51 research outputs found
Constraint of Void Bias on Primordial non-Gaussianity
We study the large-scale bias parameter of cosmic voids with primordial
non-Gaussian (PNG) initial conditions of the local type. In this scenario, the
dark matter halo bias exhibits a characteristic scale dependence on large
scales, which has been recognized as one of the most promising probes of the
local PNG. Using a suite of -body simulations with Gaussian and non-Gaussian
initial conditions, we find that the void bias features scale-dependent
corrections on large scales, similar to its halo counterpart. We find excellent
agreement between the numerical measurement of the PNG void bias and the
general peak-background split prediction. Contrary to halos, large voids
anti-correlate with the dark matter density field, and the large-scale Gaussian
void bias ranges from positive to negative values depending on void size and
redshift. Thus, the information in the clustering of voids can be complementary
to that of the halos. Using the Fisher matrix formalism for multiple tracers,
we demonstrate that including the scale-dependent bias information from voids,
constraints on the PNG parameter can be tightened by a factor of
two compared to the accessible information from halos alone, when the sampling
density of tracers reaches .Comment: 7 pages, 4 figures; dn/dlnsigma_8 prediction implemented and
excellent agreement with simulation results obtained. Matched to published
versio
Large-Scale Clustering of Cosmic Voids
We study the clustering of voids using -body simulations and simple
theoretical models. The excursion-set formalism describes fairly well the
abundance of voids identified with the watershed algorithm, although the void
formation threshold required is quite different from the spherical collapse
value. The void cross bias is measured and its large-scale value
is found to be consistent with the peak background split results. A simple
fitting formula for is found. We model the void auto-power
spectrum taking into account the void biasing and exclusion effect. A good fit
to the simulation data is obtained for voids with radii 30 Mpc/,
especially when the void biasing model is extended to 1-loop order. However,
the best-fit bias parameters do not agree well with the peak-background split
results. Being able to fit the void auto-power spectrum is particularly
important not only because it is the direct observable in galaxy surveys, but
also our method enables us to treat the bias parameters as nuisance parameters,
which are sensitive to the techniques used to identify voids.Comment: 20 pages, 14 figures, minor changes to match published versio
Universal Density Profile for Cosmic Voids
We present a simple empirical function for the average density profile of
cosmic voids, identified via the watershed technique in CDM N-body
simulations. This function is universal across void size and redshift,
accurately describing a large radial range of scales around void centers with
only two free parameters. In analogy to halo density profiles, these parameters
describe the scale radius and the central density of voids. While we initially
start with a more general four-parameter model, we find two of its parameters
to be redundant, as they follow linear trends with the scale radius in two
distinct regimes of the void sample, separated by its compensation scale.
Assuming linear theory, we derive an analytic formula for the velocity profile
of voids and find an excellent agreement with the numerical data as well. In
our companion paper [Sutter et al., Mon. Not. R. Astron. Soc. 442, 462 (2014)]
the presented density profile is shown to be universal even across tracer type,
properly describing voids defined in halo and galaxy distributions of varying
sparsity, allowing us to relate various void populations by simple rescalings.
This provides a powerful framework to match theory and simulations with
observational data, opening up promising perspectives to constrain competing
models of cosmology and gravity.Comment: 5 pages, 3 figures. Matches PRL published version after minor
correction
Probing cosmology and gravity with redshift-space distortions around voids
Cosmic voids in the large-scale structure of the Universe affect the peculiar
motions of objects in their vicinity. Although these motions are difficult to
observe directly, the clustering pattern of their surrounding tracers in
redshift space is influenced in a unique way. This allows to investigate the
interplay between densities and velocities around voids, which is solely
dictated by the laws of gravity. With the help of -body simulations and
derived mock-galaxy catalogs we calculate the average density fluctuations
around voids identified with a watershed algorithm in redshift space and
compare the results with the expectation from general relativity and the
CDM model. We find linear theory to work remarkably well in describing
the dynamics of voids. Adopting a Bayesian inference framework, we explore the
full posterior of our model parameters and forecast the achievable accuracy on
measurements of the growth rate of structure and the geometric distortion
through the Alcock-Paczynski effect. Systematic errors in the latter are
reduced from to when peculiar velocities are taken into
account. The relative parameter uncertainties in galaxy surveys with number
densities comparable to the SDSS MAIN (CMASS) sample probing a volume of
yield () and
(), respectively. At this level of precision
the linear-theory model becomes systematics dominated, with parameter biases
that fall beyond these values. Nevertheless, the presented method is highly
model independent; its viability lies in the underlying assumption of
statistical isotropy of the Universe.Comment: 38 pages, 14 figures. Published in JCAP. Referee comments
incorporated, typos corrected, references added. Considerably improved
results thanks to consideration of full covariance matrix in the MCMC
analysi
Why Cosmic Voids Matter: Nonlinear Structure & Linear Dynamics
We use the Magneticum suite of state-of-the-art hydrodynamical simulations to
identify cosmic voids based on the watershed technique and investigate their
most fundamental properties across different resolutions in mass and scale.
