Application of Stochastic Modeling to Analysis of Photometric Reverberation Mapping Data

Abstract

We use both simulated and real quasar light curves to explore modeling photometric reverberation-mapping (RM) data as a stochastic process. We do this using modifications to our previously developed RM method based on modeling quasar variability as a damped random walk. We consider the feasibility of one and two-band photometric RM and compare the results with those fr om spectroscopic RM. We find that our method for two-band photometric RM can be competitive with spectroscopic RM only for strong (large equivalent width) lines like Halpha and Hbeta, and that the one-band method is also feasible, but requires very high-precision photometry. We fail to robustly detect Halpha lags in single-band quasar light curves from OGLE-III and IV despite the outstanding cadence and time span of the data, on account of photometric uncertainties in the range 0.02-0.04 mag. Simulations suggest that success could be achieved if the photometric uncertainties were of order 0.01 mag. Single-band RM for all lines and two-band RM for lower equivalent width lines are likely only feasible for statistical estimate s of mean lags for large samples of AGN of similar properties (e.g., luminosity) rather than for individual quasars. Our approach is directly applicable to the time-domain programs within ongoing and future wide-field imaging surveys, and could provide robust lag measurements for an unprecedented number of systems.

ApJ accepted; code available at https://bitbucket.org/nye17/javelin