find 86 SN Ia (of which two are SN Ia_pec) and 38 SN Ia in our VLT sample, that is ∼30% of SN Ia . Other surveys such as SDSS-II (Zheng et al 2008) and ESSENCE (Matheson et al 2005) both find about 10% of probable SN Ia (equivalent to our SN Ia ). The SDSS-II survey targets low to intermediate redshifts (0.05 < z < 0.4, z ≈ 0.22), which probably makes identification easier.…”

Section: Discussionsupporting

confidence: 65%

“…In recent years, various large-scale SN programs have published sets of SN Ia spectra at intermediate (Balland et al 2006(Balland et al , 2007Zheng et al 2008;Foley et al 2008b) and distant Lidman et al 2005;Matheson et al 2008;Bronder et al 2008;Ellis et al 2008;Foley et al 2008a) redshifts. The SNLS VLT SN Ia spectral data set presented in this paper supplements these existing sets with 124 new SNe Ia, or probable SNe Ia.…”

Section: Discussionmentioning

confidence: 99%

“…Blondin et al (2005) proposed a PSF deconvolution technique that separates the two components, provided that the spatial extension of the Gaussian profile is very different for the SN and for its host. Zheng et al (2008) use a principal component analysis decomposition, combined with template fitting to assess the level of host contamination.…”

Section: Host Galaxy Subtractionmentioning

confidence: 99%

“…We do not add emission lines to the PEGASE templates: whenever PEGASE templates are used to model the host contribution, residual emission lines might be found in the host subtracted spectrum. This technique is then essentially comparable to the PCA+χ 2 fitting technique used by Zheng et al (2008) to evaluate the host contamination in the first season of the SDSS-II survey.…”

Section: Host Galaxy Subtractionmentioning

confidence: 99%

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The ESO/VLT 3rd year Type Ia supernova data set from the supernova legacy survey

Balland

Baumont²,

Basa

et al. 2009

A&A

104

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Aims. We present 139 spectra of 124 Type Ia supernovae (SNe Ia) that were observed at the ESO/VLT during the first three years of the Canada-France-Hawaï Telescope (CFHT) supernova legacy survey (SNLS). This homogeneous data set is used to test for redshift evolution of SN Ia spectra, and will be used in the SNLS 3rd year cosmological analyses. Methods. Spectra have been reduced and extracted with a dedicated pipeline that uses photometric information from deep CFHT legacy survey (CFHT-LS) reference images to trace, at sub-pixel accuracy, the position of the supernova on the spectrogram as a function of wavelength. It also separates the supernova and its host light in ∼60% of cases. The identification of the supernova candidates is performed using a spectrophotometric SN Ia model. Results. A total of 124 SNe Ia, roughly 50% of the overall SNLS spectroscopic sample, have been identified using the ESO/VLT during the first three years of the survey. Their redshifts range from z = 0.149 to z = 1.031. The average redshift of the sample is z = 0.63 ± 0.02. This constitutes the largest SN Ia spectral set to date in this redshift range. The spectra are presented along with their best-fit spectral SN Ia model and a host model where relevant. In the latter case, a host subtracted spectrum is also presented. We produce average spectra for pre-maximum, maximum and post-maximum epochs for both z < 0.5 and z ≥ 0.5 SNe Ia. We find that z < 0.5 spectra have deeper intermediate mass element absorptions than z ≥ 0.5 spectra. The differences with redshift are consistent with the selection of brighter and bluer supernovae at higher redshift.

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Section: Discussionsupporting

confidence: 65%

Section: Discussionmentioning

confidence: 99%

Section: Host Galaxy Subtractionmentioning

confidence: 99%

Section: Host Galaxy Subtractionmentioning

confidence: 99%

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The ESO/VLT 3rd year Type Ia supernova data set from the supernova legacy survey

Balland

Baumont²,

Basa

et al. 2009

A&A

104

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show abstract

“…The photometrically probable SNe Ia are identified as SNe Ia based on luminosity, colour, and light curve shapes (see details in Sako et al 2008). We do not include known peculiar SNe Ia classified by Zheng et al (2008) in the sample (SN2005js, SN2005gj, SDSS-SN7017, and SN2005hk are excluded). We do not use the SNe Ia whose photometry is not based upon the SDSS calibration stars in the same frame in order to avoid photometric systematic uncertainty.…”

Section: Photometric Datamentioning

confidence: 99%

Photometric properties of intermediate-redshift Type Ia supernovae observed by the Sloan Digital Sky Survey-II Supernova Survey

Doi¹,

Yasuda²,

Kuncarayakti³

et al. 2016

Mon. Not. R. Astron. Soc.

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We have analyzed multi-band light curves of 328 intermediate redshift (0.05 ≤ z < 0.24) type Ia supernovae (SNe Ia) observed by the Sloan Digital Sky Survey-II Supernova Survey (SDSS-II SN Survey). The multi-band light curves were parameterized by using the Multi-band Stretch Method, which can simply parameterize light curve shapes and peak brightness without dust extinction models. We found that most of the SNe Ia which appeared in red host galaxies (u − r > 2.5) don't have a broad light curve width and the SNe Ia which appeared in blue host galaxies (u − r < 2.0) have a variety of light curve widths. The Kolmogorov-Smirnov test shows that the colour distribution of SNe Ia appeared in red / blue host galaxies is different (significance level of 99.9%). We also investigate the extinction law of host galaxy dust. As a result, we find the value of R v derived from SNe Ia with medium light curve width is consistent with the standard Galactic value. On the other hand, the value of R v derived from SNe Ia that appeared in red host galaxies becomes significantly smaller. These results indicate that there may be two types of SNe Ia with different intrinsic colours, and they are obscured by host galaxy dust with two different properties.

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A method of searching for supernova candidates from massive galaxy spectra

Luo

et al. 2010

Sci. China Phys. Mech. Astron.

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First-Year Spectroscopy for the Sloan Digital Sky Survey-Ii Supernova Survey

Cited by 58 publications

References 76 publications

The ESO/VLT 3rd year Type Ia supernova data set from the supernova legacy survey

The ESO/VLT 3rd year Type Ia supernova data set from the supernova legacy survey

Photometric properties of intermediate-redshift Type Ia supernovae observed by the Sloan Digital Sky Survey-II Supernova Survey

A method of searching for supernova candidates from massive galaxy spectra

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