Light Curves Of Active Galactic Nuclei Research Articles

Using Gaussian Processes to detect AGN flares

ABSTRACT A key feature of active galactic nuclei (AGN) is their variability across all wavelengths. Typically, AGN vary by a few tenths of a magnitude or more over periods lasting from hours to years. By contrast, extreme variability of AGN – large luminosity changes that are a significant departure from the baseline variability – are known as AGN flares. These events are rare and their time-scales poorly constrained, with most of the literature focusing on individual events. It has been suggested that extreme AGN variability including flares can provide insights into the accretion processes in the disc. With surveys such as the Legacy Survey of Space and Time promising millions of transient detections per night in the coming decade, there is a need for fast and efficient classification of AGN flares. The problem with the systematic detection of AGN flares is the requirement to detect them against a stochastically variable baseline; the ability to define a signal as a significant departure from the ever-present variability is a statistical challenge. Recently, Gaussian Processes have revolutionized the analysis of time-series data in many areas of astronomical research. They have, however, seen limited uptake within the field of transient detection and classification. Here, we investigate the efficacy of Gaussian Processes to detect AGN flares in both simulated and real optical light curves. We show that GP analysis can successfully detect AGN flares with a false-positive rate of less than seven per cent, and we present examples of AGN light curves that show extreme variability.

Probing the roles of orientation and multiscale gas distributions in shaping the obscuration of active galactic nuclei through cosmic time

ABSTRACT The origin of obscuration in active galactic nuclei (AGNs) is still an open debate. In particular, it is unclear what drives the relative contributions to the line-of-sight column densities from galaxy-scale and torus-linked obscuration. The latter source is expected to play a significant role in Unification Models, while the former is thought to be relevant in both Unification and Evolutionary models. In this work, we make use of a combination of cosmological semi-analytic models and semi-empirical prescriptions for the properties of galaxies and AGN, to study AGN obscuration. We consider a detailed object-by-object modelling of AGN evolution, including different AGN light curves (LCs), gas density profiles, and also AGN feedback-induced gas cavities. Irrespective of our assumptions on specific AGN LC or galaxy gas fractions, we find that, on the strict assumption of an exponential profile for the gas component, galaxy-scale obscuration alone can hardly reproduce the fraction of log (NH/cm−2) ≥ 24 sources at least at z ≲ 3. This requires an additional torus component with a thickness that decreases with luminosity to match the data. The torus should be present in all evolutionary stages of a visible AGN to be effective, although galaxy-scale gas obscuration may be sufficient to reproduce the obscured fraction with 22 < log (NH/cm−2) < 24 (Compton-thin, CTN) if we assume extremely compact gas disc components. The claimed drop of CTN fractions with increasing luminosity does not appear to be a consequence of AGN feedback, but rather of gas reservoirs becoming more compact with decreasing stellar mass.

A Negative Long Lag from the Optical to the UV Continuum in Fairall 9

We report the detection of a long-timescale negative lag, where the blue bands lag the red bands, in the nearby Seyfert 1 galaxy Fairall 9, with two independent methods. Active Galactic Nuclei (AGNs) light curves show variability over a wide range of timescales. By measuring time lags between different wavelengths, the otherwise inaccessible structure and kinematics of the accretion disk can be studied. One common approach, reverberation mapping, quantifies the continuum and line lags moving outward through the disk at the light-travel time, revealing the size and temperature profile of the disk. Inspired by numerical simulations, we expect longer lags to exist in AGN light curves that travel inward on longer timescales, tracing the accretion process itself. By analyzing AGN light curves in both temporal and frequency space, we report the detection of long-timescale lags (∼−70 days) in Fairall 9 that propagate in the opposite direction to the reverberation lag. The short continuum lag (<10 days) is also detected and is consistent with reverberation lags reported in the literature. When fitting the longer lag as a function of frequency with a model motivated by the thin disk model, we find that the disk scale height likely increases outward in the disk. This detection raises the exciting prospect of mapping accretion disk structures across a wide range of AGN parameters.

