19,956 research outputs found
A study of digital holographic filters generation. Phase 2: Digital data communication system, volume 1
An empirical study of the performance of the Viterbi decoders in bursty channels was carried out and an improved algebraic decoder for nonsystematic codes was developed. The hybrid algorithm was simulated for the (2,1), k = 7 code on a computer using 20 channels having various error statistics, ranging from pure random error to pure bursty channels. The hybrid system outperformed both the algebraic and the Viterbi decoders in every case, except the 1% random error channel where the Viterbi decoder had one bit less decoding error
Observational evidence for stochastic biasing
We show that the galaxy density in the Las Campanas Redshift Survey (LCRS)
cannot be perfectly correlated with the underlying mass distribution since
various galaxy subpopulations are not perfectly correlated with each other,
even taking shot noise into account. This rules out the hypothesis of simple
linear biasing, and suggests that the recently proposed stochastic biasing
framework is necessary for modeling actual data.Comment: 4 pages, with 2 figures included. Minor revisions to match accepted
ApJL version. Links and color fig at
http://www.sns.ias.edu/~max/r_frames.html or from [email protected]
Detecting the Earliest Galaxies Through Two New Sources of 21cm Fluctuations
The first galaxies that formed at a redshift ~20-30 emitted continuum photons
with energies between the Lyman-alpha and Lyman limit wavelengths of hydrogen,
to which the neutral universe was transparent except at the Lyman-series
resonances. As these photons redshifted or scattered into the Lyman-alpha
resonance they coupled the spin temperature of the 21cm transition of hydrogen
to the gas temperature, allowing it to deviate from the microwave background
temperature. We show that the fluctuations in the radiation emitted by the
first galaxies produced strong fluctuations in the 21cm flux before the
Lyman-alpha coupling became saturated. The fluctuations were caused by biased
inhomogeneities in the density of galaxies, along with Poisson fluctuations in
the number of galaxies. Observing the power-spectra of these two sources would
probe the number density of the earliest galaxies and the typical mass of their
host dark matter halos. The enhanced amplitude of the 21cm fluctuations from
the era of Lyman-alpha coupling improves considerably the practical prospects
for their detection.Comment: 11 pages, 7 figures, ApJ, published. Normalization fixed in top
panels of Figures 4-
Properties of Galaxy Groups in the SDSS: II.- AGN Feedback and Star Formation Truncation
Successfully reproducing the galaxy luminosity function and the bimodality in
the galaxy distribution requires a mechanism that can truncate star formation
in massive haloes. Current models of galaxy formation consider two such
truncation mechanisms: strangulation, which acts on satellite galaxies, and AGN
feedback, which predominantly affects central galaxies. The efficiencies of
these processes set the blue fraction of galaxies as function of galaxy
luminosity and halo mass. In this paper we use a galaxy group catalogue
extracted from the Sloan Digital Sky Survey (SDSS) to determine these
fractions. To demonstrate the potential power of this data as a benchmark for
galaxy formation models, we compare the results to the semi-analytical model
for galaxy formation of Croton et al. (2006). Although this model accurately
fits the global statistics of the galaxy population, as well as the shape of
the conditional luminosity function, there are significant discrepancies when
the blue fraction of galaxies as a function of mass and luminosity is compared
between the observations and the model. In particular, the model predicts (i)
too many faint satellite galaxies in massive haloes, (ii) a blue fraction of
satellites that is much too low, and (iii) a blue fraction of centrals that is
too high and with an inverted luminosity dependence. In the same order, we
argue that these discrepancies owe to (i) the neglect of tidal stripping in the
semi-analytical model, (ii) the oversimplified treatment of strangulation, and
(iii) improper modeling of dust extinction and/or AGN feedback. The data
presented here will prove useful to test and calibrate future models of galaxy
formation and in particular to discriminate between various models for AGN
feedback and other star formation truncation mechanisms.Comment: 16 pages, 5 figures, submitted to MNRA
Star Formation and Stellar Mass Assembly in Dark Matter Halos: From Giants to Dwarfs
The empirical model of Lu et al. 2014 is updated with recent data and used to
study galaxy star formation and assembly histories. At , the predicted
galaxy stellar mass functions are steep, and a significant amount of star
formation is hosted by low-mass haloes that may be missed in current
observations. Most of the stars in cluster centrals formed earlier than
