THE CLUSTERING CHARACTERISTICS OF H I-SELECTED GALAXIES FROM THE 40% ALFALFA SURVEY
The 40% Arecibo Legacy Fast ALFA survey catalog ( alpha .40) of ~10, 150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the...
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Published in | The Astrophysical journal Vol. 750; no. 1; pp. 1 - 11 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
Bristol
IOP
01.05.2012
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Subjects | |
Online Access | Get full text |
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Summary: | The 40% Arecibo Legacy Fast ALFA survey catalog ( alpha .40) of ~10, 150 H I-selected galaxies is used to analyze the clustering properties of gas-rich galaxies. By employing the Landy-Szalay estimator and a full covariance analysis for the two-point galaxy-galaxy correlation function, we obtain the real-space correlation function and model it as a power law, [xi](r) = (r/r sub(0)) super(- gamma ), on scales <10 h super(-1) Mpc. As the largest sample of blindly H I-selected galaxies to date, alpha .40 provides detailed understanding of the clustering of this population. We find gamma = 1.51 + or - 0.09 and r sub(0) = 3.3 + 0.3, -0.2 h super(-1) Mpc, reinforcing the understanding that gas-rich galaxies represent the most weakly clustered galaxy population known; we also observe a departure from a pure power-law shape at intermediate scales, as predicted in [Lambda]CDM halo occupation distribution models. Furthermore, we measure the bias parameter for the alpha .40 galaxy sample and find that H I galaxies are severely antibiased on small scales, but only weakly antibiased on large scales. The robust measurement of the correlation function for gas-rich galaxies obtained via the alpha .40 sample constrains models of the distribution of H I in simulated galaxies, and will be employed to better understand the role of gas in environmentally dependent galaxy evolution. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0004-637X 1538-4357 |
DOI: | 10.1088/0004-637X/750/1/38 |