Measurement of AGN dust extinction based on the near-infrared flux variability of WISE data

Abstract

We present the measurement of the line-of-sight extinction of the dusty torus for a large number of obscured active galactic nuclei (AGNs) based on the reddening of the colour of the variable flux component in near-infrared (NIR) wavelengths. We collected long-term monitoring data by $\text{Wide-field Infrared Survey Explorer (WISE)}$ for 513 local AGNs catalogued by the $Swift/$BAT AGN Spectroscopic Survey (BASS) and found that the multi-epoch NIR flux data in two different bands (WISE $W1$ and $W2$) are tightly correlated for more than 90% of the targets. The flux variation gradient (FVG) in the $W1$ and $W2$ bands was derived by applying linear regression analysis, and we reported that those for unobscured AGNs fall in a relatively narrow range, whereas those for obscured AGNs are distributed in a redder and broader range. The AGN's line-of-sight dust extinction ($A_V$) is calculated using the amount of the reddening in the FVG and is compared with the neutral hydrogen column density ($N_{\mathrm{H}}$) of the BASS catalogue. We found that the $N_{\mathrm{H}}/A_V$ ratios of obscured AGNs are greater than those of the Galactic diffuse interstellar medium (ISM) and are distributed with a large scatter by at most two orders of magnitude. Furthermore, we found that the lower envelope of the $N_{\mathrm{H}}/A_V$ of obscured AGNs is comparable to the Galactic diffuse ISM. These properties of the $N_{\mathrm{H}}/A_V$ can be explained by increase in the $N_{\mathrm{H}}$ attributed to the dust-free gas clouds covering the line of sight in the broad-line region.

arXiv comment11 pages, 7 figures, published in MNRAS

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• Updated Picture of the Active Galactic Nuclei with Dusty/Dust-free Gas Structures and Effects of the Radiation Pressure
• A New Mid-Infrared and X-ray Machine Learning Algorithm to Discover Compton-thick AGN
• The Host Galaxy Fluxes of Active Galaxy Nuclei Are Generally Overestimated by the Flux Variation Gradient Method