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The variability of active galaxies: I. Broad-band noise X-ray power spectra from XMM-Newton and Swift

Mehdy Lefkir, Simon Vaughan, Mike Goad, Daniela Huppenkothen, Phil Uttley

TL;DR

This study analyzes long-term soft X-ray variability in 56 unabsorbed AGN using XMM-Newton and Swift data and a Gaussian-process-based method called PIORAN to estimate bending power spectra. Bend frequencies span from roughly $7\ ext{min}$ to $62\ ext{days}$, with high-frequency slopes typically $\alpha_2>2$, and low-frequency bends detected in several sources, including new ones. The bend timescale scales approximately linearly with black hole mass $M_{ m BH}$ and shows only a weak dependence on luminosity, after accounting for mass, with intrinsic scatter indicating additional drivers or non-stationarity. The results align with MRI/GRMHD expectations for inner-disk variability and reveal parallels and distinctions with BH X-ray binaries, while highlighting the need for future UV/optical timing and more complex QPO modeling. Overall, the work provides a comprehensive, model-based reanalysis of AGN timing that enhances the X-ray variability plane and informs disk-physics interpretations.

Abstract

Accreting supermassive black holes at the centres of galaxies are the engine of active galactic nuclei (AGN). X-ray light curves of unabsorbed AGN show dramatic random variability on timescales ranging from seconds to years. The power spectrum of the fluctuations is usually well-modelled with a power law that decays as $1/f$ at low frequencies, and which bends to $1/f^{2-3}$ at high frequencies. The timescale associated with the bend correlates well with the mass of the black hole and may also correlate with bolometric luminosity in the `X-ray variability plane'. Because AGN light curves are usually irregularly sampled, the estimation of AGN power spectra is challenging. In a previous paper, we introduced a new method to estimate the parameters of bending power law power spectra from AGN light curves. We apply this method to a sample of 56 variable and unabsorbed AGN, observed with XMM-Newton and Swift in the $0.3-1.5$ keV band over the past two decades. We obtain estimates of the bends in 50 sources, which is the largest sample of X-ray bends in the soft band. We also find that the high-frequency power spectrum is often steeper than 2. We update the X-ray variability plane with new bend timescale measurements spanning from 7 min to 62 days. We report the detections of low-frequency bends in the power spectra of five AGN, three of which are previously unpublished: 1H 1934-063, Mkn 766 and Mkn 279.

The variability of active galaxies: I. Broad-band noise X-ray power spectra from XMM-Newton and Swift

TL;DR

This study analyzes long-term soft X-ray variability in 56 unabsorbed AGN using XMM-Newton and Swift data and a Gaussian-process-based method called PIORAN to estimate bending power spectra. Bend frequencies span from roughly to , with high-frequency slopes typically , and low-frequency bends detected in several sources, including new ones. The bend timescale scales approximately linearly with black hole mass and shows only a weak dependence on luminosity, after accounting for mass, with intrinsic scatter indicating additional drivers or non-stationarity. The results align with MRI/GRMHD expectations for inner-disk variability and reveal parallels and distinctions with BH X-ray binaries, while highlighting the need for future UV/optical timing and more complex QPO modeling. Overall, the work provides a comprehensive, model-based reanalysis of AGN timing that enhances the X-ray variability plane and informs disk-physics interpretations.

Abstract

Accreting supermassive black holes at the centres of galaxies are the engine of active galactic nuclei (AGN). X-ray light curves of unabsorbed AGN show dramatic random variability on timescales ranging from seconds to years. The power spectrum of the fluctuations is usually well-modelled with a power law that decays as at low frequencies, and which bends to at high frequencies. The timescale associated with the bend correlates well with the mass of the black hole and may also correlate with bolometric luminosity in the `X-ray variability plane'. Because AGN light curves are usually irregularly sampled, the estimation of AGN power spectra is challenging. In a previous paper, we introduced a new method to estimate the parameters of bending power law power spectra from AGN light curves. We apply this method to a sample of 56 variable and unabsorbed AGN, observed with XMM-Newton and Swift in the keV band over the past two decades. We obtain estimates of the bends in 50 sources, which is the largest sample of X-ray bends in the soft band. We also find that the high-frequency power spectrum is often steeper than 2. We update the X-ray variability plane with new bend timescale measurements spanning from 7 min to 62 days. We report the detections of low-frequency bends in the power spectra of five AGN, three of which are previously unpublished: 1H 1934-063, Mkn 766 and Mkn 279.
Paper Structure (32 sections, 7 equations, 10 figures, 1 table)

This paper contains 32 sections, 7 equations, 10 figures, 1 table.

Figures (10)

  • Figure 1: Light curves and power spectral densities for Fairall 9, NGC 7469, NGC 4748 and 1H 1934-063. The sources are identified by a similar colour in all panels.
  • Figure 2: Correlations between the black hole mass, optical luminosity, $2-6$ keV X-ray luminosity and the median value of the bend timescale $t_1$, low-frequency slope $\alpha_1$, high-frequency slope $\alpha_2$, power spectrum at the bend frequency, power spectrum at the bend frequency times bend frequency, integral of power spectrum model and average rms amplitude of variability $F_\mathrm{var}$ computed over segments of $30$ ks from XMM--Newton light curves. The distribution of each quantity are plotted in the upper and right panels.
  • Figure 3: Posterior power spectra of the sources with evidence for two bends. The shaded areas correspond to the $68\%$ and $95\%$ percentiles from the posterior distributions. As we are mainly interested in the general shape and not total power, the amplitudes of individual sources have been rescaled for plotting purposes.
  • Figure 4: Distribution of the power spectral parameters for sources with evidence of a second bend. $f_2/f_1$ is the ratio between the high- and low-frequency bends and $\alpha_i$ for $i\in[1,2,3]$ are the slopes of the bending power law model.
  • Figure 5: X-ray variability plane for all sources. For sources with detection of low-frequency bend, we use the high-frequency bend.
  • ...and 5 more figures