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This work develops application techniques for stochastic modelling of Active Galactic Nuclei (AGN) variability as a probe of accretion disk physics. Stochastic models, specifically Continuous Auto-Regressive Moving Average (CARMA) models, characterize lightcurves by estimating delay timescales that describe movements away from and toward equilibrium (mean flux) as well as an amplitude and frequency of intrinsic perturbations to the AGN flux. We begin this tutorial by reviewing discrete auto-regressive (AR) and moving-average (MA) processes, we bridge these components to their continuous analogs, and lastly we investigate the significance of timescales from direct stochastic modelling of a lightcurve projected in power spectrum (PSD) and structure function (SF) space. We determine that higher order CARMA models, for example the Damped Harmonic Oscillator (DHO or CARMA(2,1)) are more sensitive to deviations from a single-slope power-law description of AGN variability; unlike Damped Random Walks (DRW or CAR(1)) where the PSD slope is fixed, the DHO slope is not. Higher complexity stochastic models than the DRW capture additional covariance in data and output additional characteristic timescales that probe the driving mechanisms of variability.
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The advent of new time domain surveys and the imminent increase in astronomical data expose the shortcomings in traditional time series analysis (such as power spectra analysis) in characterising the abundantly varied, complex and stochastic light curves of Active Galactic Nuclei (AGN). Recent applications of novel methods from non-linear dynamics have shown promise in characterising higher modes of variability and time-scales in AGN. Recurrence analysis in particular can provide complementary information about characteristic time-scales revealed by other methods, as well as probe the nature of the underlying physics in these objects. Recurrence analysis was developed to study the recurrences of dynamical trajectories in phase space, which can be constructed from one-dimensional time series such as light curves. We apply the methods of recurrence analysis to two optical light curves of Kepler-monitored AGN. We confirm the detection and period of an optical quasi-periodic oscillation in one AGN, and confirm multiple other time-scales recovered from other methods ranging from 5 days to 60 days in both objects. We detect regions in the light curves that deviate from regularity, provide evidence of determinism and non-linearity in the mechanisms underlying one light curve (KIC 9650712), and determine a linear stochastic process recovers the dominant variability in the other light curve (Zwicky 229--015). We discuss possible underlying processes driving the dynamics of the light curves and their diverse classes of variability.
Here we present the evidence for periodicity of an optical emission detected in several AGN. Significant periodicity is found in light curves and radial velocity curves. We discuss possible mechanisms that could produce such periodic variability and their implications. The results are consistent with possible detection of the orbital motion in proximity of the AGN central supermassive black holes.
We used data from the QUEST-La Silla Active Galactic Nuclei (AGN) variability survey to construct light curves for 208,583 sources over $sim 70$ deg$^2$, with a a limiting magnitude $r sim 21$. Each light curve has at least 40 epochs and a length of $geq 200$ days. We implemented a Random Forest algorithm to classify our objects as either AGN or non-AGN according to their variability features and optical colors, excluding morphology cuts. We tested three classifiers, one that only includes variability features (RF1), one that includes variability features and also $r-i$ and $i-z$ colors (RF2), and one that includes variability features and also $g-r$, $r-i$, and $i-z$ colors (RF3). We obtained a sample of high probability candidates (hp-AGN) for each classifier, with 5,941 candidates for RF1, 5,252 candidates for RF2, and 4,482 candidates for RF3. We divided each sample according to their $g-r$ colors, defining blue ($g-rleq 0.6$) and red sub-samples ($g-r>0.6$). We find that most of the candidates known from the literature belong to the blue sub-samples, which is not necessarily surprising given that, unlike for many literature studies, we do not cut our sample to point-like objects. This means that we can select AGN that have a significant contribution from redshifted starlight in their host galaxies. In order to test the efficiency of our technique we performed spectroscopic follow-up, confirming the AGN nature of 44 among 54 observed sources (81.5% of efficiency). From the campaign we concluded that RF2 provides the purest sample of AGN candidates.
The Gaia DR2 sample of short-timescale variable candidates results from the investigation of the first 22 months of Gaia photometry for a subsample of sources at the Gaia faint end. For this exercise, we limited ourselves to the case of suspected rapid periodic variability. Our study combines fast-variability detection through variogram analysis, high-frequency search by means of least-squares periodograms, and empirical selection based on the investigation of specific sources seen through the Gaia eyes (e.g. known variables or visually identified objects with peculiar features in their light curves). The progressive definition and validation of this selection criterion also benefited from supplementary ground-based photometric monitoring of a few preliminary candidates, performed at the Flemish Mercator telescope (Canary Islands, Spain) between August and November 2017. We publish a list of 3,018 short-timescale variable candidates, spread throughout the sky, with a false-positive rate up to 10-20% in the Magellanic Clouds, and a more significant but justifiable contamination from longer-period variables between 19% and 50%, depending on the area of the sky. Although its completeness is limited to about 0.05%, this first sample of Gaia short-timescale variables recovers some very interesting known short-period variables, such as post-common envelope binaries or cataclysmic variables, and brings to light some fascinating, newly discovered variable sources. In the perspective of future Gaia data releases, several improvements of the short-timescale variability processing are considered, by enhancing the existing variogram and period-search algorithms or by classifying the identified candidates. Nonetheless, the encouraging outcome of our Gaia DR2 analysis demonstrates the power of this mission for such fast-variability studies, and opens great perspectives for this domain of astrophysics.
We present preliminary results on the variability properties of AGN above 20 keV in order to show the potential of the INTEGRAL IBIS/ISGRI and Swift/BAT instruments for hard X-ray timing analysis of AGN. The 15-50 keV light curves of 36 AGN observed by BAT during 5 years show significantly larger variations when the blazar population is considered (average normalized excess variance = 0.25) with respect to the Seyfert one (average normalized excess variance = 0.09). The hard X-ray luminosity is found to be anti-correlated to the variability amplitude in Seyfert galaxies and correlated to the black hole mass, confirming previous findings obtained with different AGN hard X-ray samples. We also present results on the Seyfert 1 galaxy IC 4329A, as an example of spectral variability study with INTEGRAL/ISGRI data. The position of the high-energy cut-off of this source is found to have varied during the INTEGRAL observations, pointing to a change of temperature of the Comptonising medium. For several bright Seyfert galaxies, a considerable amount of INTEGRAL data have already been accumulated and are publicly available, allowing detailed spectral variability studies at hard X-rays.
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