Applying wavelet analysis to the X-ray light curves of active galactic nuclei and quasi-periodic eruptions

ABSTRACT In this work, we examine the application of the wavelet transform to the X-ray timing analyses of active galactic nuclei (AGN) and quasi-periodic eruption sources (QPEs). Several scenarios are simulated to test the effectiveness of the wavelet analysis to stationary and non-stationary data. We find that the power spectral density (PSD) slope and the nature of the periodic signal can influence the ability to identify important features in the wavelet power spectrum. In general, weak and transient features can be discerned, which make the wavelet spectrum an important tool in examining AGN light curves. We carried out a wavelet analysis to four unique objects: Ark 120, IRAS 13224-3809, RE J1034+396, and the QPE GSN 069. The well-known quasi-periodic oscillation (QPO) in RE J1034 + 396 is significantly detected in the wavelet power spectrum. In IRAS 13224-3809, significant transient features appear during a flare at frequencies coincident with previously detected reverberation signals. Finally, the wavelet power spectrum of the QPE GSN 069 significantly reveals four persistent signals that exhibit a 3:2 ratio in oscillation frequencies, consistent with high-frequency QPOs in stellar mass X-ray binaries, but we cannot rule out the possibility this is an artefact of the calculation.

Constraining AGN Torus Sizes with Optical and Mid-infrared Ensemble Structure Functions

We propose a new method to constrain the size of the dusty torus in broad-line active galactic nuclei (AGNs) using optical and mid-infrared (MIR) ensemble structure functions (SFs). Because of the geometric dilution of the torus, the MIR response to optical continuum variations has suppressed variability with respect to the optical that depends on the geometry (e.g., size, orientation, opening angle) of the torus. More extended tori have steeper MIR SFs with respect to the optical SFs. We demonstrate the feasibility of this SF approach using simulated AGN light curves and a geometric torus model. While it is difficult to use SFs to constrain the orientation and opening angle due to the insensitivity of the SF on these parameters, the size of the torus can be well determined. Applying this method to the ensemble SFs measured for 587 SDSS quasars, we measure a torus R–L relation of in the WISE W1 band and sizes ∼1.4 times larger in the W2 band, which are in good agreement with dust reverberation mapping measurements. Compared with the reverberation mapping technique, the SF method is much less demanding in data quality and can be applied to any optical+MIR light curves for which a lag measurement may not be possible, as long as the variability process and torus structure are stationary. While this SF method does not extract all information contained in the light curves (i.e., the transfer function), it provides an intuitive interpretation for the observed trends of AGN MIR SFs compared with optical SFs.

Simultaneous Millimeter-wave, Gamma-Ray, and Optical Monitoring of the Blazar PKS 2326-502 during a Flaring State

Including millimeter-wave data in multiwavelength studies of the variability of active galactic nuclei (AGN) can provide insights into AGN physics that are not easily accessible at other wavelengths. We demonstrate in this work the potential of cosmic microwave background (CMB) telescopes to provide long-term, high-cadence millimeter-wave AGN monitoring over large fractions of sky. We report on a pilot study using data from the SPTpol instrument on the South Pole Telescope (SPT), which was designed to observe the CMB at arcminute and larger angular scales. Between 2013 and 2016, SPTpol was used primarily to observe a single 500 deg2 field, covering the entire field several times per day with detectors sensitive to radiation in bands centered at 95 and 150 GHz. We use SPT 150 GHz observations to create AGN light curves, and we compare these millimeter-wave light curves to those at other wavelengths, in particular γ-ray and optical. In this Letter, we focus on a single source, PKS 2326-502, which has extensive, day-timescale monitoring data in gamma-ray, optical, and now millimeter-wave between 2013 and 2016. We find PKS 2326-502 to be in a flaring state in the first 2 yr of this monitoring, and we present a search for evidence of correlated variability between millimeter-wave, optical R-band, and γ-ray observations. This pilot study is paving the way for AGN monitoring with current and upcoming CMB experiments such as SPT-3G, Simons Observatory, and CMB-S4, including multiwavelength studies with facilities such as Vera C. Rubin Observatories Large Synoptic Survey Telescope.

Active Galactic Nucleus Variability in the Age of Rubin

Over the next 10 years, the Vera C. Rubin Observatory (Rubin) will observe ∼10 million active galactic nuclei (AGNs) with a regular and high cadence. During this time, the intensities of most of these AGNs will fluctuate stochastically. Here, we explore the prospects to quantify precisely these fluctuations with Rubin measurements of AGN light curves. To do so, we suppose that each light curve is described by a damped random walk with a given fluctuation amplitude and correlation time. Theoretical arguments and some current measurements suggest that the correlation timescale and fluctuation amplitude for each AGN may be correlated with other observables. We use an expected-information analysis to calculate the precision with which these parameters will be inferred from the measured light curves. We find that the measurements will be so precise as to allow the AGNs to be separated into up to ∼10 different correlation-timescale bins. We then show that if the correlation time varies as some power of the luminosity, the normalization and power-law index of that relation will be determined to . These results suggest that with Rubin, precisely measured variability parameters will take their place alongside spectroscopy in the detailed characterization of individual AGNs and in the study of AGN population statistics. Analogous analyses will be enabled by other time-domain projects, such as CMB-S4.

Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches for Supermassive Black Hole Binaries in Time-domain Surveys

Supermassive black hole binaries (SMBHBs) are an inevitable consequence of galaxy mergers. At sub-parsec separations, they are practically impossible to resolve, and the most promising technique is to search for quasars with periodic variability. However, searches for quasar periodicity in time-domain data are challenging due to the stochastic variability of quasars. In this paper, we used Bayesian methods to disentangle periodic SMBHB signals from intrinsic damped random walk (DRW) variability in active galactic nuclei light curves. We simulated a wide variety of realistic DRW and DRW+sine light curves. Their observed properties are modeled after the Catalina Real-time Transient Survey (CRTS) and expected properties of the upcoming Legacy Survey of Space and Time (LSST) from the Vera C. Rubin Observatory. Through a careful analysis of parameter estimation and Bayesian model selection, we investigated the range of parameter space for which binary systems can be detected. We also examined which DRW signals can mimic periodicity and be falsely classified as binary candidates. We found that periodic signals are more easily detectable if the period is short or the amplitude of the signal is large compared to the contribution of the DRW noise. We saw similar detection rates both in the CRTS and LSST-like simulations, while the false-detection rate depends on the quality of the data and is minimal in LSST. Our idealized simulations provide an excellent way to uncover the intrinsic limitations in quasar periodicity searches and set the stage for future searches for SMBHBs.

Legacy Survey of Space and Time cadence strategy evaluations for active galactic nucleus time-series data in Wide-Fast-Deep field

ABSTRACT Machine learning is a promising tool to reconstruct time-series phenomena, such as variability of active galactic nuclei (AGNs), from sparsely sampled data. Here, we use three Continuous Autoregressive Moving Average (CARMA) representations of AGN variability – the Damped Random Walk (DRW) and (over/under)Damped Harmonic Oscillator – to simulate 10-yr AGN light curves as they would appear in the upcoming Vera Rubin Observatory Legacy Survey of Space and Time (LSST), and provide a public tool to generate these for any survey cadence. We investigate the impact on AGN science of five proposed cadence strategies for LSST’s primary Wide-Fast-Deep (WFD) survey. We apply for the first time in astronomy a novel Stochastic Recurrent Neural Network (SRNN) algorithm to reconstruct input light curves from the simulated LSST data, and provide a metric to evaluate how well SRNN can help recover the underlying CARMA parameters. We find that the light-curve reconstruction is most sensitive to the duration of gaps between observing season, and that of the proposed cadences, those that change the balance between filters, or avoid having long gaps in the g band perform better. Overall, SRNN is a promising means to reconstruct densely sampled AGN light curves and recover the long-term structure function of the DRW process (SF∞) reasonably well. However, we find that for all cadences, CARMA/SRNN models struggle to recover the decorrelation time-scale (τ) due to the long gaps in survey observations. This may indicate a major limitation in using LSST WFD data for AGN variability science.

Conditional Neural Process for nonparametric modeling of active galactic nuclei light curves

AbstractThe consequences of complex disturbed environments in the vicinity of a supermassive black hole are not well represented by standard statistical models of optical variability in active galactic nuclei (AGN). Thus, developing new methodologies for investigating and modeling AGN light curves is crucial. Conditional Neural Processes (CNPs) are nonlinear function models that forecast stochastic time series based on a finite amount of known data without the use of any additional parameters or prior knowledge (kernels). We provide a CNP algorithm that is specifically designed for simulating AGN light curves. It was trained using data from the All‐Sky Automated Survey for Supernovae, which included 153 AGN. We present CNP modeling performance for a subsample of five AGNs with distinctive difficult‐to‐model properties. The performance of CNP in predicting temporal flux fluctuation was assessed using a minimizing loss function, and the results demonstrated the algorithm's usefulness. Our preliminary parallelization experiments show that CNP can efficiently handle large amounts of data. These results imply that CNP can be more effective than standard tools in modeling large volumes of AGN data (as anticipated from time‐domain surveys such as the Vera C. Rubin Observatory's Legacy Survey of Space and Time).

