SPECTROSCOPIC PROPERTIES OF STAR-FORMING HOST GALAXIES AND TYPE Ia SUPERNOVA HUBBLE RESIDUALS IN A NEARLY UNBIASED SAMPLE

We examine the correlation between supernova (SN) host-galaxy properties and their residuals in the Hubble diagram. We use SNe discovered during the Sloan Digital Sky Survey-II Supernova Survey, and focus on objects at a redshift of z < 0.15, where the selection effects of the survey are known to...

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Bibliographic Details
Published in:The Astrophysical journal Vol. 743; no. 2
Main Authors: D'Andrea, Chris B., Gupta, Ravi R., Sako, Masao, Morris, Matt, Nichol, Robert C., Campbell, Heather, Lampeitl, Hubert, Brown, Peter J., Olmstead, Matthew D., Frieman, Joshua A., Kessler, Richard, Garnavich, Peter, Jha, Saurabh W., Marriner, John, Schneider, Donald P., Smith, Mathew
Format: Journal Article
Language:English
Published: United States 20-12-2011
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Summary:We examine the correlation between supernova (SN) host-galaxy properties and their residuals in the Hubble diagram. We use SNe discovered during the Sloan Digital Sky Survey-II Supernova Survey, and focus on objects at a redshift of z < 0.15, where the selection effects of the survey are known to yield a complete Type Ia supernova (SN Ia) sample. To minimize the bias in our analysis with respect to measured host-galaxy properties, spectra were obtained for nearly all hosts, spanning a range in magnitude of -23 < M{sub r} < -17. In contrast to previous works that use photometric estimates of host mass as a proxy for global metallicity, we analyze host-galaxy spectra to obtain gas-phase metallicities and star formation rates (SFRs) from host galaxies with active star formation. From a final sample of {approx}40 emission-line galaxies, we find that light-curve-corrected SNe Ia are {approx}0.1 mag brighter in high-metallicity hosts than in low-metallicity hosts. We also find a significant (>3{sigma}) correlation between the Hubble Residuals of SNe Ia and the specific SFR of the host galaxy. We comment on the importance of SN/host-galaxy correlations as a source of systematic bias in future deep SN surveys.
ISSN:0004-637X
1538-4357
DOI:10.1088/0004-637X/743/2/172