but have been assembled much later. Milky Way mass galaxies have
had on-going star formation without significant mergers since , and
are thus free of significant (classic) bulges produced by major mergers. In
massive clusters, stars bound in galaxies and scattered in the halo form a
homogeneous population that is old and with solar metallicity. In contrast, in
Milky Way mass systems the two components form two distinct populations, with
halo stars being older and poorer in metals by a factor of . Dwarf
galaxies in haloes with have experienced a
star formation burst accompanied by major mergers at , followed by a
nearly constant star formation rate after . The early burst leaves a
significant old stellar population that is distributed in spheroids.Comment: 17 pages, 17 figure
The clustering of SDSS galaxy groups: mass and color dependence
We use a sample of galaxy groups selected from the SDSS DR 4 with an adaptive
halo-based group finder to probe how the clustering strength of groups depends
on their masses and colors. In particular, we determine the relative biases of
groups of different masses, as well as that of groups with the same mass but
with different colors. In agreement with previous studies, we find that more
massive groups are more strongly clustered, and the inferred mass dependence of
the halo bias is in good agreement with predictions for the CDM
cosmology. Regarding the color dependence, we find that groups with red
centrals are more strongly clustered than groups of the same mass but with blue
centrals. Similar results are obtained when the color of a group is defined to
be the total color of its member galaxies. The color dependence is more
prominent in less massive groups and becomes insignificant in groups with
masses \gta 10^{14}\msunh. We construct a mock galaxy redshift survey
constructed from the large Millenium simulation that is populated with galaxies
according to the semi-analytical model of Croton et al. Applying our group
finder to this mock survey, and analyzing the mock data in exactly the same way
as the true data, we are able to accurately recover the intrinsic mass and
color dependencies of the halo bias in the model. This suggests that our group
finding algorithm and our method of assigning group masses do not induce
spurious mass and/or color dependencies in the group-galaxy correlation
function. The semi-analytical model reveals the same color dependence of the
halo bias as we find in our group catalogue. In halos with M\sim
10^{12}\msunh, though, the strength of the color dependence is much stronger
in the model than in the data.Comment: 16 pages, 14 figures, Accepted for publication in ApJ. In the new
version, we add the bias of the shuffled galaxy sample. The errors are
estimated according to the covariance matrix of the GGCCF, which is then
diagonalize
Sunyaev - Zel'dovich fluctuations from spatial correlations between clusters of galaxies
We present angular power spectra of the cosmic microwave background radiation
anisotropy due to fluctuations of the Sunyaev-Zel'dovich (SZ) effect through
clusters of galaxies. A contribution from the correlation among clusters is
especially focused on, which has been neglected in the previous analyses.
Employing the evolving linear bias factor based on the Press-Schechter
formalism, we find that the clustering contribution amounts to 20-30% of the
Poissonian one at degree angular scales. If we exclude clusters in the local
universe, it even exceeds the Poissonian noise, and makes dominant contribution
to the angular power spectrum. As a concrete example, we demonstrate the
subtraction of the ROSAT X-ray flux-limited cluster samples. It indicates that
we should include the clustering effect in the analysis of the SZ fluctuations.
We further find that the degree scale spectra essentially depend upon the
normalization of the density fluctuations, i.e., \sigma_8, and the gas mass
fraction of the cluster, rather than the density parameter of the universe and
details of cluster evolution models. Our results show that the SZ fluctuations
at the degree scale will provide a possible measure of \sigma_8, while the
arc-minute spectra a probe of the cluster evolution. In addition, the
clustering spectrum will give us valuable information on the bias at high
redshift, if we can detect it by removing X-ray luminous clusters.Comment: 11 pages, 4 figures, submitted to Astrophysical Journa
Multisensory causal inference in the brain
At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions
The mass function
We present the mass functions for different mass estimators for a range of
cosmological models. We pay particular attention to how universal the mass
function is, and how it depends on the cosmology, halo identification and mass
estimator chosen. We investigate quantitatively how well we can relate observed
masses to theoretical mass functions.Comment: 14 pages, 12 figures, to appear in ApJ
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