THE LOCAL GROUP AS A TEST OF COSMOLOGICAL MODELS

Citation
F. Governato et al., THE LOCAL GROUP AS A TEST OF COSMOLOGICAL MODELS, New astronomy, 2(2), 1997, pp. 91-106
Citations number
80
Categorie Soggetti
Astronomy & Astrophysics
Journal title
ISSN journal
13841092
Volume
2
Issue
2
Year of publication
1997
Pages
91 - 106
Database
ISI
SICI code
1384-1092(1997)2:2<91:TLGAAT>2.0.ZU;2-#
Abstract
The dynamics of the Local Group and its environment provide a unique c hallenge to cosmological models. The velocity field within 5h(-1) Mpc of the Local Group (LG) is extremely ''cold''. The deviation from a pu re Hubble flow, characterized by the observed radial peculiar velocity dispersion, is measured to be similar to 60 km s(-1). We compare the local velocity field with similarly defined regions extracted from N-b ody simulations of Universes dominated by cold dark matter (CDM). This test is able to strongly discriminate between models that have differ ent mean mass densities. We find that neither the Ohm=1 (SCDM) nor Ohm =0.3 (OCDM) cold dark matter models can produce a single candidate Loc al Group that is embedded in a region with such small peculiar velocit ies. For these models, we measure velocities dispersion between 300-70 0 km s(-1) and 150-300 km s(-1), respectively, more than twice the obs erved value. Although both CDM models fail to produce environments sim ilar to those of our Local Group on a scale of a few Mpc, they can giv e rise to many binary systems that have similar orbital properties as the Milky Way-Andromeda system. The local, gravitationally induced bia s of halos in the CDM ''Local Group'' environment, if defined within a sphere of 10 Mpc around each Local Group is similar to 1.5, independe nt of Ohm. No biasing scheme could reconcile the measured velocity dis persions around Local Groups with the observed one. Identification of binary systems using a halo finder (named Skid(7)) based on a local de nsity maxima search instead of a simple linking algorithm, gives a muc h more complete sample. We show that a standard ''friend-of-friends'' algorithm would miss about 40% of the LG candidates present in the sim ulations. (C) 1997 Elsevier Science B.V.