A deep learning approach to quasar continuum prediction

@article{Liu2020ADL,
  title={A deep learning approach to quasar continuum prediction},
  author={Bin Liu and Rongmon Bordoloi},
  journal={arXiv: Astrophysics of Galaxies},
  year={2020}
}
We present a novel deep learning model, intelligent quasar continuum neural network (iQNet), which predicts the intrinsic continuum of any quasar in the rest-frame wavelength range 1020 Angstroms $\leq \lambda \leq$ 1600 Angstroms. We train this network using quasar spectra at low redshift ($z \sim 0.2$) from the Hubble Spectroscopic Legacy Archive, and apply it to predict quasar continua from different astronomical surveys. We introduce a standardization process to the data, reducing the… 
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TLDR
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