Optical variability of quasars with 20-yr photometric light curves

Abstract

We study the optical gri photometric variability of a sample of 190 quasars within the SDSS Stripe 82 region that have long-term photometric coverage during ∼1998 − 2020 with SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up monitoring with Blanco 4m/DECam. With on average ∼200 nightly epochs per quasar per filter band, we improve the parameter constraints from a Damped Random Walk (DRW) model fit to the light curves over previous studies with 10–15 yr baselines and ≲ 100 epochs. We find that the average damping timescale τDRW continues to rise with increased baseline, reaching a median value of ∼750 days (g band) in the rest-frame of these quasars using the 20-yr light curves. Some quasars may have gradual, long-term trends in their light curves, suggesting that either the DRW fit requires very long baselines to converge, or that the underlying variability is more complex than a single DRW process for these quasars. Using a subset of quasars with better-constrained τDRW (less than 20% of the baseline), we confirm a weak wavelength dependence of τDRW∝λ0.51 ± 0.20. We further quantify optical variability of these quasars over days to decades timescales using structure function (SF) and power spectrum density (PSD) analyses. The SF and PSD measurements qualitatively confirm the measured (hundreds of days) damping timescales from the DRW fits. However, the ensemble PSD is steeper than that of a DRW on timescales less than ∼ a month for these luminous quasars, and this second break point correlates with the longer DRW damping timescale.

The relation between quasars' optical spectra and variability

“…Assuming that the luminosity of [OIII]5007 does not change during observations, a 0.28 change in log10EW ([OIII]5007) means that the continuum changes by about 0.71 mag. On the other hand, the structure function of 20 years light curves indicates that the standard deviation of the magnitude difference between the data with 10 years separation is about 0.3 mag (Stone et al 2022). This comparison indicates that the scatter of the distribution on the EV1 plane is more extensive than would be explained by the typical continuous light variation over ten years.…”

The LSST Era of Supermassive Black Hole Accretion Disk Reverberation Mapping

“…There are ongoing efforts of creating a prime sample of quasars to further test the applicability of the DRW model and the stationarity of the stochastic variability process. Stone et al (2022) investigated the optical continuum variability of 190 quasars within the SDSS Stripe 82 over 20 yr long baseline. This sample contains hundreds of epochs from SDSS, PanSTARRS-1, the Dark Energy Survey, and dedicated follow-up photometric monitoring with DECam on the CTIO-4 m Blanco telescope, making it one of the best-quality light-curve data sets for studying quasar variability.…”

“…However, the following limitation of the DRW model should be kept in mind: as Kozłowski (2017) identified, it is important that the time baseline of the light curve is considerably longer than the damping timescale. Also, Stone et al (2022) implied that even a 20 yr baseline is unlikely to be long enough to constrain the damping timescale in some of the quasars in their sample. This could be due to long-term trends in the light curve, or that these processes are more complex than a basic DRW with only one characteristic timescale (see Stone et al 2022).…”

“…Also, Stone et al (2022) implied that even a 20 yr baseline is unlikely to be long enough to constrain the damping timescale in some of the quasars in their sample. This could be due to long-term trends in the light curve, or that these processes are more complex than a basic DRW with only one characteristic timescale (see Stone et al 2022). We also used the AGN lamppost 29 AD model (Cackett et al 2007) to account for wavelength dependence and replicate delayed LSST multiband light curves.…”

Gaussian Process regression for astronomical time-series

“…The idea is that the properties of the stochastic variations of an AGN light curve are driven by an accretion disk near the central supermassive black hole, and that this variability provides an observational probe of the small scale astrophysical processes. The standard approach is to fit a GP model to the light curve-typically using a "damped random walk" kernel, or the more general "continuous-time autoregressive moving average" (CARMA) kernel (e.g., Kelly et al 2014), since these permit efficient computations even with large datasets-and then to use the inferred hyper-parameter values to constrain the variability amplitudes and timescales of the system (e.g., Kelly et al 2014;Kasliwal et al 2017;Moreno et al 2019;Stone et al 2022). These amplitudes and timescales have been shown to empirically correlate with the fundamental properties of the AGN system, such as the mass of the central black hole, Eddington ratio, and bolometric luminosity (Yu et al 2022b).…”