Directly imaging damped Lyman-alpha galaxies at z>2. I: Methodology and First Results

Details Directly imaging damped Lyman-alpha galaxies at z>2. I: Methodology and First Results Directly imaging damped Lyman-alpha galaxies at z>2. I: Methodology and First Results

2010-06-07

arxiv.org/abs/1006.1364v2

Astronomy and Astrophysics

Astrophysics

Cosmology and Extragalactic Astrophysics

22 pages, 13 figures. Accepted for publication in MNRAS. Typos corrected

Scientific paper

We present the methodology for, and the first results from, a new imaging program aimed at identifying and characterizing the host galaxies of damped Lyman-alpha absorbers (DLAs) at z>2. We target quasar sightlines with multiple optically-thick HI absorbers and use the higher-redshift system as a "blocking filter" (via its Lyman-limit absorption) to eliminate all far-ultraviolet (FUV) emission from the quasar. This allows us to directly image the rest-frame FUV continuum emission of the lower-redshift DLA, without any quasar contamination and with no bias towards large impact parameters. We introduce a formalism based on galaxy number counts and Bayesian statistics with which we quantify the probability that a candidate is the DLA host galaxy. This method will allow the identification of a bona fide sample of DLAs that are too faint to be spectroscopically confirmed. The same formalism can be adopted to the study of other quasar absorption line systems (e.g. MgII absorbers). We have applied this imaging technique to two QSO sightlines. For the z~2.69 DLA towards J073149+285449, a galaxy with impact parameter b=1.54"=11.89 kpc and implied star formation rate (SFR) of ~5 M/yr is identified as the most reliable candidate. In the case of the z~2.92 DLA towards J211444-005533, no likely host is found down to a 3-sigma SFR limit of 1.4 M/yr. Studying the HI column density as a function of the impact parameter, including 6 DLAs with known hosts from the literature, we find evidence that the observed HI distribution is more extended than what is generally predicted from numerical simulation.

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