Automated Measurement of Quasar Redshift with a Gaussian Process (2020)

by Leah Fauber, Ming-Feng Ho, Simeon Bird, Christian R. Shelton, Roman Garnett, and Ishita Korde

Abstract: We develop an automated technique to measure quasar redshifts in the Baryon Oscillation Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS). Our technique is an extension of an earlier Gaussian process method for detecting damped Lyman-α absorbers (DLAs) in quasar spectra with known redshifts. We apply this technique to a subsample of SDSS DR12 with BAL quasars removed and redshift larger than 2.15. We show that we are broadly competitive to existing quasar redshift estimators, disagreeing with the PCA redshift by more than 0.5 in only 0.38% of spectra. Our method produces a probabilistic density function for the quasar redshift, allowing quasar redshift uncertainty to be propagated to downstream users. We apply this method to detecting DLAs, accounting in a Bayesian fashion for redshift uncertainty. Compared to our earlier method with a known quasar redshift, we have a moderate decrease in our ability to detect DLAs, predominantly in the noisiest spectra. The area under curve drops from 0.96 to 0.91. Our code is publicly available.

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Leah Fauber, Ming-Feng Ho, Simeon Bird, Christian R. Shelton, Roman Garnett, and Ishita Korde (2020). "Automated Measurement of Quasar Redshift with a Gaussian Process." Monthly Notices of the Royal Astronomical Society.

Bibtex citation

@article{Fauetal20,
     author = "Leah Fauber and Ming-Feng Ho and Simeon Bird and Christian R. Shelton and Roman Garnett and Ishita Korde",
     title = "Automated Measurement of Quasar Redshift with a {G}aussian Process",
     journal = "Monthly Notices of the Royal Astronomical Society",
     year = 2020,
   month = 09,
   issn = "0035-8711",
   doi = {10.1093/mnras/staa2826},
}

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