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Examining AGN UV/optical Variability Beyond the Simple Damped Random Walk

Yu, Weixiang and Richards, Gordon T. and Vogeley, Michael S. and Moreno, Jackeline and Graham, Matthew J. (2022) Examining AGN UV/optical Variability Beyond the Simple Damped Random Walk. . (Unpublished)

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We present damped harmonic oscillator (DHO) light-curve modeling for a sample of 12,714 spectroscopically confirmed quasars in the Sloan Digital Sky Survey Stripe 82 region. DHO is a second-order continuous-time autoregressive moving-average (CARMA) process, and features four independent parameters: a natural oscillation frequency (ω₀), a damping ratio (ξ), a characteristic perturbation timescale (τ_(perturb)), and an amplitude for the perturbing white noise (σ_ϵ). The asymptotic variability amplitude of a DHO process is quantified by σ_(DHO) -- a function of ω₀, ξ, τ_(perturb), and σ_ϵ. We found that both τperturb and σϵ follow different dependencies with rest-frame wavelength (λ_(RF)) on either side of 2500 angstroms, whereas σ_(DHO) follows a single power-law relation with λ_(RF). After correcting for wavelength dependence, σ_(DHO) exhibits anti-correlations with both the Eddington ratio and black hole mass, and τ_(perturb) -- with a typical value of days in rest-frame -- shows an anti-correlation with the bolometric luminosity. Modeling AGN variability as a DHO offers more insight into how accretion disks work close to the supermassive black holes (SMBHs) at the center of AGN. The newly discovered short-term variability (τperturb) and its correlation with bolometric luminosity pave the way for new algorithms that will derive fundamental properties (e.g., Eddington ratio) of AGN using photometric data alone.

Item Type:Report or Paper (Discussion Paper)
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URLURL TypeDescription Paper ItemPublished Version
Yu, Weixiang0000-0003-1262-2897
Richards, Gordon T.0000-0002-1061-1804
Vogeley, Michael S.0000-0001-7416-9800
Moreno, Jackeline0000-0001-9134-6522
Graham, Matthew J.0000-0002-3168-0139
Additional Information:Attribution 4.0 International (CC BY 4.0). M.S.V and J.M. acknowledge support from NASA grant NNX17AF18G. Funding for the SDSS and SDSS-II has been provided by the Alfred P. Sloan Foundation, the Participating Institutions, the National Science Foundation, the U.S. Department of Energy, the National Aeronautics and Space Administration, the Japanese Monbukagakusho, the Max Planck Society, and the Higher Education Funding Council for England. The SDSS Web Site is The SDSS is managed by the Astrophysical Research Consortium for the Participating Institutions. The Participating Institutions are the American Museum of Natural History, Astrophysical Institute Potsdam, University of Basel, University of Cambridge, Case Western Reserve University, University of Chicago, Drexel University, Fermilab, the Institute for Advanced Study, the Japan Participation Group, Johns Hopkins University, the Joint Institute for Nuclear Astrophysics, the Kavli Institute for Particle Astrophysics and Cosmology, the Korean Scientist Group, the Chinese Academy of Sciences (LAMOST), Los Alamos National Laboratory, the Max-Planck-Institute for Astronomy (MPIA), the Max-Planck-Institute for Astrophysics (MPA), New Mexico State University, Ohio State University, University of Pittsburgh, University of Portsmouth, Princeton University, the United States Naval Observatory, and the University of Washington. Funding for the Sloan Digital Sky Survey IV has been provided by the Alfred P. Sloan Foundation, the U.S. Department of Energy Office of Science, and the Participating Institutions. SDSS-IV acknowledges support and resources from the Center for High Performance Computing at the University of Utah. The SDSS website is SDSS-IV is managed by the Astrophysical Research Consortium for the Participating Institutions of the SDSS Collaboration including the Brazilian Participation Group, the Carnegie Institution for Science, Carnegie Mellon University, Center for Astrophysics — Harvard & Smithsonian, the Chilean Participation Group, the French Participation Group, Instituto de Astrofísica de Canarias, The Johns Hopkins University, Kavli Institute for the Physics and Mathematics of the Universe (IPMU) / University of Tokyo, the Korean Participation Group, Lawrence Berkeley National Laboratory, Leibniz Institut für Astrophysik Potsdam (AIP), Max-Planck-Institut für Astronomie (MPIA Heidelberg), Max-Planck-Institut für Astrophysik (MPA Garching), Max-Planck-Institut für Extraterrestrische Physik (MPE), National Astronomical Observatories of China, New Mexico State University, New York University, University of Notre Dame, Observatário Nacional / MCTI, The Ohio State University, Pennsylvania State University, Shanghai Astronomical Observatory, United Kingdom Participation Group, Universidad Nacional Autónoma de México, University of Arizona, University of Colorado Boulder, University of Oxford, University of Portsmouth, University of Utah, University of Virginia, University of Washington, University of Wisconsin, Vanderbilt University, and Yale University. This research makes use of the SciServer science platform ( SciServer is a collaborative research environment for large-scale data-driven science. It is being developed at, and administered by, the Institute for Data Intensive Engineering and Science at Johns Hopkins University. SciServer is funded by the National Science Foundation through the Data Infrastructure Building Blocks (DIBBs) program and others, as well as by the Alfred P. Sloan Foundation and the Gordon and Betty Moore Foundation. Software: pandas (Wes McKinney 2010), numpy (Harris et al. 2020), scipy (Virtanen et al. 2020), matplotlib (Hunter 2007), astropy (The Astropy Collaboration et al. 2013), emcee (Foreman-Mackey et al. 2013),
Funding AgencyGrant Number
Alfred P. Sloan FoundationUNSPECIFIED
Participating InstitutionsUNSPECIFIED
Department of Energy (DOE)UNSPECIFIED
Japanese MonbukagakushoUNSPECIFIED
Max Planck SocietyUNSPECIFIED
Higher Education Funding Council for EnglandUNSPECIFIED
Gordon and Betty Moore FoundationUNSPECIFIED
Subject Keywords:quasars, AGN, supermassive black holes — time series analysis — surveys
Record Number:CaltechAUTHORS:20220224-200911259
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:113597
Deposited By: George Porter
Deposited On:28 Feb 2022 17:59
Last Modified:03 Dec 2022 00:26

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