Photoreverberation mapping of quasars in the context of Legacy Survey of Space and Time observing strategies

AbstractThe upcoming photometric surveys, such as the Rubin Observatory's Legacy Survey of Space and Time (LSST) will monitor unprecedented number of active galactic nuclei (AGN) in a decade‐long campaign. Motivated by the science goals of LSST, which includes the harnessing of broadband light curves of AGN for photometric reverberation mapping (PhotoRM), we implement the existing formalism to estimate the lagged response of the emission line flux to the continuum variability using only multi‐band photometric light curves. We test the PhotoRM method on a set of 19 artificial light curves simulated using a stochastic model based on the damped random walk process. These light curves are sampled using different observing strategies, including the two proposed by the LSST, in order to compare the accuracy of time‐lag retrieval based on different observing cadences. In addition, we apply the same procedure for time‐lag retrieval to the observed photometric light curves of NGC 4395, and compare our results to the existing literature.

Properties of a Previously Unidentified Instrumental Signature in Kepler/K2 That was Confused for AGN Variability

Abstract The Kepler satellite potentially provides the highest precision photometry of active galactic nuclei (AGNs) available to investigate short-timescale optical variability. We targeted quasars from the Sloan Digital Sky Survey that lie in the fields of view of the Kepler/K2 campaigns. Based on those observations, we report the discovery and properties of a previously unidentified instrumental signature in K2. Systematic errors in K2, beyond those due to the motion of the detector, plague our AGNs and other faint-target, guest observer science proposals. Weakly illuminated pixels are dominated by low-frequency trends that are both nonastrophysical and correlated from object to object. The instrumental signature lags in time as a function of radius from the center of the detector, crossing channel boundaries. Thus, systematics documented in this investigation are unlikely to be due to Moiré noise, rolling band, or pointing jitter. A critical clue to understanding this instrumental systematic is that different targets observed in the same channels of Campaign 8 (rear facing) and Campaign 16 (forward facing) have nearly identical light curves after time reversal of one of the campaigns. We find evidence of temperature trends that also reverse according to the Sun–spacecraft field orientation and that may dominate the systematics. These temperature variations are larger in K2 than in the nominal Kepler mission and strongly support our hypothesis of temperature-driven focus changes. Further characterization of this signature is crucial for rehabilitating K2 data for use in investigations of AGN light curves.

Searching for Changing-state AGNs in Massive Data Sets. I. Applying Deep Learning and Anomaly-detection Techniques to Find AGNs with Anomalous Variability Behaviors

Abstract The classic classification scheme for active galactic nuclei (AGNs) was recently challenged by the discovery of the so-called changing-state (changing-look) AGNs. The physical mechanism behind this phenomenon is still a matter of open debate and the samples are too small and of serendipitous nature to provide robust answers. In order to tackle this problem, we need to design methods that are able to detect AGNs right in the act of changing state. Here we present an anomaly-detection technique designed to identify AGN light curves with anomalous behaviors in massive data sets. The main aim of this technique is to identify CSAGN at different stages of the transition, but it can also be used for more general purposes, such as cleaning massive data sets for AGN variability analyses. We used light curves from the Zwicky Transient Facility data release 5 (ZTF DR5), containing a sample of 230,451 AGNs of different classes. The ZTF DR5 light curves were modeled with a Variational Recurrent Autoencoder (VRAE) architecture, that allowed us to obtain a set of attributes from the VRAE latent space that describes the general behavior of our sample. These attributes were then used as features for an Isolation Forest (IF) algorithm that is an anomaly detector for a “one class” kind of problem. We used the VRAE reconstruction errors and the IF anomaly score to select a sample of 8809 anomalies. These anomalies are dominated by bogus candidates, but we were able to identify 75 promising CSAGN candidates.

On possible proxies of AGN light-curves cadence selection in future time domain surveys

ABSTRACT Motivated by upcoming photometric and spectroscopic surveys [Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), Manuakea Spectroscopic Explorer], we design the statistical proxies to measure the cadence effects on active galactic nuclei (AGNs) variability-observables [time-lags, periodicity, and structure-function (SF)]. We constructed a multiple-regression model to statistically identify the cadence-formal error pattern knowing AGN time-lags and periodicity from different surveys. We defined the simple metric for the SF’s properties, accounting for the ‘observed’ SF’s deviation relative to those obtained from the homogenously sampled light curves. We tested the regression models on different observing strategies: the optical data set of long light curves of eight AGN with peculiarities and the artificial data sets based on several idealized and LSST-like cadences. The SFs metric is assessed on synthetic data sets. The regression models (for both data types) predict similar cadences for time-lags and oscillation detection, whereas for light curves with low variability (${\sim}10{{\ \rm per\ cent}}$), cadences for oscillation detection differ. For higher variability (${\sim}20{{\ \rm per\ cent}}$), predicted cadences are larger than for $F_{var}\sim 10{{\ \rm per\ cent}}$. The predicted cadences are decreasing with redshift. SFs with dense and homogenous cadences are more likely to behave similarly. SFs with oscillatory signals are sensitive to the cadences, possibly impacting LSST-like operation strategy. The proposed proxies can help to select spectroscopic and photometric-surveys cadence strategies, and they will be tested further in larger samples of objects.

