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Register a new userModeling the Time Variability of SDSS Stripe 82 Quasars as a Damped Random Walk
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We model the time variability of ~9,000 spectroscopically confirmed quasars in SDSS Stripe 82 as a damped random walk. Using 2.7 million photometric measurements collected over 10 years, we confirm the results of Kelly et al. (2009) and Koz{l}owski et al. (2010) that this model can explain quasar light curves at an impressive fidelity level (0.01-0.02 mag). The damped random walk model provides a simple, fast [O(N) for N data points], and powerful statistical description of quasar light curves by a characteristic time scale (tau) and an asymptotic rms variability on long time scales (SF_inf). We searched for correlations between these two variability parameters and physical parameters such as luminosity and black hole mass, and rest-frame wavelength. We find that tau increases with increasing wavelength with a power law index of 0.17, remains nearly constant with redshift and luminosity, and increases with increasing black hole mass with power law index of 0.21+/-0.07. The amplitude of variability is anti-correlated with the Eddington ratio, which suggests a scenario where optical fluctuations are tied to variations in the accretion rate. The radio-loudest quasars have systematically larger variability amplitudes by about 30%, when corrected for the other observed trends, while the distribution of their characteristic time scale is indistinguishable from that of the full sample. We do not detect any statistically robust differences in the characteristic time scale and variability amplitude between the full sample and the small subsample of quasars detected by ROSAT. Our results provide a simple quantitative framework for generating mock quasar light curves, such as currently used in LSST image simulations. (abridged)
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The SDSS-III BOSS Quasar survey will attempt to observe z>2.15 quasars at a density of at least 15 per square degree to yield the first measurement of the Baryon Acoustic Oscillations in the Ly-alpha forest. To help reaching this goal, we have developed a method to identify quasars based on their variability in the u g r i z optical bands. The method has been applied to the selection of quasar targets in the SDSS region known as Stripe 82 (the Southern equatorial stripe), where numerous photometric observations are available over a 10-year baseline. This area was observed by BOSS during September and October 2010. Only 8% of the objects selected via variability are not quasars, while 90% of the previously identified high-redshift quasar population is recovered. The method allows for a significant increase in the z>2.15 quasar density over previous strategies based on optical (ugriz) colors, achieving a density of 24.0 deg^{-2} on average down to g~22 over the 220 deg^2 area of Stripe 82. We applied this method to simulated data from the Palomar Transient Factory and from Pan-STARRS, and showed that even with data that have sparser time sampling than what is available in Stripe 82, including variability in future quasar selection strategies would lead to increased target selection efficiency in the z>2.15 redshift range. We also found that Broad Absorption Line quasars are preferentially present in a variability than in a color selection.
A damped random walk is a stochastic process, defined by an exponential covariance matrix that behaves as a random walk for short time scales and asymptotically achieves a finite variability amplitude at long time scales. Over the last few years, it has been demonstrated, mostly but not exclusively using SDSS data, that a damped random walk model provides a satisfactory statistical description of observed quasar variability in the optical wavelength range, for rest-frame timescales from 5 days to 2000 days. The best-fit characteristic timescale and asymptotic variability amplitude scale with the luminosity, black hole mass, and rest wavelength, and appear independent of redshift. In addition to providing insights into the physics of quasar variability, the best-fit model parameters can be used to efficiently separate quasars from stars in imaging surveys with adequate long-term multi-epoch data, such as expected from LSST.
Hundreds of Type 2 quasars have been identified in Sloan Digital Sky Survey (SDSS) data, and there is substantial evidence that they are generally galaxies with highly obscured central engines, in accord with unified models for active galactic nuclei (AGNs). A straightforward expectation of unified models is that highly obscured Type 2 AGNs should show little or no optical variability on timescales of days to years. As a test of this prediction, we have carried out a search for variability in Type 2 quasars in SDSS Stripe 82 using difference-imaging photometry. Starting with the Type 2 AGN catalogs of Zakamska et al. (2003) and Reyes et al. (2008), we find evidence of significant g-band variability in 17 out of 173 objects for which light curves could be measured from the Stripe 82 data. To determine the nature of this variability, we obtained new Keck spectropolarimetry observations for seven of these variable AGNs. The Keck data show that these objects have low continuum polarizations (p<~1% in most cases) and all seven have broad H-alpha and/or MgII emission lines in their total (unpolarized) spectra, indicating that they should actually be classified as Type 1 AGNs. We conclude that the primary reason variability is found in the SDSS-selected Type 2 AGN samples is that these samples contain a small fraction of Type 1 AGNs as contaminants, and it is not necessary to invoke more exotic possible explanations such as a population of naked or unobscured Type 2 quasars. Aside from misclassified Type 1 objects, the Type 2 quasars do not generally show detectable optical variability over the duration of the Stripe 82 survey.
We report on a blind survey for extragalactic radio variability that was carried out by comparing two epochs of data from the FIRST survey with a third epoch from a new 1.4 GHz survey of SDSS Stripe 82. The three epochs are spaced seven years apart and have an overlapping area of 60 deg^2. We uncover 89 variable sources down to the millijansky level, 75 of which are newly-identified, and we find no evidence for transient phenomena. This new sample of variable sources allows us to infer an upper limit to the mean characteristic timescale of AGN radio variability of 14 years. We find that only 1% of extragalactic sources have fractional variability f_var >3, while 44% of Galactic sources vary by this much. The variable sample contains a larger fraction of quasars than a comparable non-variable control sample, though the majority of the variable sources appear to be extended galaxies in the optical. This implies that either quasars are not the dominant contributor to the variability of the sample, or that the deep optical data allow us to detect the host galaxies of some low-z quasars. We use the new, higher resolution data to report on the morphology of the variable sources. Finally, we show that the fraction of sources that are variable remains constant or increases at low flux densities. This may imply that next generation radio surveys with telescopes like the Australian Square Kilometer Array Pathfinder and MeerKAT will see a constant or even increasing fraction of variable sources down into the submillijansky regime.
The damped random walk (DRW) model is increasingly used to model the variability in quasar optical light curves, but it is still uncertain whether the DRW model provides an adequate description of quasar optical variability across all time scales. Using a sample of OGLE quasar light curves, we consider four modifications to the DRW model by introducing additional parameters into the covariance function to search for deviations from the DRW model on both short and long time scales. We find good agreement with the DRW model on time scales that are well sampled by the data (from a month to a few years), possibly with some intrinsic scatter in the additional parameters, but this conclusion depends on the statistical test employed and is sensitive to whether the estimates of the photometric errors are correct to within ~10%. On very short time scales (below a few months), we see some evidence of the existence of a cutoff below which the correlation is stronger than the DRW model, echoing the recent finding of Mushotzky et al. (2011) using quasar light curves from Kepler. On very long time scales (> a few years), the light curves do not constrain models well, but are consistent with the DRW model.
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