Finding Galaxies in the Shadows of Quasars with Gaussian Processes
Abstract
We develop an automated technique for detecting damped Lyman-αabsorbers (DLAs) along spectroscopic sightlines to quasi-stellar objects (QSOs or quasars). The detection of DLAs in large-scale spectroscopic surveys such as SDSS–III is critical to address outstanding cosmological questions, such as the nature of galaxy formation. We use nearly 50000 QSO spectra to learn a tailored Gaussian process model for quasar emission spectra, which we apply to the DLA detection problem via Bayesian model selection. We demonstrate our method’s effectiveness with a large-scale validation experiment on over 100000 spectra, with excellent performance.
Cite
Text
Garnett et al. "Finding Galaxies in the Shadows of Quasars with Gaussian Processes." International Conference on Machine Learning, 2015.Markdown
[Garnett et al. "Finding Galaxies in the Shadows of Quasars with Gaussian Processes." International Conference on Machine Learning, 2015.](https://mlanthology.org/icml/2015/garnett2015icml-finding/)BibTeX
@inproceedings{garnett2015icml-finding,
title = {{Finding Galaxies in the Shadows of Quasars with Gaussian Processes}},
author = {Garnett, Roman and Ho, Shirley and Schneider, Jeff},
booktitle = {International Conference on Machine Learning},
year = {2015},
pages = {1025-1033},
volume = {37},
url = {https://mlanthology.org/icml/2015/garnett2015icml-finding/}
}