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Title: The Clustering of High-redshift (2.9 ≤ $$z$$ ≤ 5.1) Quasars in SDSS Stripe 82

Abstract

We present a measurement of the two-point autocorrelation function of photometrically selected high-$$z$$ quasars over ~100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the $Spitzer$ IRAC Equatorial Survey and the $Spitzer$-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-$$z$$ quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ $$z$$ ≤ 5.1 and are generally fainter than $$i$$ = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of $$δ$$ = 1.39 ± 0.618 and amplitude of $$θ_0$$ = 0$$^{\prime}_{.}$$71 ± 0$$^{\prime}_{.}$$546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey ($$\langle z\rangle =3.38$$), the bias is $$b$$ = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83$$\times {10}^{12}{h}^{-1}\,{M}_{\odot }$$. Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-$$z$$.

Authors:
ORCiD logo [1];  [2]; ORCiD logo [1];  [3];  [1]; ORCiD logo [4]; ORCiD logo [5];  [6]; ORCiD logo [7]; ORCiD logo [8]
  1. Drexel Univ., Philadelphia, PA (United States). Dept. of Physics
  2. Univ. of Edinburgh, Scotland (United Kingdom). Inst. of Astronomy
  3. Univ. of Wyoming, Laramie, WY (United States). Dept. of Physics and Astronomy
  4. Instituto de Astrofísica and Centro de Astroingeniería, Facultad de Física, (Chile); Millennium Institute of Astrophysics (MAS), Santiago (Chile); Space Science Inst., Boulder, CO (United States)
  5. National Radio Astronomy Observatory, Charlottesville, VA (United States)
  6. Univ. of Pennsylvania, Philadelphia, PA (United States). Dept. of Physics and Astronomy; Pennsylvania State Univ., University Park, PA (United States). Inst. for Gravitation and the Cosmos
  7. NASA Goddard Inst. for Space Studies (GISS), New York, NY (United States)
  8. Johns Hopkins Univ., Baltimore, MD (United States). Department of Physics and Astronomy
Publication Date:
Research Org.:
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Org.:
USDOE
OSTI Identifier:
1544058
Resource Type:
Accepted Manuscript
Journal Name:
The Astrophysical Journal (Online)
Additional Journal Information:
Journal Name: The Astrophysical Journal (Online); Journal Volume: 859; Journal Issue: 1; Journal ID: ISSN 1538-4357
Publisher:
Institute of Physics (IOP)
Country of Publication:
United States
Language:
English
Subject:
79 ASTRONOMY AND ASTROPHYSICS; Astronomy & Astrophysics

