Abstract One of the hallmarks of active galactic nuclei is that they are highly variable with time. In watching the spectra vary it has been observed that the emission lines often appear to “reverberate”—that is they vary in response to continuum variations assumed to originate close to the black hole. This critical observation underlies the reverberation mapping technique, an elegant physics experiment that has allowed us to characterize the environment around many supermassive black holes in nearby active galactic nuclei. Recent observations are of such quality that the response can be measured as a function of velocity across the emission line, and in doing so we can construct velocity-delay maps that show the structure and physics of the gas in the broad-line region better than any other measurement to date. Unfortunately, constructing such maps requires a deconvolution, and given that the data are often noisy and with gaps such deconvolutions are nontrivial. Here we present a novel deconvolution method for the recovery of velocity-delay maps using a custom convolutional neural network architecture, showcasing that such methods have great promise for the deconvolution of reverberation mapping data products. While we have designed this new method with the BLR in mind, in principle this technique could be applied to any reverberation deconvolution problem, including in the accretion disk and torus.
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TLDR: time lag/delay reconstructor
ABSTRACT We present the time lag/delay reconstructor (TLDR), an algorithm for reconstructing velocity delay maps in the maximum a posteriori framework for reverberation mapping. Reverberation mapping is a tomographical method for studying the kinematics and geometry of the broad-line region of active galactic nuclei at high spatial resolution. Leveraging modern image reconstruction techniques, including total variation and compressed sensing, TLDR applies multiple regularization schemes to reconstruct velocity delay maps using the alternating direction method of multipliers. Along with the detailed description of the TLDR algorithm we present test reconstructions from TLDR applied to synthetic reverberation mapping spectra as well as a preliminary reconstruction of the Hβ feature of Arp 151 from the 2008 Lick Active Galactic Nuclei Monitoring Project.
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- Award ID(s):
- 2009230
- PAR ID:
- 10275821
- Date Published:
- Journal Name:
- Monthly Notices of the Royal Astronomical Society
- Volume:
- 505
- Issue:
- 2
- ISSN:
- 0035-8711
- Page Range / eLocation ID:
- 2903 to 2912
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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