We have already seen that
CDM correctly
predicts the abundances of clusters nearby and at z
1 within the
current uncertainties in
the values of the parameters. It is even consistent with
P(k) from
the Ly
forest
[36]
and from CMB anisotropies.
Low-
m CDM
predicts that the amplitude of the power spectrum
P(k) is rather large for k
0.02h / Mpc-1, i.e. on
size scales larger (k smaller) than the peak in
P(k). The largest-scale surveys, 2dF and SDSS, should be
able to measure P(k)
on these scales and test this crucial prediction soon; preliminary
results are encouraging
[37].
The hierarchical structure formation which is inherent in CDM already explains why most stars are in big galaxies like the Milky Way [14]: smaller galaxies merge to form these larger ones, but the gas in still larger structures takes too long to cool to form still larger galaxies, so these larger structures - the largest bound systems in the universe - become groups and clusters instead of galaxies.
What about the more detailed predictions of
CDM, for example
on the spatial distribution of galaxies. On large scales, there appears to
be a pretty good match. In order to investigate such questions
quantitatively on the smaller scales where the best data is available
it is essential to do N-body simulations, since the mass fluctuations
/
are nonlinear
on the few-Mpc scales that are
relevant. My colleagues and I were initially concerned that
CDM would fail
this test,
[38]
since the dark matter power spectrum Pdm(k) in
CDM, and its
Fourier transform the correlation function
(r), are seriously in disagreement with the galaxy
data Pg(k) and
g(r). One
way of describing this is to say
that scale-dependent antibiasing is required for
CDM to agree with
observations. That is, the bias parameter
b(r)
[
g(r) /
(r)]1/2, which is about unity on large scales,
must decrease to less than 1/2 on scales of a few
Mpc [38,
39].
This was the opposite of what was expected:
galaxies were generally thought to be more correlated than the dark
matter on small scales. However, when it became possible to do
simulations of sufficiently high resolution to identify the dark
matter halos that would host visible galaxies
[40,
41],
it turned out that their correlation function is essentially identical
with that of observed galaxies! This is illustrated in
Fig. 1.
![]() |
Figure 1. Bottom panel: Comparison
of the halo correlation function in an
|
Jim Peebles, who largely initiated the study of galaxy correlations
and first showed that
g(r)
(r /
r0)-1.8 with
r0
5h-1Mpc
[48],
thought that this simple power law
must be telling us something fundamental about cosmology. However, it
now appears that the power law
g arises because of
a coincidence - an interplay between the non-power-law
dm(r) (see
Fig. 1) and the decreasing survival probability
of dark
matter halos in dense regions because of their destruction and
merging. But the essential lesson is that
CDM correctly predicts
the observed
g(r).
The same theory also predicts the number density of galaxies. Using
the observed correlations between galaxy luminosity and internal
velocity, known as the Tully-Fisher and Faber-Jackson relations for
spiral and elliptical galaxies respectively, it is possible to convert
observed galaxy luminosity functions into approximate galaxy velocity
functions, which describe the number of galaxies per unit volume as a
function of their internal velocity. The velocity function of dark
matter halos is robustly predicted by N-body simulations for CDM-type
theories, but to connect it with the observed internal velocities of
bright galaxies it is necessary to correct for the infall of the
baryons in these galaxies
[43,
44,
45],
which must have happened to create their bright centers and disks. When
we did this it appeared that
CDM with
m = 0.3
predicts perhaps too
many dark halos compared with the number of observed galaxies with
internal rotation velocities
V
200km
s-1
[46,
47].
While the latest results from the big surveys now
underway appear to be in better agreement with these
CDM predictions
[49,
50],
this is an important issue that is being investigated in detail
[51].
The problem just mentioned of accounting for baryonic infall is just
one example of the hydrodynamical phenomena that must be taken into
account in order to make realistic predictions of galaxy properties in
cosmological theories. Unfortunately, the crucial processes of
especially star formation and supernova feedback are not yet well
enough understood to allow reliable calculations. Therefore, rather
than trying to understand galaxy formation from full-scale
hydrodynamic simulations (for example
[52]),
more progress has been made via the simpler approach of semi-analytic
modelling of galaxy formation (initiated by White and Frenk
[53,
54,
55],
recently reviewed and extended by Rachel Somerville and me
[56]).
The computational
efficiency of SAMs permits detailed exploration of the effects of the
cosmological parameters, as well as the parameters that control star
formation and supernova feedback. We have shown
[56] that both
flat and open CDM-type models with
m = 0.3 -
0.5 predict galaxy
luminosity functions and Tully-Fisher relations that are in good
agreement with observations. Including the effects of (proto-)galaxy
interactions at high redshift in SAMs allows us to account for the
observed properties of high-redshift galaxies, but only for
m
0.3 - 0.5
[57]. Models with
m = 1 and
realistic
power spectra produce far too few galaxies at high redshift,
essentially because of the fluctuation growth rate argument mentioned
above.
In order to tell whether
CDM accounts in
detail for galaxy
properties, it is essential to model the dark halos accurately. The
Navarro-Frenk-White (NFW)
[58]
density profile
NFW(r)
r-1(r + rs)-2 is a
good representation of typical dark
matter halos of galactic mass, except possibly in their very centers
(Section 4). Comparing simulations of the
same halo with numbers of
particles ranging from ~ 103 to ~ 106, my
colleagues and I have also shown
[59]
that rs, the radius where the
log-slope is -2, can be determined accurately for halos with as few as
~ 103 particles. Based on a study of thousands of halos at many
redshifts in an Adaptive Refinement Tree (ART)
[60] simulation
of the
CDM
cosmology, we
[61]
found that the concentration cvir
Rvir
/ rs has a log-normal distribution,
with 1
(log
cvir) = 0.14 at a given
mass [62,
63].
This scatter in concentration results in a
scatter in maximum rotation velocities of
Vmax / Vmax = 0.12;
thus the distribution of halo concentrations has as large an effect on
galaxy rotation curves shapes as the well-known log-normal
distribution of halo spin parameters
. Frank van den Bosch
[64]
showed, based on a semi-analytic model for galaxy
formation including the NFW profile and supernova feedback, that the
spread in
mainly
results in movement along the Tully-Fisher
line, while the spread in concentration results in dispersion
perpendicular to the Tully-Fisher relation. Remarkably, he found that
the dispersion in
CDM halo
concentrations produces a Tully-Fisher
dispersion that is consistent with the observed
one. (4)
4 Actually, this was the case with the
dispersion in concentration
(log
cvir) = 0.1 found for relaxed halos by
Jing [62],
while we [61]
found the larger dispersion mentioned above. However Risa Wechsler, in her
dissertation research with me
[63],
found that the dispersion
in the concentration at fixed mass of the halos that have not had a
major merger since redshift z = 2 (and could thus host a spiral
galaxy) is consistent with that found by Jing. We also found that the
median and dispersion of halo concentration as a function of mass and
redshift are explained by the spread in halo mass accretion
histories.
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