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| ![]() | © CAMBRIDGE UNIVERSITY PRESS 2000 |
7.1.1 Measures of galaxy clustering
One way to describe the tendency of galaxies to cluster together is
the wo-point correlation function
(r).
If we make a random choice
of two small volumes
V1 and
V2, and the average
spatial density of galaxies is n per cubic megaparsec,
then the chance of finding a galaxy in
V1 is just
n
V1.
If galaxies tend to clump together, then the
probability that we then also have a galaxy in
V2 will be greater
when the separation r12 between the two regions is
small. We write the joint probability of finding a galaxy in both volumes as
![]() | (7.1) |
if (r) > 0 at
small r, then galaxies are clustered,
while if
(r) <
0, they tend to avoid each other.
We generally compute
(r) by estimating the galaxy distances from
their redshifts, making a correction for the distortion introduced by
peculiar velocities. On scales
r
50
h-1 Mpc, it takes roughly the form
![]() | (7.2) |
with > 0. The
probability of finding one galaxy within
radius r of another is significantly larger than random when
r < r0, the correlation length. Since
(r) represents the
deviation from an average density, it must at some point become negative
as r increases.
Figure 7.7 shows the two-point correlation
function for
galaxies of the Las Campanas survey of
Figure 7.3. In the range 2
h-1
r
16
h-1 Mpc where
(r) is well
measured, the
correlation length r0
6 h-1 Mpc
and
1.5.
A rough average over many surveys gives
r0 ~ 5 h-1 Mpc, and
~ 1.8.
The two-Point correlation function oscillates around zero for
r
30
h-1 Mpc, roughly the size of the largest wall or
void features; the galaxy distribution is fairly uniform on larger
scales.
Unfortunately, the correlation function is not very useful for
describing the one-dimensional filaments or two-dimensional walls
of Figure 7.3.
If our volume
V1 lies in one of
these, the probability of finding a galaxy in
V2 is high
only when it also lies within the structure. Since
(r) is an
average over all possible placements of
V2, it will not
rise far above zero once the separation r exceeds the thickness of
the wall or filament. We can try to overcome this by defining the
three-point and four-point correlation functions, which give the joint
probability of finding galaxies in each of three or four distinct
volumes; but this is not very satisfactory. A good statistical
method has yet to be developed to describe the strength and prevalence
of walls and filaments.
The Fourier transform of
(r) is the power spectrum P(k):
![]() | (7.3) |
so that small k corresponds to a large spatial scale.
Since (r) is
dimensionless, P(k) has the dimensions of a
volume. The function sin kr / kr is positive for
|kr| <
, and
it oscillates with decreasing amplitude as kr becomes large; so very
roughly, P(k) will have its maximum when k-1 is
close to the
radius where
(r) drops to zero. The right panel of
Figure 7.7 shows that when k is large,
we have P(k)
k-1.8; the power spectrum
flattens and starts to decline for k-1
60 h-1 Mpc.
Problem 7.4: Prove the last equality of Equation 7.3. One method is
to write the volume integral for P(k)
in spherical polar coordinates r,
|
Problem 7.5: Show that the power spectrum P(k)
|
We can write the local density at position x as a multiple of the
mean level
, as
(x) =
[1 +
(x)],
and let
R be the
fractional deviation
(x) averaged
within a sphere of radius R. When we take the average
<
R > over all such
spheres, this must be zero. The
dimensionless quantity
<
R2 >
measures the lumpiness or
non-uniformity of the galaxy distribution on this scale. We can
relate <
R2 >
to k3 P(k), the dimensionless number
prescribing the fluctuation in density within a volume
k-1 Mpc in radius. If clumps of galaxies with size
k-1
are placed randomly in relation to those on larger or smaller scales
(the random phase hypothesis), we have
![]() | (7.4) |
where k
R-1.
We often parametrize the clustering by
8, defined as the
average fluctuation on a scale R = 8 h-1 Mpc.
For the Las Campanas survey,
8
1.
Since P(k) declines more slowly than k-3 at
high wavenumbers,
k2
increases with k. The smaller the region we consider,
the greater the probability of finding a very high density of
galaxies.
Cosmological models for the development of structure
can predict P(k), for comparison with observations; we return
to this topic in Section 7.4.
Problem 7.6: The quantity
< |
In this section we have seen that the present-day distribution of galaxies is very lumpy and inhomogeneous on scales up to 100 h-1 Mpc. But measurements of the cosmic background radiation show that its temperature is the same in all parts of the sky to within a few parts in 100 000. Thus at the time of recombination, when the pregalactic gas became neutral and transparent, matter and radiation were very smoothly distributed. How could our present highly structured Universe of galaxies have arisen from such uniform beginnings? To understand what might have happened, we must begin by looking at how the Universe expanded following the Big Bang, and how concentrations of galaxies could form within it.