Detecting nonlinearity in the light curves of active galactic nuclei

This paper discusses a statistical method of detecting nonlinearity in the light curves of active galactic nuclei (AGN). We model the light curves of AGN by two-variate stochastic differential equation (SDE) in which one variable is observable but not the other. Applying a nonparametric model of the SDE as well as its parametric models of linear and quadratic functions to the light curves provided by the Kepler satellite, we estimate the three models and thereby compare their prediction accuracy to detect nonlinearity. The results suggest that there exist quadratic or other nonlinearities in the light curves, while the others exhibit linearity.

A QPO in NGC 4945 from Archival RXTE Data

Abstract We report the discovery of an ∼6 week quasi-periodic oscillation (QPO) in archival NGC 4945 data observed by the Rossi X-ray Timing Explorer (RXTE) satellite. QPOs are important observables in accretion disks and have been studied extensively in both neutron star (NS) and black hole (BH) X-ray binaries (XRB). QPOs should be present in active galactic nuclei (AGN) if galactic BHs and supermassive black holes are governed by a common set of physical processes. The search for QPOs in AGN has proven difficult because the time scales would be much longer, due to their higher mass. RXTE AGN light curves spanning 1996 to 2011 provide an excellent and perhaps unique opportunity to search for low-frequency QPOs. We investigated the 533 RXTE observations made of the Seyfert-2 AGN, NGC 4945. During a large cluster of observations in 2006–2007 (194 observations, spanning 396 days), the Lomb–Scargle periodogram shows a candidate QPO at 0.274 μHz (period ≈42.2 days). We estimate the uncertainties using the false alarm probability. We discuss the possible identification of this feature with the Lense–Thirring precession period.

Complex variability of Kepler AGN revealed by recurrence analysis

ABSTRACT The advent of new time domain surveys and the imminent increase in astronomical data expose the shortcomings of traditional time series analysis (such as power spectra analysis) in characterizing the abundantly varied, complex, and stochastic light curves of Active Galactic Nuclei (AGNs). Recent applications of novel methods from non-linear dynamics have shown promise in characterizing 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 dynamical trajectories in phase space, which can be constructed from 1D 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 to 60 d 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 realizations of a linear stochastic process describe 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.

On the Time Scales of Optical Variability of AGN and the Shape of Their Optical Emission Line Profiles

The mechanism of the optical variability of active galactic nuclei (AGN) is still very puzzling. It is now widely accepted that the optical variability of AGN is stochastic, producing red noise-like light curves. In case they were to be periodic or quasi-periodic, one should expect that the time scales of optical AGN variability should relate to orbiting time scales of regions inside the accretion disks with temperatures mainly emitting the light in this wavelength range. Knowing the reverberation scales and masses of AGN, expected orbiting time scales are in the order of decades. Unfortunately, most of monitored AGN light curves are not long enough to investigate such time scales of periodicity. Here we investigate the AGN optical variability time scales and their possible connections with the broad emission line shapes.

The Kepler Light Curves of AGN: A Detailed Analysis

Abstract We present a comprehensive analysis of 21 light curves of Type 1 active galactic nuclei (AGN) from the Kepler spacecraft. First, we describe the necessity and development of a customized pipeline for treating Kepler data of stochastically variable sources like AGN. We then present the light curves, power spectral density functions (PSDs), and flux histograms. The light curves display an astonishing variety of behaviors, many of which would not be detected in ground-based studies, including switching between distinct flux levels. Six objects exhibit PSD flattening at characteristic timescales that roughly correlate with black hole mass. These timescales are consistent with orbital timescales or free-fall accretion timescales. We check for correlations of variability and high-frequency PSD slope with accretion rate, black hole mass, redshift, and luminosity. We find that bolometric luminosity is anticorrelated with both variability and steepness of the PSD slope. We do not find evidence of the linear rms–flux relationships or lognormal flux distributions found in X-ray AGN light curves, indicating that reprocessing is not a significant contributor to optical variability at the 0.1%–10% level.

A model for AGN variability on multiple time-scales

Abstract We present a framework to link and describe active galactic nuclei (AGN) variability on a wide range of time-scales, 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 time-scales 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/LEdd) distribution. Motivated by general galaxy population properties, we propose that the PDF may be inspired by the L/LEdd 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 time-scales, therefore providing new insights into AGN variability and black hole growth phenomena.