APPLICATION OF STOCHASTIC MODELING TO ANALYSIS OF PHOTOMETRIC REVERBERATION MAPPING DATA

• Published in: The Astrophysical journal Vol. 819; no. 2; pp. 122 - 133
• Main Authors: Zu, Ying, Kochanek, C. S., Koz owski, Szymon, Peterson, B. M.
• Format: Journal Article
• Language: English
• Published: The American Astronomical Society 10-03-2016
• Subjects: Equivalence; galaxies: active; galaxies: statistics; methods: data analysis; methods: numerical; methods: statistical; Modelling; Photometry; Quasars; Samples; Spectroscopy; Statistical methods; Uncertainty
• ISSN: 0004-637X; 1538-4357
• DOI: 10.3847/0004-637X/819/2/122

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 from 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 H and Hβ, and that the one-band method is also feasible but requires very high precision photometry. We fail to robustly detect H lags in single-band quasar light curves from OGLE-III and OGLE-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 estimates of mean lags for large samples of active galactic nuclei 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.