Flexible and Scalable Methods for Quantifying Stochastic Variability in the Era of Massive Time-Domain Astronomical Data Sets

Kelly, Brandon C.; Becker, A. C.; Sobolewska, M.; Siemiginowska, Aneta; Uttley, P.

doi:10.1088/0004-637x/788/1/33

Cited by 263 publications

(423 citation statements)

References 68 publications

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“…Autoregressive processes, such as those used to describe quasar variability (Kelly et al 2014), have correlated (red) noise [characterized by a power spectrum of the form P(f) ∝ ν −2 ] which can introduce features in their time series, such as dips and humps (see Fig. 9).…”

Section: Mock Datamentioning

confidence: 99%

Understanding extreme quasar optical variability with CRTS – I. Major AGN flares

Graham¹,

Djorgovski²,

Drake³

et al. 2017

Monthly Notices of the Royal Astronomical Society

120

133

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There is a large degree of variety in the optical variability of quasars and it is unclear whether this is all attributable to a single (set of) physical mechanism(s). We present the results of a systematic search for major flares in active galactic nucleus (AGN) in the Catalina Real-time Transient Survey as part of a broader study into extreme quasar variability. Such flares are defined in a quantitative manner as being atop of the normal, stochastic variability of quasars. We have identified 51 events from over 900 000 known quasars and high-probability quasar candidates, typically lasting 900 d and with a median peak amplitude of m = 1.25 mag. Characterizing the flare profile with a Weibull distribution, we find that nine of the sources are well described by a single-point single-lens model. This supports the proposal by Lawrence et al. that microlensing is a plausible physical mechanism for extreme variability. However, we attribute the majority of our events to explosive stellar-related activity in the accretion disc: superluminous supernovae, tidal disruption events and mergers of stellar mass black holes.

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Section: Mock Datamentioning

confidence: 99%

Understanding extreme quasar optical variability with CRTS – I. Major AGN flares

Graham¹,

Djorgovski²,

Drake³

et al. 2017

Monthly Notices of the Royal Astronomical Society

120

133

View full text Add to dashboard Cite

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“…The existence of a break frequency and associated flattening of the slope at low frequencies is still unclear, with various studies suggesting breaks occuring at scales of anywhere from ∼10 to ∼ 1000 days or longer (Collier et al 2001, Kelly et al 2009, MacLeod et al 2010. Recently Kelly et al (2014) introduced a flexible algorithm to estimate the PSD of light curves in the context of a broad family of continuous-time autoregressive moving average processes, which also enables estimates of PSD for sparsely sampled data to be obtained.…”

Section: Nevencaplar@physethzch 1 Zwicky Fellowmentioning

confidence: 99%

“…We then investigate the connections between the optical variability and the physical properties of the AGNs in terms of luminosity, black hole mass and redshift. In general, we use time domain analysis, using the SF formalism, as well as new methods introduced in Kelly et al (2014) to study variability in the frequency domain.…”

Section: Nevencaplar@physethzch 1 Zwicky Fellowmentioning

confidence: 99%

“…While the SF 2 analysis was used on the ensemble of objects, the PSD analysis can be only used on individual light-curves. We will be using the code presented in Kelly et al (2014) that estimates the PSD of a light curve by modelling it as a continuous auto-regressive moving average (CARMA) process. This method is suitable for use even when using data with non-uniform time sampling with large gaps, as in (i)PTF.…”

Section: Wavelength Correctionmentioning

confidence: 99%

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OPTICAL VARIABILITY OF AGNs IN THE PTF/iPTF SURVEY

