paper

Homogeneous Velocity-Distance Data for Peculiar Velocity Analysis. I. Calibration of Cluster Samples

arXiv:astro-ph/9411046 · doi:10.1086/175762

Abstract

We have combined five Tully-Fisher (TF) redshift-distance samples for peculiar velocity analysis: the cluster data of Han, Mould and coworkers (1991-93, HM) and Willick (1991, W91CL), and the field data of Aaronson et al. (1992), Willick (1991), Courteau & Faber (1992), and Mathewson et al. (1992), totaling over 3000 spiral galaxies. We treat the cluster data in this paper, which is the first of a series; in Paper II we treat the field TF samples. These data are to be combined with elliptical data (e.g., Faber et al. 1989) to form the MARK III CATALOG OF GALAXY PECULIAR VELOCITIES, which we will present in Paper III. The catalog will be used as input for POTENT reconstruction of velocity and density fields, described in later papers, as well as for alternative velocity analyses. Our main goal in Papers I & II is to place the TF data onto a self-consistent system by (i) applying a uniform set of corrections to the raw observables, (ii) determining the TF slopes and scatters separately for each sample, and (iii) adjusting the TF zeropoints to ensure mutually consistent distances. The global zeropoint is set by the HM sample, chosen because of its depth and uniformity on the sky and its substantial overlap with each of the other samples. In this paper, we calibrate the ``forward'' and ``inverse'' TF relations for HM and W91CL. We study the selection criteria for these samples and correct for the resultant statistical biases. The bias corrections are validated by comparing forward and inverse cluster distances. We find that many sample clusters are better modeled as ``expanding'' than relaxed, which significantly affects the TF calibrations. Proper corrections for internal extinction are derived self-consistently from the data.

42 Pages, uuencoded PostScript. Submitted to ApJ. 22 Figures not included, can be obtained via ftp, contact [email protected]

Cited by in corpus (59)