Based on an updated Hβ reverberation mapping (RM) sample of 44 nearby active galactic nuclei (AGNs), we propose a novel approach for black hole (BH) mass estimation using two filtered luminosities computed from single-epoch (SE) AGN spectra around the Hβ region. We found that the two optimal-filter luminosities extract virial information (size and virial velocity of the broad-line region, BLR) from the spectra, justifying their usage in this empirical BH mass estimator. The major advantages of this new recipe over traditional SE BH mass estimators utilizing continuum luminosity and broad-line width are (1) it has a smaller intrinsic scatter of 0.28 dex calibrated against RM masses, (2) it is extremely simple to use in practice, without any need to decompose the spectrum, and (3) it produces unambiguous and highly repeatable results even with low signal-to-noise spectra. The combination of the two luminosities can also cancel out, to some extent, systematic luminosity errors potentially introduced by uncertainties in distance or flux calibration. In addition, we recalibrated the traditional SE mass estimators using broad Hβ FWHM and monochromatic continuum luminosity at 5100 Å (L 5100). We found that using the best-fit slopes on FWHM and L 5100(derived from fitting the BLR radius-luminosity relation and the correlation between rms line dispersion and SE FWHM, respectively) rather than simple assumptions (e.g., 0.5 for L 5100and 2 for FWHM) leads to more precise SE mass estimates, improving the intrinsic scatter from 0.41 dex to 0.36 dex with respect to the RM masses. We compared different estimators and discussed their applications to the Sloan Digital Sky Survey quasar sample. Due to the limitations of the current RM sample, application of any SE recipe calibrated against RM masses to distant quasars should be treated with caution.
CITATION STYLE
Feng, H., Shen, Y., & Li, H. (2014). Single-epoch black hole mass estimators for broad-line active galactic nuclei: Recalibrating hβ with a new approach. Astrophysical Journal, 794(1). https://doi.org/10.1088/0004-637X/794/1/77
Mendeley helps you to discover research relevant for your work.