Finding galaxies in the shadows of quasars with Gaussian processes
Conference Paper, Proceedings of (ICML) International Conference on Machine Learning, Vol. 37, pp. 1025 - 1033, July, 2015
Abstract
We develop an automated technique for detecting damped Lyman-α absorbers (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 50 000 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 100 000 spectra, with excellent performance.
BibTeX
@conference{Garnett-2015-119756,author = {R. Garnett and S. Ho and J. Schneider},
title = {Finding galaxies in the shadows of quasars with Gaussian processes},
booktitle = {Proceedings of (ICML) International Conference on Machine Learning},
year = {2015},
month = {July},
volume = {37},
pages = {1025 - 1033},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.