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Figure 1:
Evolution of the cosmic scale factor as a function of . The present
value of the scale factor is set to unity; solid line: , dotted line: , dot-dashed line: , long dashed
line: , short dashed line:
. |
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Figure 2:
Linear growth rate of density fluctuations. |
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Figure 3:
One-point PDFs in CDM models with Gaussian (left panels) and top-hat (right panels) smoothing windows: (cyan), (red),
and (green). The solid and long-dashed lines represent the
log-normal PDF adopting calculated directly
from the simulations and estimated
from the nonlinear fitting formula of [67],
respectively. (Figure taken from [40].) |
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Figure 4:
Isodensity surfaces of dark matter distribution from -body simulation: LCDM
in at (upper left panel), (upper right panel), (lower left panel),
and
(lower right panel). (Figure taken
from [54].) |
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Figure 5:
Top-view of distribution of objects at in real (left panels) and
redshift (right panels) spaces around
the fiducial observer at the center: dark matter particles (top
panels), peaks with (middle
panels), and halos with (bottom panels) in the LCDM model. The thickness of those slices is . (Figure taken from [86].) |
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Figure 6:
Same as Figure 5, but at . (Figure taken
from [86].) |
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Figure 7:
Auto- and cross-correlation functions of dark matter and peaks in SCDM (left panels), LCDM (middle panels), and OCDM (right panels) for (a) (upper panels)
and (b) (lower panels). Different
symbols indicate the results in real space (open squares for
, filled triangles
for , open circles for , and crosses for dark matter), while different
curves indicate those in redshift
space (dashed for , dot-dashed for , solid for , and
dotted for dark matter). (Figure taken
from [86].) |
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Figure 8:
Same as Figure 7, but for a halo model, again for (a) (upper panels)
and (b) (lower panels): Open squares
and dashed lines for ,
filled triangles and dot-dashed lines
for , open circles and solid lines for , and crosses and dotted lines for dark matter. For
the SCDM model, we only plot the correlation functions with and .
(Figure taken from [86].) |
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Figure 9:
Distribution of gas particles (upper right panel), dark matter particles (upper left panel), galaxies (lower right panel), and dark halos (lower left panel) in the volume of a model at . (Figure taken from [103].) |
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Figure 10:
Snapshots of the most massive cluster ( ) in
the simulation at . Upper left panel: dark matter; upper right panel:
gas; lower left panel: DM cores; lower right panel: cold gas. The circles in the lower panels indicate
the positions of galaxies identified according to our criteria. The comoving size of the box is
per side. (Figure taken from [103].) |
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Figure 11:
Joint probability distributions of overdensity fields for dark halos and galaxies with dark matter overdensity smoothed over at redshift , , and . Solid lines indicate
the conditional mean for each object. Dashed lines
in each panel depict the theoretical prediction of conditional mean by Taruya and
Suto [87]. (Figure
taken from [103].) |
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Figure 12:
Two-point correlation functions of dark matter, galaxies, and dark halos from cosmological hydrodynamical simulations. (Figure taken from [103].) |
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Figure 13:
Two-point correlation functions for the old and young populations of galaxies at as well as that of the dark matter distribution.
The profiles of bias parameters for both of
the two populations are also shown in
the lower panel. (Figure taken from [103].) |
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Figure 14:
Mass two-point correlation functions on the light-cone for particles with redshift-dependent selection functions in the SCDM model, for (upper
panels) and (lower panels). Left
panels: with selection function whose shape is the same as that of
the B-band magnitude limit of 19 for
galaxies (upper) and 21 for QSOs (lower); right panels: randomly
selected particles from the particles
in the results from the left panels. (Figure taken
from [28].) |
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Figure 15:
Same as Figure 14 but for the -CDM model. (Figure taken from [28].) |
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Figure 16:
Two-dimensional power spectra in cosmological redshift space at . (Figure taken from [46].) |
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Figure 17:
The confidence contours on the - plane from the -analysis of the
monopole and quadrupole moments of the
power spectrum in the cosmological redshift space at . We randomly
selected (upper panels), (middle panels), and (lower panels) particles from -body simulation. The value of is adopted from the cluster abundance. (Figure taken from [46].) |
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Figure 18:
Light-cone and cosmological redshift-space distortion effects on angle-averaged power spectra. (Figure taken from [84].) |
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Figure 19:
Same as Figure 18 on angle-averaged two-point correlation functions. (Figure taken from [84].) |
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Figure 20:
The 2dFGRS fields (small circles) superimposed on the APM catalogue area (dotted outlines of Sky Survey plates). |
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Figure 21:
The distribution of 63,000 2dFGRS galaxies in the NGP (left panel) and SGP (right panel) strips. |
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Figure 22:
3D redshift-space map centered on us, and its projection on the celestial sphere of SDSS galaxy subset, including the three main regions. (Figure taken from [32].) |
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Figure 23:
Redshift slices of SDSS galaxy data around the equatorial plane. The redshift limits and the thickness of the planes are and (upper
panel), and (middle panel), and and (lower
panel). The size of points has been adjusted. Note that the data for the Southern part are
sparser than those for the Northern part, especially for
thick slices. (Figure taken
from [32].) |
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Figure 24:
The power spectrum of the 2dFGRS. The points with error bars show the measured 2dFGRS power spectrum measurements in redshift space, convolved with the window function. Also plotted are linear CDM models with neutrino contribution of , , and (bottom
to top lines). The other parameters
are fixed to the concordance model. The good fit of the linear
theory power spectrum at
is due to a conspiracy between the non-linear
gravitational growth and the
finger-of-God smearing [72]. (Figure
taken from [20].) |
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Figure 25:
The variation of the galaxy biasing parameter with luminosity, relative to an galaxy for the full
sample and for subsamples of early and late spectra types. (Figure
taken from [61].) |
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Figure 26:
The two point correlation function plotted for passively (left
panel) and actively (right panel)
star-forming galaxies. The line contours levels show the
best-fitting model. (Figure taken from [45].) |
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Figure 27:
The correlation function for early and late spectral types. The solid lines show best-fitting models, whereas the dashes lines are extrapolations of these lines. (Figure taken from [45].) |
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Figure 28:
The SDSS (EDR) projected correlation function for blue (squares), red (triangles) and the full sample, with best-fitting models over the range (upper panel), and the
SDSS (EDR) projected correlation function for three volume-limited
samples, with absolute magnitude and
redshift ranges as indicated and best-fitting power-law models
(lower panel). (Figure taken
from [104].) |
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Figure 29:
Dimensionless amplitude of the three-point correlation functions of SDSS galaxies in redshift space. The galaxies are classified according to their colors; all galaxies in open circles, red galaxies in solid triangles, and blue galaxies in crosses. (Figure taken from [39].) |
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Figure 30:
Same as Figure 29, but for the inverse of the biasing parameter defined through the two-point correlation functions. (Figure taken from [39].) |
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Figure 31:
MFs as a function of for for SDSS
data. Averaged MFs of the mock samples
are plotted for LCDM (solid lines) and SCDM (long dashed lines).
Gaussian model predictions (see
Equations ( 112 , 113 , 114 , 115 )) are also plotted with short dashed lines. The
results favor the LCDM model with
random-Gaussian initial conditions. (Figure taken
from [32].) |
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