Abstract

Reverberation mapping (RM) is an important technique in studies of active galactic nuclei (AGN). The key idea of RM is to measure the time lag ττ between variations in the continuum emission from the accretion disc and subsequent response of the broad line region (BLR). The measurement of ττ is typically used to estimate the physical size of the BLR and is combined with other measurements to estimate the black hole mass MBHM_{\rm BH}. A major difficulty with RM campaigns is the large amount of data needed to measure ττ. Recently, Fine et al (2012) introduced a new approach to RM where the BLR light curve is sparsely sampled, but this is counteracted by observing a large sample of AGN, rather than a single system. The results are combined to infer properties of the sample of AGN. In this letter we implement this method using a hierarchical Bayesian model and contrast this with the results from the previous stacked cross-correlation technique. We find that our inferences are more precise and allow for more straightforward interpretation than the stacked cross-correlation results.

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