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Register a new userLSST AGN SC Cadence Note: Two metrics on AGN variability observable
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We have developed two metrics related to AGN variability observables (time-lags, periodicity, and Structure Function (SF)) to evaluate LSST OpSim FBS 1.5, 1.6, 1.7 performance in AGN time-domain analysis. For this purpose, we generate an ensemble of AGN light curves based on AGN empirical relations and LSST OpSim cadences. Although our metrics show that denser LSST cadences produce more reliable time-lag, periodicity, and SF measurements, the discrepancies in the performance between different LSST OpSim cadences are not drastic based on Kullback-Leibler divergence. This is complementary to Yu and Richards results on DCR and SF metrics, extending them to include the point of view of AGN variability.
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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 present a framework to link and describe AGN variability on a wide range of timescales, from days to billions of years. In particular, we concentrate on the AGN variability features related to changes in black hole fuelling and accretion rate. In our framework, the variability features observed in different AGN at different timescales may be explained as realisations of the same underlying statistical properties. In this context, we propose a model to simulate the evolution of AGN light curves with time based on the probability density function (PDF) and power spectral density (PSD) of the Eddington ratio ($L/L_{rm Edd}$) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the $L/L_{rm Edd}$ distribution function (ERDF), and that a single (or limited number of) ERDF+PSD set may explain all observed variability features. After outlining the framework and the model, we compile a set of variability measurements in terms of structure function (SF) and magnitude difference. We then combine the variability measurements on a SF plot ranging from days to Gyr. The proposed framework enables constraints on the underlying PSD and the ability to link AGN variability on different timescales, therefore providing new insights into AGN variability and black hole growth phenomena.
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.
With upcoming all sky surveys such as LSST poised to generate a deep digital movie of the optical sky, variability-based AGN selection will enable the construction of highly-complete catalogs with minimum contamination. In this study, we generate $g$-band difference images and construct light curves for QSO/AGN candidates listed in SDSS Stripe 82 public catalogs compiled from different methods, including spectroscopy, optical colors, variability, and X-ray detection. Image differencing excels at identifying variable sources embedded in complex or blended emission regions such as Type II AGNs and other low-luminosity AGNs that may be omitted from traditional photometric or spectroscopic catalogs. To separate QSOs/AGNs from other sources using our difference image light curves, we explore several light curve statistics and parameterize optical variability by the characteristic damping timescale ($tau$) and variability amplitude. By virtue of distinguishable variability parameters of AGNs, we are able to select them with high completeness of 93.4% and efficiency (i.e., purity) of 71.3%. Based on optical variability, we also select highly variable blazar candidates, whose infrared colors are consistent with known blazars. One third of them are also radio detected. With the X-ray selected AGN candidates, we probe the optical variability of X-ray detected optically-extended sources using their difference image light curves for the first time. A combination of optical variability and X-ray detection enables us to select various types of host-dominated AGNs. Contrary to the AGN unification model prediction, two Type II AGN candidates (out of 6) show detectable variability on long-term timescales like typical Type I AGNs. This study will provide a baseline for future optical variability studies of extended sources.
We present our statistical analysis of the connection between active galactic nuclei (AGN) variability and physical properties of the central supermassive black hole (SMBH). We constructed optical light curves using data from the QUEST-La Silla AGN variability survey. To model the variability, we used the structure function, among the excess variance and the amplitude from Damp Random Walk (DRW) modeling. For the measurement of SMBH physical properties, we used public spectra from the Sloan Digital Sky Survey (SDSS). Our analysis is based on an original sample of 2345 sources detected in both SDSS and QUEST-La Silla. For 1473 of these sources we could perform a proper measurement of the spectral and variability properties, and 1348 of these sources were classified as variable ($91.5%$). We found that the amplitude of the variability ($A$) depends solely on the rest frame emission wavelength and the Eddington ratio, where $A$ anti-correlates with both $lambda_{rest}$ and $L/L_{text{Edd}}$. This suggests that AGN variability does not evolve over cosmic time, and its amplitude is inversely related to the accretion rate. We found that the logarithmic gradient of the variability ($gamma$) does not correlate significantly with any SMBH physical parameter, since there is no statistically significant linear regression model with an absolute value of the slope higher than 0.1. Finally, we found that the general distribution of $gamma$ measured for our sample differs from the distribution of $gamma$ obtained for light curves simulated from a DRW process. For 20.6% of the variable sources in our sample, a DRW model is not appropriate to describe the variability, since $gamma$ differs considerably from the expected value of 0.5.
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