6,604 research outputs found
High-Resolution Simulations of Cosmic Microwave Background non-Gaussian Maps in Spherical Coordinates
We describe a new numerical algorithm to obtain high-resolution simulated
maps of the Cosmic Microwave Background (CMB), for a broad class of
non-Gaussian models. The kind of non-Gaussianity we account for is based on the
simple idea that the primordial gravitational potential is obtained by a
non-linear but local mapping from an underlying Gaussian random field, as
resulting from a variety of inflationary models. Our technique, which is based
on a direct realization of the potential in spherical coordinates and fully
accounts for the radiation transfer function, allows to simulate non-Gaussian
CMB maps down to the Planck resolution (), with
reasonable memory storage and computational time.Comment: 9 pages, 5 figures. Submitted to ApJ. A version with higher quality
figures is available at http://www.pd.infn.it/~liguori/content.htm
A Counts-in-Cells Analysis of Lyman-break Galaxies at z~3
We have measured the counts-in-cells fluctuations of 268 Lyman-break galaxies
with spectroscopic redshifts in six 9 arcmin by 9 arcmin fields at z~3. The
variance of galaxy counts in cubes of comoving side length 7.7, 11.9, 11.4
h^{-1} Mpc is \sigma_{gal}^2 ~ 1.3\pm0.4 for \Omega_M=1, 0.2 open, 0.3 flat,
implying a bias on these scales of \sigma_{gal} / \sigma_{mass} = 6.0\pm1.1,
1.9\pm0.4, 4.0\pm0.7. The bias and abundance of Lyman-break galaxies are
surprisingly consistent with a simple model of structure formation which
assumes only that galaxies form within dark matter halos, that Lyman-break
galaxies' rest-UV luminosities are tightly correlated with their dark masses,
and that matter fluctuations are Gaussian and have a linear power-spectrum
shape at z~3 similar to that determined locally (\Gamma~0.2). This conclusion
is largely independent of cosmology or spectral normalization \sigma_8. A
measurement of the masses of Lyman-break galaxies would in principle
distinguish between different cosmological scenarios.Comment: Accepted for publication in ApJ, 16 pages including 4 figure
Extreme events and event size fluctuations in biased random walks on networks
Random walk on discrete lattice models is important to understand various
types of transport processes. The extreme events, defined as exceedences of the
flux of walkers above a prescribed threshold, have been studied recently in the
context of complex networks. This was motivated by the occurrence of rare
events such as traffic jams, floods, and power black-outs which take place on
networks. In this work, we study extreme events in a generalized random walk
model in which the walk is preferentially biased by the network topology. The
walkers preferentially choose to hop toward the hubs or small degree nodes. In
this setting, we show that extremely large fluctuations in event-sizes are
possible on small degree nodes when the walkers are biased toward the hubs. In
particular, we obtain the distribution of event-sizes on the network. Further,
the probability for the occurrence of extreme events on any node in the network
depends on its 'generalized strength', a measure of the ability of a node to
attract walkers. The 'generalized strength' is a function of the degree of the
node and that of its nearest neighbors. We obtain analytical and simulation
results for the probability of occurrence of extreme events on the nodes of a
network using a generalized random walk model. The result reveals that the
nodes with a larger value of 'generalized strength', on average, display lower
probability for the occurrence of extreme events compared to the nodes with
lower values of 'generalized strength'
The Cluster Distribution as a Test of Dark Matter Models. IV: Topology and Geometry
We study the geometry and topology of the large-scale structure traced by
galaxy clusters in numerical simulations of a box of side 320 Mpc, and
compare them with available data on real clusters. The simulations we use are
generated by the Zel'dovich approximation, using the same methods as we have
used in the first three papers in this series. We consider the following models
to see if there are measurable differences in the topology and geometry of the
superclustering they produce: (i) the standard CDM model (SCDM); (ii) a CDM
model with (OCDM); (iii) a CDM model with a `tilted' power
spectrum having (TCDM); (iv) a CDM model with a very low Hubble
constant, (LOWH); (v) a model with mixed CDM and HDM (CHDM); (vi) a
flat low-density CDM model with and a non-zero cosmological
term (CDM). We analyse these models using a variety of
statistical tests based on the analysis of: (i) the Euler-Poincar\'{e}
characteristic; (ii) percolation properties; (iii) the Minimal Spanning Tree
construction. Taking all these tests together we find that the best fitting
model is CDM and, indeed, the others do not appear to be consistent
with the data. Our results demonstrate that despite their biased and extremely
sparse sampling of the cosmological density field, it is possible to use
clusters to probe subtle statistical diagnostics of models which go far beyond
the low-order correlation functions usually applied to study superclustering.Comment: 17 pages, 7 postscript figures, uses mn.sty, MNRAS in pres
Topology of Neutral Hydrogen Within the Small Magellanic Cloud
In this paper, genus statistics have been applied to an HI column density map
of the Small Magellanic Cloud in order to study its topology. To learn how
topology changes with the scale of the system, we provide the study of topology
for column density maps at varying resolution. To evaluate the statistical
error of the genus we randomly reassign the phases of the Fourier modes while
keeping the amplitudes. We find, that at the smallest scales studied () the genus shift is in all regions negative,
implying a clump topology. At the larger scales () the topology shift is detected to be negative in 4 cases and positive
(``swiss cheese'' topology) in 2 cases. In 4 regions there is no statistically
significant topology shift at large scales
Two-Dimensional Topology of the 2dF Galaxy Redshift Survey
We study the topology of the publicly available data released by the 2dFGRS.
The 2dFGRS data contains over 100,000 galaxy redshifts with a magnitude limit
of b_J=19.45 and is the largest such survey to date. The data lie over a wide
range of right ascension (75 degree strips) but only within a narrow range of
declination (10 degree and 15 degree strips). This allows measurements of the
two-dimensional genus to be made.
The NGP displays a slight meatball shift topology, whereas the SGP displays a
bubble like topology. The current SGP data also have a slightly higher genus
amplitude. In both cases, a slight excess of overdense regions are found over
underdense regions. We assess the significance of these features using mock
catalogs drawn from the Virgo Consortium's Hubble Volume LCDM z=0 simulation.
We find that differences between the NGP and SGP genus curves are only
significant at the 1 sigma level. The average genus curve of the 2dFGRS agrees
well with that extracted from the LCDM mock catalogs.
We compare the amplitude of the 2dFGRS genus curve to the amplitude of a
Gaussian random field with the same power spectrum as the 2dFGRS and find,
contradictory to results for the 3D genus of other samples, that the amplitude
of the GRF genus curve is slightly lower than that of the 2dFGRS. This could be
due to a a feature in the current data set or the 2D genus may not be as
sensitive as the 3D genus to non-linear clustering due to the averaging over
the thickness of the slice in 2D. (Abridged)Comment: Submitted to ApJ A version with Figure 1 in higher resolution can be
obtained from http://www.physics.drexel.edu/~hoyle
Nonlinear Evolution of the Genus Statistics with Zel'dovich Approximation
Evolution of genus density is calculated from Gaussian initial conditions
using Zel'dovich approximation. A new approach is introduced which formulates
the desired quantity in a rotationally invariant manner. It is shown that
normalized genus density does not depend on the initial spectral shape but is a
function of the fluctuation amplitude only.Comment: 21 pages, 6 Postscript figures, LaTe
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