A New Approach for Measuring Power Spectra and Reconstructing Time Series in Active Galactic Nuclei

Abstract

We provide a new approach to measure power spectra and reconstruct time series in active galactic nuclei (AGNs) based on the fact that the Fourier transform of AGN stochastic variations is a series of complex Gaussian random variables. The approach parameterizes a stochastic series in frequency domain and transforms it back to time domain to fit the observed data. The parameters and their uncertainties are derived in a Bayesian framework, which also allows us to compare the relative merits of different power spectral density models. The well-developed fast Fourier transform algorithm together with parallel computation enable an acceptable time complexity for the approach.

5 pages, 4 figures; accepted to MNRAS Letter; software available at https://github.com/LiyrAstroph/RECON

References in corpus (4)

• Modeling reverberation mapping data I: improved geometric and dynamical models and comparison with cross-correlation results
• Limitations on the recovery of the true AGN variability parameters using Damped Random Walk modeling
• A Bayesian Method for the Intercalibration of Spectra in Reverberation Mapping
• A Method to Measure the Unbiased Decorrelation Timescale of the AGN Variable Signal from Structure Functions

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• Differential Interferometric Signatures of Close Binaries of Supermassive Black Holes in Active Galactic Nuclei: II. Merged Broad Line Regions
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