101. Testing the Completeness of the SDSS Colour Selection for Ultramassive, Slowly Spinning Black Holes
- Author
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Benny Trakhtenbrot, Kevin Schawinski, Chris Done, Martin Elvis, and Caroline Bertemes
- Subjects
media_common.quotation_subject ,Astrophysics::High Energy Astrophysical Phenomena ,Population ,FOS: Physical sciences ,Astrophysics ,Astrophysics::Cosmology and Extragalactic Astrophysics ,01 natural sciences ,0103 physical sciences ,Astrophysics::Solar and Stellar Astrophysics ,education ,010303 astronomy & astrophysics ,Astrophysics::Galaxy Astrophysics ,media_common ,Spin-½ ,Physics ,Supermassive black hole ,education.field_of_study ,Accretion (meteorology) ,010308 nuclear & particles physics ,Astronomy ,Astronomy and Astrophysics ,Quasar ,Astrophysics - Astrophysics of Galaxies ,Redshift ,Space and Planetary Science ,Sky ,Astrophysics of Galaxies (astro-ph.GA) ,Spectral energy distribution - Abstract
We investigate the sensitivity of the colour-based quasar selection algorithm of the Sloan Digital Sky Survey to several key physical parameters of supermassive black holes (SMBHs), focusing on BH spin ($a_{\star}$) at the high BH-mass regime ($M_{BH} \geqslant10^9\, M_{\odot}$). We use a large grid of model spectral energy distribution, assuming geometrically-thin, optically-thick accretion discs, and spanning a wide range of five physical parameters: BH mass $M_{BH}$, BH spin $a_{\star}$, Eddington ratio $L / L_{Edd}$ , redshift $z$, and inclination angle $inc$. Based on the expected fluxes in the SDSS imaging ugriz bands, we find that $\sim 99.8\%$ of our models with $M_{BH} \leqslant 10^{9.5}\, M_{\odot}$ are selected as quasar candidates and thus would have been targeted for spectroscopic follow-up. However, in the extremely high-mass regime, $\geqslant 10^{10} M_{\odot}$, we identify a bias against slowly/retrograde spinning SMBHs. The fraction of SEDs that would have been selected as quasar candidates drops below $\sim50\%$ for $a_{\star}, Comment: 13 pages, 9 figures, accepted for publication in MNRAS
- Published
- 2016
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