This encompasses the distributions of void sizes, shapes, and content, as well
as their radial density and velocity profiles traced by the distribution of
cold dark matter particles and halos. We also study the impact of various
tracer properties, such as their sparsity and mass, and the influence of void
merging on these summary statistics. Our results reveal that all of the
analyzed void properties are physically related to each other and describe
universal characteristics that are largely independent of tracer type and
resolution. Most notably, we find that the motion of tracers around void
centers is perfectly consistent with linear dynamics, both for individual, as
well as stacked voids. Despite the large range of scales accessible in our
simulations, we are unable to identify the occurrence of nonlinear dynamics
even inside voids of only a few Mpc in size. This suggests voids to be among
the most pristine probes of cosmology down to scales that are commonly referred
to as highly nonlinear in the field of large-scale structure.Comment: 35 pages (+ references), 22 figures. Key results in figure 22.
Accepted for publication in JCA
The bias of cosmic voids in the presence of massive neutrinos
Cosmic voids offer an extraordinary opportunity to study the effects of
massive neutrinos on cosmological scales. Because they are freely streaming,
neutrinos can penetrate the interior of voids more easily than cold dark matter
or baryons, which makes their relative contribution to the mass budget in voids
much higher than elsewhere in the Universe. In simulations it has recently been
shown how various characteristics of voids in the matter distribution are
affected by neutrinos, such as their abundance, density profiles, dynamics, and
clustering properties. However, the tracers used to identify voids in
observations (e.g., galaxies or halos) are affected by neutrinos as well, and
isolating the unique neutrino signatures inherent to voids becomes more
difficult. In this paper we make use of the DEMNUni suite of simulations to
investigate the clustering bias of voids in Fourier space as a function of
their core density and compensation. We find a clear dependence on the sum of
neutrino masses that remains significant even for void statistics extracted
from halos. In particular, we observe that the amplitude of the linear void
bias increases with neutrino mass for voids defined in dark matter, whereas
this trend gets reversed and slightly attenuated when measuring the relative
void-halo bias using voids identified in the halo distribution. Finally, we
argue how the original behaviour can be restored when considering observations
of the total matter distribution (e.g. via weak lensing), and comment on
scale-dependent effects in the void bias that may provide additional
information on neutrinos in the future.Comment: 23 pages, 18 figure
Dark matter voids in the SDSS galaxy survey
What do we know about voids in the dark matter distribution given the Sloan
Digital Sky Survey (SDSS) and assuming the model? Recent
application of the Bayesian inference algorithm BORG to the SDSS Data Release 7
main galaxy sample has generated detailed Eulerian and Lagrangian
representations of the large-scale structure as well as the possibility to
accurately quantify corresponding uncertainties. Building upon these results,
we present constrained catalogs of voids in the Sloan volume, aiming at a
physical representation of dark matter underdensities and at the alleviation of
the problems due to sparsity and biasing on galaxy void catalogs. To do so, we
generate data-constrained reconstructions of the presently observed large-scale
structure using a fully non-linear gravitational model. We then find and
analyze void candidates using the VIDE toolkit. Our methodology therefore
predicts the properties of voids based on fusing prior information from
simulations and data constraints. For usual void statistics (number function,
ellipticity distribution and radial density profile), all the results obtained
are in agreement with dark matter simulations. Our dark matter void candidates
probe a deeper void hierarchy than voids directly based on the observed
galaxies alone. The use of our catalogs therefore opens the way to
high-precision void cosmology at the level of the dark matter field. We will
make the void catalogs used in this work available at
http://www.cosmicvoids.net.Comment: 15 pages, 6 figures, matches JCAP published version, void catalogs
publicly available at http://www.cosmicvoids.ne
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