Čaplar

Lilly

Trakhtenbrot

2017

ApJ

116

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We characterize the optical variability of quasars in the intermediate Palomar Transient Factory (iPTF) and Palomar Transient Factory (PTF) surveys. We re-calibrate the r-band light curves for ∼28,000 luminous, broad-line AGNs from the SDSS, producing a total of ∼2.4 million photometric data points. We utilize both the structure function (SF) and power spectrum density (PSD) formalisms to search for links between the optical variability and the physical parameters of the accreting supermassive black holes that power the quasars. The excess variance (SF 2 ) of the quasar sample tends to zero at very short time separations, validating our re-calibration of the time-series data. We find that the the amplitude of variability at a given time-interval, or equivalently the time-scale of variability to reach a certain amplitude, is most strongly correlated with luminosity with weak or no dependence on black hole mass and redshift. For a variability level of SF(τ )=0.07 mag, the time-scale has a dependency of τ ∝ L 0.4 . This is broadly consistent with the expectation from a simple Keplerian accretion disk model, which provides τ ∝ L 0.5 . The PSD analysis also reveals that many quasar light curves are steeper than a damped random walk. We find a correlation between the steepness of the PSD slopes, specifically the fraction of slopes steeper than 2.5, and black hole mass, although we cannot exclude the possibility that luminosity or Eddington ratio are the drivers of this effect. This effect is also seen in the SF analysis of the (i)PTF data, and in a PSD analysis of quasars in the SDSS Stripe 82.

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“…By setting the PE power to β ≡ 1, the ACF becomes the one for the damped random walk (DRW) model (Kelly et al 2009;Koz lowski et al 2010;MacLeod et al 2010MacLeod et al , 2011MacLeod et al , 2012Butler & Bloom 2011;Ruan et al 2012;Zu et al 2011Zu et al , 2013Zu et al , 2016, which is the simplest of a broader class of continuous-time autoregressive moving average (CARMA) models (Kelly et al 2014). DRW is nowadays frequently used to model individual AGN light curves, although the PE power seems to be β > 1 for bright AGNs and/or massive black holes (Simm et al 2016; Koz lowski 2016a), causing biases in the measured DRW parameters (Koz lowski 2016b).…”

Section: Description Of Variabilitymentioning

confidence: 99%

A Method to Measure the Unbiased Decorrelation Timescale of the AGN Variable Signal from Structure Functions

Kozłowski

2017

ApJ

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A simple, model-independent method to quantify the stochastic variability of active galactic nuclei (AGNs) is the structure function (SF) analysis. If the SF for the timescales shorter than the decorrelation timescale τ is a single power-law and for the longer ones becomes flat (i.e., the white noise), the auto-correlation function (ACF) of the signal can have the form of the power exponential (PE). We show that the signal decorrelation timescale can be measured directly from the SF as the timescale matching the amplitude 0.795 of the flat SF part (at long timescales), and only then the measurement is independent of the ACF PE power. Typically, the timescale has been measured at an arbitrarily fixed SF amplitude, but as we prove, this approach provides biased results because the AGN SF/PSD slopes, so the ACF shape, are not constant and depend on either the AGN luminosity and/or the black hole mass. In particular, we show that using such a method for the simulated SFs that include a combination of empirically known dependencies between the AGN luminosity L and both the SF amplitude and the PE power, and having no intrinsic τ -L dependence, produces a fake τ ∝ L κ relation with 0.3 κ 0.6, that otherwise is expected from theoretical works (κ ≡ 0.5). Our method provides an alternative means for analyzing AGN variability to the standard SF fitting. The caveats, for both methods, are that the light curves must be sufficiently long (several years rest-frame) and the ensemble SF assumes AGNs to have the same underlying variability process.

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Flexible and Scalable Methods for Quantifying Stochastic Variability in the Era of Massive Time-Domain Astronomical Data Sets

Cited by 263 publications

References 68 publications

Understanding extreme quasar optical variability with CRTS – I. Major AGN flares

Understanding extreme quasar optical variability with CRTS – I. Major AGN flares

OPTICAL VARIABILITY OF AGNs IN THE PTF/iPTF SURVEY

A Method to Measure the Unbiased Decorrelation Timescale of the AGN Variable Signal from Structure Functions

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