97 research outputs found
Galaxy Bias and Halo-Occupation Numbers from Large-Scale Clustering
We show that current surveys have at least as much signal to noise in
higher-order statistics as in the power spectrum at weakly nonlinear scales. We
discuss how one can use this information to determine the mean of the galaxy
halo occupation distribution (HOD) using only large-scale information, through
galaxy bias parameters determined from the galaxy bispectrum and trispectrum.
After introducing an averaged, reasonably fast to evaluate, trispectrum
estimator, we show that the expected errors on linear and quadratic bias
parameters can be reduced by at least 20-40%. Also, the inclusion of the
trispectrum information, which is sensitive to "three-dimensionality" of
structures, helps significantly in constraining the mass dependence of the HOD
mean. Our approach depends only on adequate modeling of the abundance and
large-scale clustering of halos and thus is independent of details of how
galaxies are distributed within halos. This provides a consistency check on the
traditional approach of using two-point statistics down to small scales, which
necessarily makes more assumptions. We present a detailed forecast of how well
our approach can be carried out in the case of the SDSS.Comment: 16 pages, 9 figure
On the streaming motions of haloes and galaxies
A simple model of how objects of different masses stream towards each other
as they cluster gravitationally is described. The model shows how the mean
streaming velocity of dark matter particles is related to the motions of the
parent dark matter haloes. It also provides a reasonably accurate description
of how the pairwise velocity dispersion of dark matter particles differs from
that of the parent haloes. The analysis is then extended to describe the
streaming motions of galaxies. This shows explicitly that the streaming motions
measured in a given galaxy sample depend on how the sample was selected, and
shows how to account for this dependence on sample selection. In addition,we
show that the pairwise dispersion should also depend on sample type. Our model
predicts that, on small scales, redshift space distortions should affect red
galaxies more strongly than blue.Comment: 10 pages, submitted to MNRA
Large-scale Bias and Efficient Generation of Initial Conditions for Non-Local Primordial Non-Gaussianity
We study the scale-dependence of halo bias in generic (non-local) primordial
non-Gaussian (PNG) initial conditions of the type motivated by inflation,
parametrized by an arbitrary quadratic kernel. We first show how to generate
non-local PNG initial conditions with minimal overhead compared to local PNG
models for a general class of primordial bispectra that can be written as
linear combinations of separable templates. We run cosmological simulations for
the local, and non-local equilateral and orthogonal models and present results
on the scale-dependence of halo bias. We also derive a general formula for the
Fourier-space bias using the peak-background split (PBS) in the context of the
excursion set approach to halos and discuss the difference and similarities
with the known corresponding result from local bias models. Our PBS bias
formula generalizes previous results in the literature to include non-Markovian
effects and non-universality of the mass function and are in better agreement
with measurements in numerical simulations than previous results for a variety
of halo masses, redshifts and halo definitions. We also derive for the first
time quadratic bias results for arbitrary non-local PNG, and show that
non-linear bias loops give small corrections at large-scales. The resulting
well-behaved perturbation theory paves the way to constrain non-local PNG from
measurements of the power spectrum and bispectrum in galaxy redshift surveys.Comment: 43 pages, 10 figures. v2: references added. 2LPT parallel code for
generating non-local PNG initial conditions available at
http://cosmo.nyu.edu/roman/2LP
Gravity and Large-Scale Non-local Bias
The relationship between galaxy and matter overdensities, bias, is most often
assumed to be local. This is however unstable under time evolution, we provide
proofs under several sets of assumptions. In the simplest model galaxies are
created locally and linearly biased at a single time, and subsequently move
with the matter (no velocity bias) conserving their comoving number density (no
merging). We show that, after this formation time, the bias becomes unavoidably
non-local and non-linear at large scales. We identify the non-local
gravitationally induced fields in which the galaxy overdensity can be expanded,
showing that they can be constructed out of the invariants of the deformation
tensor (Galileons). In addition, we show that this result persists if we
include an arbitrary evolution of the comoving number density of tracers. We
then include velocity bias, and show that new contributions appear, a dipole
field being the signature at second order. We test these predictions by
studying the dependence of halo overdensities in cells of fixed matter density:
measurements in simulations show that departures from the mean bias relation
are strongly correlated with the non-local gravitationally induced fields
identified by our formalism. The effects on non-local bias seen in the
simulations are most important for the most biased halos, as expected from our
predictions. The non-locality seen in the simulations is not fully captured by
assuming local bias in Lagrangian space. Accounting for these effects when
modeling galaxy bias is essential for correctly describing the dependence on
triangle shape of the galaxy bispectrum, and hence constraining cosmological
parameters and primordial non-Gaussianity. We show that using our formalism we
remove an important systematic in the determination of bias parameters from the
galaxy bispectrum, particularly for luminous galaxies. (abridged)Comment: 26 pages, 9 figures. v2: improved appendix
Halo Sampling, Local Bias and Loop Corrections
We develop a new test of local bias, by constructing a locally biased halo
density field from sampling the dark matter-halo distribution. Our test differs
from conventional tests in that it preserves the full scatter in the bias
relation and it does not rely on perturbation theory. We put forward that bias
parameters obtained using a smoothing scale R can only be applied to computing
the halo power spectrum at scales k ~ 1/R. Our calculations can automatically
include the running of bias parameters and give vanishingly small loop
corrections at low-k. Our proposal results in much better agreement of the
sampling and perturbation theory results with simulations. In particular,
unlike the standard interpretation of local bias in the literature, our
treatment of local bias does not generate a constant power in the low-k limit.
