Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches forSupermassive Black Hole Binaries in Time-Domain Surveys. (arXiv:2110.07465v1 [astro-ph.GA])

Quasars with Periodic Variability: Capabilities and Limitations of Bayesian Searches forSupermassive Black Hole Binaries in Time-Domain Surveys. (arXiv:2110.07465v1 [astro-ph.GA])
<a href="http://arxiv.org/find/astro-ph/1/au:+Witt_C/0/1/0/all/0/1">Caitlin A. Witt</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Charisi_M/0/1/0/all/0/1">Maria Charisi</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Taylor_S/0/1/0/all/0/1">Stephen R. Taylor</a>, <a href="http://arxiv.org/find/astro-ph/1/au:+Burke_Spolaor_S/0/1/0/all/0/1">Sarah Burke-Spolaor</a>

In this paper, we use Bayesian methods to disentangle periodic supermassive
black hole binary (SMBHB) signals from intrinsic damped random walk (DRW)
variability in AGN light curves. We simulated a wide variety of realistic DRW
and DRW+sine light curves. Their observed properties (cadence, gaps,
photometric uncertaintly) 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 investigate the range
of parameter space for which binary systems can be detected. We also examine
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, the amplitude of the signal is large, and the contribution of
the DRW noise is weak. We saw similar detection rates both in the CRTS and
LSST-like simulations. On the other hand, the false detection rate depends on
the quality of the data and is minimal in LSST, with every set of DRW
parameters being equally capable of producing false positives in CRTS. Our
idealized simulations provide an excellent way to uncover the intrinsic
limitations in quasar periodicity searches and set the stage for future
searches for supermassive black hole binaries.

In this paper, we use Bayesian methods to disentangle periodic supermassive
black hole binary (SMBHB) signals from intrinsic damped random walk (DRW)
variability in AGN light curves. We simulated a wide variety of realistic DRW
and DRW+sine light curves. Their observed properties (cadence, gaps,
photometric uncertaintly) 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 investigate the range
of parameter space for which binary systems can be detected. We also examine
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, the amplitude of the signal is large, and the contribution of
the DRW noise is weak. We saw similar detection rates both in the CRTS and
LSST-like simulations. On the other hand, the false detection rate depends on
the quality of the data and is minimal in LSST, with every set of DRW
parameters being equally capable of producing false positives in CRTS. Our
idealized simulations provide an excellent way to uncover the intrinsic
limitations in quasar periodicity searches and set the stage for future
searches for supermassive black hole binaries.

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