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Title: The Ensemble Photometric Variability of Over 105 Quasars in the Dark Energy Camera Legacy Survey and the Sloan Digital Sky Survey

Journal Article · · The Astrophysical Journal (Online)
 [1]; ORCiD logo [2]; ORCiD logo [3]; ORCiD logo [4]; ORCiD logo [5]
  1. Peking Univ., Beijing (China). School of Physics, Dept. of Astronomy
  2. Univ. of Arizona, Tucson, AZ (United States)
  3. Peking Univ., Beijing (China). School of Physics, Dept. of Astronomy and Kavli Inst. for Astronomy and Astrophysics
  4. Univ. of Arizona, Tucson, AZ (United States); Peking Univ., Beijing (China). Kavli Inst. for Astronomy and Astrophysics
  5. Peking Univ., Beijing (China). Kavli Inst. for Astronomy and Astrophysics; Peking Univ., Beijing (China). School of Physics, Dept. of Astronomy
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We present the ensemble variability analysis results of quasars using the Dark Energy Camera Legacy Survey (DECaLS) and the Sloan Digital Sky Survey (SDSS) quasar catalogs. Our data set includes 119,305 quasars with redshifts up to 4.89. Combining the two data sets provides a 15 year baseline and permits the analysis of the long timescale variability. Adopting a power-law form for the variability structure function, $V=A(t/$1years)$^γ$, we use the multidimensional parametric fitting to explore the relationships between the quasar variability amplitude and a wide variety of quasar properties, including redshift (positive), bolometric luminosity (negative), rest-frame wavelength (negative), and black hole mass (uncertain). We also find that γ can be also expressed as a function of redshift (negative), bolometric luminosity (positive), rest-frame wavelength (positive), and black hole mass (positive). Tests of the fitting significance with the bootstrap method show that, even with such a large quasar sample, some correlations are marginally significant. The typical value of $$γ$$ for the entire data set is $≳0.25$, consistent with the results in previous studies on both the quasar ensemble variability and the structure function. A significantly negative correlation between the variability amplitude and the Eddington ratio is found, which may be explained as an effect of accretion disk instability.

Research Organization:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States). National Energy Research Scientific Computing Center (NERSC)
Sponsoring Organization:
USDOE
OSTI ID:
1544064
Journal Information:
The Astrophysical Journal (Online), Vol. 861, Issue 1; ISSN 1538-4357
Publisher:
Institute of Physics (IOP)Copyright Statement
Country of Publication:
United States
Language:
English
Citation Metrics:
Cited by: 9 works
Citation information provided by
Web of Science

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A Synoptic, Multiwavelength Analysis of a Large Quasar Sample text January 2005
The dependence of quasar variability on black hole mass text January 2006
Active Galactic Nuclei as scaled-up Galactic black holes text January 2006
The Ensemble Variability Properties of Faint QSOs text January 1994
Thermal Instability of Advection-Dominated Disks against Local Perturbations text January 1995
The QSO variability-luminosity-redshift relation text January 1996
QSO variability: probing the Starburst model text January 1996
Optical Variability in Active Galactic Nuclei: Starbursts or Disk Instabilities? text January 1997
Long-term optical variability properties of the Palomar-Green quasars text January 1999
Optical Monitoring of Quasars: I. Variability text January 1999

Cited By (3)

The QUEST–La Silla AGN Variability Survey: Connection between AGN Variability and Black Hole Physical Properties journal September 2018
The QUEST-La Silla AGN Variability Survey: Selection of AGN Candidates through Optical Variability journal May 2019
The QUEST-La Silla AGN variability survey: connection between AGN variability and black hole physical properties text January 2018

Figures / Tables (12)

Fig. 1(p. 2)figure Fig. 1
Fig. 2(p. 3)figure Fig. 2
TABLE 1(p. 3)table TABLE 1
TABLE 2(p. 4)table TABLE 2
Fig. 3(p. 5)figure Fig. 3
Fig. 4(p. 7)figure Fig. 4
TABLE 3(p. 7)table TABLE 3
Fig. 5(p. 8)figure Fig. 5
Fig. 6(p. 9)figure Fig. 6
Fig. 7(p. 10)figure Fig. 7
Fig. 8(p. 11)figure Fig. 8
TABLE 4(p. 12)table TABLE 4

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