False periodicities in quasar time-domain surveys

TL;DR

This paper demonstrates that apparent periodicities in quasar light curves, such as PG 1302-102, can often be false positives caused by stochastic red noise, emphasizing the need for careful statistical analysis.

Contribution

It shows that stochastic variability can mimic periodic signals in quasar data and highlights the importance of calibrating false positive rates in large surveys.

Findings

Many stochastic simulations show false periodicity similar to observed signals.

Bayesian analysis favors stochastic models over sinusoidal ones for PG 1302-102.

Calibrating false positive rates is crucial in large-scale periodicity searches.

Abstract

There have recently been several reports of apparently periodic variations in the light curves of quasars, e.g. PG 1302-102 by Graham et al. (2015a). Any quasar showing periodic oscillations in brightness would be a strong candidate to be a close binary supermassive black hole and, in turn, a candidate for gravitational wave studies. However, normal quasars -- powered by accretion onto a single, supermassive black hole -- usually show stochastic variability over a wide range of timescales. It is therefore important to carefully assess the methods for identifying periodic candidates from among a population dominated by stochastic variability. Using a Bayesian analysis of the light curve of PG 1302-102, we find that a simple stochastic process is preferred over a sinusoidal variations. We then discuss some of the problems one encounters when searching for rare, strictly periodic signals among a large number of irregularly sampled, stochastic time series, and use simulations of quasar light curves to illustrate these points. From a few thousand simulations of steep spectrum (`red noise') stochastic processes, we find many simulations that display few-cycle periodicity like that seen in PG 1302-102. We emphasise the importance of calibrating the false positive rate when the number of targets in a search is very large.