Citation Formats

Timlin, John D., Ross, Nicholas P., Richards, Gordon T., Myers, Adam D., Pellegrino, Andrew, Bauer, Franz E., Lacy, Mark, Schneider, Donald P., Wollack, Edward J., and Zakamska, Nadia L. The Clustering of High-redshift (2.9 ≤ $z$ ≤ 5.1) Quasars in SDSS Stripe 82. United States: N. p., 2018. Web. doi:10.3847/1538-4357/aab9ac.
Timlin, John D., Ross, Nicholas P., Richards, Gordon T., Myers, Adam D., Pellegrino, Andrew, Bauer, Franz E., Lacy, Mark, Schneider, Donald P., Wollack, Edward J., & Zakamska, Nadia L. The Clustering of High-redshift (2.9 ≤ $z$ ≤ 5.1) Quasars in SDSS Stripe 82. United States. https://doi.org/10.3847/1538-4357/aab9ac
Timlin, John D., Ross, Nicholas P., Richards, Gordon T., Myers, Adam D., Pellegrino, Andrew, Bauer, Franz E., Lacy, Mark, Schneider, Donald P., Wollack, Edward J., and Zakamska, Nadia L. Thu . "The Clustering of High-redshift (2.9 ≤ $z$ ≤ 5.1) Quasars in SDSS Stripe 82". United States. https://doi.org/10.3847/1538-4357/aab9ac. https://www.osti.gov/servlets/purl/1544058.
@article{osti_1544058,
title = {The Clustering of High-redshift (2.9 ≤ $z$ ≤ 5.1) Quasars in SDSS Stripe 82},
author = {Timlin, John D. and Ross, Nicholas P. and Richards, Gordon T. and Myers, Adam D. and Pellegrino, Andrew and Bauer, Franz E. and Lacy, Mark and Schneider, Donald P. and Wollack, Edward J. and Zakamska, Nadia L.},
abstractNote = {We present a measurement of the two-point autocorrelation function of photometrically selected high-$z$ quasars over ~100 deg2 on the Sloan Digital Sky Survey Stripe 82 field. Selection is performed using three machine-learning algorithms in a six-dimensional optical/mid-infrared color space. Optical data from the Sloan Digital Sky Survey are combined with overlapping deep mid-infrared data from the $Spitzer$ IRAC Equatorial Survey and the $Spitzer$-HETDEX Exploratory Large-Area survey. Our selection algorithms are trained on the colors of known high-$z$ quasars. The selected quasar sample consists of 1378 objects and contains both spectroscopically confirmed quasars and photometrically selected quasar candidates. These objects span a redshift range of 2.9 ≤ $z$ ≤ 5.1 and are generally fainter than $i$ = 20.2, a regime that has lacked sufficient number density to perform autocorrelation function measurements of photometrically classified quasars. We compute the angular correlation function of these data, marginally detecting quasar clustering. We fit a single power law with an index of $δ$ = 1.39 ± 0.618 and amplitude of $θ_0$ = 0$^{\prime}_{.}$71 ± 0$^{\prime}_{.}$546 . A dark matter model is fit to the angular correlation function to estimate the linear bias. At the average redshift of our survey ($\langle z\rangle =3.38$), the bias is $b$ = 6.78 ± 1.79. Using this bias, we calculate a characteristic dark matter halo mass of 1.70–9.83$\times {10}^{12}{h}^{-1}\,{M}_{\odot }$. Our bias estimate suggests that quasar feedback intermittently shuts down the accretion of gas onto the central supermassive black hole at early times. If confirmed, these results hint at a level of luminosity dependence in the clustering of quasars at high-$z$.},
doi = {10.3847/1538-4357/aab9ac},
journal = {The Astrophysical Journal (Online)},
number = 1,
volume = 859,
place = {United States},
year = {Thu May 17 00:00:00 EDT 2018},
month = {Thu May 17 00:00:00 EDT 2018}
}

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Cited by: 19 works
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TABLE 1 TABLE 1: Selected quasar clustering measurements.

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Works referenced in this record:

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Photometric Redshifts of Quasars
text, January 2001


Stable clustering, the halo model and nonlinear cosmological power spectra
text, January 2002


Cosmic Evolution of Quasar Clustering: Implications for the Host Haloes
text, January 2004


Mid-Infrared Selection of Active Galaxies
text, January 2004


Hectospec, the MMT's 300 Optical Fiber-Fed Spectrograph
text, January 2005


The James Webb Space Telescope
text, January 2006


How accurate is Limber's equation?
text, January 2006


Stochastic Nonlinear Galaxy Biasing
text, January 1998


Works referencing / citing this record:

Surveying the reach and maturity of machine learning and artificial intelligence in astronomy
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The route to massive black hole formation via merger-driven direct collapse: a review
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Downsizing of star formation measured from the clustered infrared background correlated with quasars
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The clustering of undetected high-redshift black holes and their signatures in cosmic backgrounds
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A high baryon fraction in massive haloes at z ∼ 3
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The REQUIEM Survey. I. A Search for Extended Ly α Nebular Emission Around 31 z > 5.7 Quasars
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Black versus Dark: Rapid Growth of Supermassive Black Holes in Dark Matter Halos at z ∼ 6
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The route to massive black hole formation via merger-driven direct collapse: a review
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