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-alpha absorbers (DLAs) in quasar spectra with known
redshifts. We show that we are competitive to existing quasar redshift
estimators. Importantly 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 only a moderate decrease in our ability to
detect DLAs, predominantly in the noisiest spectra. Our code is publicly
available.
Описание
Automated Measurement of Quasar Redshift with a Gaussian Process
%0 Journal Article
%1 fauber2020automated
%A Fauber, Leah
%A Ho, Ming-Feng
%A Bird, Simeon
%A Shelton, Christian R.
%A Garnett, Roman
%A Korde, Ishita
%D 2020
%K Gaussian_process quasar redshift
%T Automated Measurement of Quasar Redshift with a Gaussian Process
%U http://arxiv.org/abs/2006.07343
%X 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-alpha absorbers (DLAs) in quasar spectra with known
redshifts. We show that we are competitive to existing quasar redshift
estimators. Importantly 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 only a moderate decrease in our ability to
detect DLAs, predominantly in the noisiest spectra. Our code is publicly
available.
@article{fauber2020automated,
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-alpha absorbers (DLAs) in quasar spectra with known
redshifts. We show that we are competitive to existing quasar redshift
estimators. Importantly 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 only a moderate decrease in our ability to
detect DLAs, predominantly in the noisiest spectra. Our code is publicly
available.},
added-at = {2020-06-15T10:54:47.000+0200},
author = {Fauber, Leah and Ho, Ming-Feng and Bird, Simeon and Shelton, Christian R. and Garnett, Roman and Korde, Ishita},
biburl = {https://www.bibsonomy.org/bibtex/2147f03258f30f93fa7f5dab61a361669/kiwasawa},
description = {Automated Measurement of Quasar Redshift with a Gaussian Process},
interhash = {a8f8abab2192bf406e010a10f0ecc99d},
intrahash = {147f03258f30f93fa7f5dab61a361669},
keywords = {Gaussian_process quasar redshift},
note = {cite arxiv:2006.07343Comment: 13 pages, 11 figures, to be submitted to MNRAS},
timestamp = {2020-06-15T10:54:47.000+0200},
title = {Automated Measurement of Quasar Redshift with a Gaussian Process},
url = {http://arxiv.org/abs/2006.07343},
year = 2020
}