We search for extra noise in the Poisson corrected halo power spectrum at
wavenumbers below its turn-over and find no evidence of significant positive
noise (as predicted by the standard interpretation) while we find evidence of
negative noise coming from halo exclusion for very massive halos. Using
perturbation theory and our non-perturbative sampling technique we also
demonstrate that nonlocal bias effects discovered recently in simulations
impact the power spectrum only at the few percent level in the weakly nonlinear
regime.Comment: 25 pages, 14 figures; V2: significant revision including more details
about halo exclusion and low-k noise. Conclusions unchange
PTHalos: A fast method for generating mock galaxy distributions
Current models of galaxy formation applied to understanding the large-scale
structure of the universe have two parts. The first is an accurate solution of
the equations of motion for the dark matter due to gravitational clustering.
The second consists of making physically reasonable approximations to the
behavior of baryons inside dark matter halos. The first uses large,
computationally intensive, -body simulations. We argue that because the
second step is, at least at present, uncertain, it is possible to obtain
similar galaxy distributions without solving the first step exactly. We
describe an algorithm which is several orders of magnitude faster than n-body
simulations, but which is, nevertheless, rather accurate. The algorithm
combines perturbation theory with virialized halo models of the nonlinear
density and velocity fields. For two- and three-point statistics the resulting
fields are exact on large scales, and rather accurate well into the nonlinear
regime, particularly for two-point statistics in real and redshift space. We
then show how to use this algorithm to generate mock galaxy distributions from
halo occupation numbers. As a first application, we show that it provides a
good description of the clustering of galaxies in the PSCz survey. We also
discuss applications to the estimation of non-Gaussian contributions to error
bars and covariance matrix of the power spectrum, in real and redshift space,
for galaxies and dark matter. The results for the latter show good agreement
with simulations, supporting the use of our method to constrain cosmological
parameters from upcoming galaxy surveys.Comment: 13 pages, 10 figures. (references added
Remote sensing of night lights: a review and an outlook for the future
This is the author accepted manuscript. The final version is available from Elsevier via the DOI in this recordRemote sensing of night light emissions in the visible band offers a unique opportunity to directly observe human activity from space. This has allowed a host of applications including mapping urban areas, estimating population and GDP, monitoring disasters and conflicts. More recently, remotely sensed night lights data have found use in understanding the environmental impacts of light emissions (light pollution), including their impacts on human health. In this review, we outline the historical development of night-time optical sensors up to the current state of the art sensors, highlight various applications of night light data, discuss the special challenges associated with remote sensing of night lights with a focus on the limitations of current sensors, and provide an outlook for the future of remote sensing of night lights. While the paper mainly focuses on space borne remote sensing, ground based sensing of night-time brightness for studies on astronomical and ecological light pollution, as well as for calibration and validation of space borne data, are also discussed. Although the development of night light sensors lags behind day-time sensors, we demonstrate that the field is in a stage of rapid development. The worldwide transition to LED lights poses a particular challenge for remote sensing of night lights, and strongly highlights the need for a new generation of space borne night lights instruments. This work shows that future sensors are needed to monitor temporal changes during the night (for example from a geostationary platform or constellation of satellites), and to better understand the angular patterns of light emission (roughly analogous to the BRDF in daylight sensing). Perhaps most importantly, we make the case that higher spatial resolution and multispectral sensors covering the range from blue to NIR are needed to more effectively identify lighting technologies, map urban functions, and monitor energy use.European Union Horizon 2020Helmholtz AssociationNatural Environment Research Council (NERC)Chinese Academy of ScienceLeibniz AssociationIGB Leibniz Institut
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