The galaxy-weighted small-scale velocity dispersion of the Las Campanas Redshift Survey

Citation
Je. Baker et al., The galaxy-weighted small-scale velocity dispersion of the Las Campanas Redshift Survey, ASTROPHYS J, 536(1), 2000, pp. 112-121
Citations number
36
Categorie Soggetti
Space Sciences
Journal title
ASTROPHYSICAL JOURNAL
ISSN journal
0004637X → ACNP
Volume
536
Issue
1
Year of publication
2000
Part
1
Pages
112 - 121
Database
ISI
SICI code
0004-637X(20000610)536:1<112:TGSVDO>2.0.ZU;2-O
Abstract
The Fair-weighted relative velocity dispersion of galaxies provides a measu re of the thermal energy of fluctuations of the observed galaxy distributio n, but the measure is difficult to interpret and is very sensitive to the e xistence of rare rich clusters of galaxies. Several alternative statistical procedures have recently been suggested to relieve these problems. We appl y a variant of the object-weighted statistical method of Davis, Miller, & W hite to the Las Campanas Redshift Survey (LCRS), which is the largest and d eepest existing redshift survey that is nearly fully sampled. The derived o ne-dimensional dispersion on scales of similar to 1 h(-1) Mpc is quite low: sigma(1) = 126 +/- 10 km s(-1), with a modest decrease at larger scales. T he statistic is very stable; the six independent slices of the LCRS all yie ld consistent results. We apply the same statistical procedure to halos in numerical simulations of an open cosmological model and flat models with an d without a cosmological constant. In contrast to the LCRS, all the models show a dispersion that increases for scales > 1 h(-1) Mpc; it is uncertain whether this is a numerical artifact or a real physical effect. The standar d cluster-normalized cold dark matter model with Omega(m) = 1, as well as a tilted variant with n = 0.8, yield dispersions substantially hotter than t he LCRS value, while models with low matter density (Omega(m) = 0.3) are br oadly consistent with the LCRS data. Using a filtered cosmic energy equatio n, we measure Omega(m) approximate to 0.2, with small-scale bias factors b = 1.0-1.5 for high-density models and b = 0.7-1.1 for low-density models.