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Published December 10, 2019 | Accepted Version + Published
Journal Article Open

Predicting Lyα Emission from Galaxies via Empirical Markers of Production and Escape in the KBSS

Abstract

Lyα emission is widely used to detect and confirm high-redshift galaxies and characterize the evolution of the intergalactic medium (IGM). However, many galaxies do not display Lyα emission in typical spectroscopic observations, and intrinsic Lyα emitters represent a potentially biased set of high-redshift galaxies. In this work, we analyze a set of 703 galaxies at 2 ≾ z ≾ 3 with both Lyα spectroscopy and measurements of other rest-frame ultraviolet and optical properties in order to develop an empirical model for Lyα emission from galaxies and understand how the probability of Lyα emission depends on other observables. We consider several empirical proxies for the efficiency of Lyα photon production, as well as the subsequent escape of these photons through their local interstellar medium. We find that the equivalent width of metal-line absorption and the O3 ratio of rest-frame optical nebular lines are advantageous empirical proxies for Lyα escape and production, respectively. We develop a new quantity, X_(LIS)^(O3), that combines these two properties into a single predictor of net Lyα emission, which we find describes ~90% of the observed variance in Lyα equivalent width when accounting for our observational uncertainties. We also construct conditional probability distributions demonstrating that galaxy selection based on measurements of galaxy properties yield samples of galaxies with widely varying probabilities of net Lyα emission. The application of the empirical models and probability distributions described here may be used to infer the selection biases of current galaxy surveys and evaluate the significance of high-redshift Lyα (non)detections in studies of reionization and the IGM.

Additional Information

© 2019. The American Astronomical Society. Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Received 2019 August 13; revised 2019 September 24; accepted 2019 September 29; published 2019 December 12. Based on data obtained at the W. M. Keck Observatory, which is operated as a scientific partnership among the California Institute of Technology, the University of California, and NASA, and was made possible by the generous financial support of the W. M. Keck Foundation. We are indebted to the staff of the W. M. Keck Observatory who keep the instruments and telescopes running effectively. We also wish to extend thanks to those of Hawaiian ancestry on whose sacred mountain we are privileged to be guests. This work has been supported in part by the US National Science Foundation through grants AST-0908805 and AST-1313472. We also acknowledge support from the JPL/Caltech President's and Director's Program. Software: Astropy (Astropy Collaboration et al. 2013), Matplotlib (Hunter 2007).

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Published - Trainor_2019_ApJ_887_85.pdf

Accepted Version - 1908.04794.pdf

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August 22, 2023
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