234 research outputs found
Robust, data-driven inference in non-linear cosmostatistics
We discuss two projects in non-linear cosmostatistics applicable to very
large surveys of galaxies. The first is a Bayesian reconstruction of galaxy
redshifts and their number density distribution from approximate, photometric
redshift data. The second focuses on cosmic voids and uses them to construct
cosmic spheres that allow reconstructing the expansion history of the Universe
using the Alcock-Paczynski test. In both cases we find that non-linearities
enable the methods or enhance the results: non-linear gravitational evolution
creates voids and our photo-z reconstruction works best in the highest density
(and hence most non-linear) portions of our simulations.Comment: 14 pages, 10 figures. Talk given at "Statistical Challenges in Modern
Astronomy V," held at Penn Stat
Linearisation with Cosmological Perturbation Theory
We propose a new method to linearise cosmological mass density fields using
higher order Lagrangian perturbation theory (LPT). We demonstrate that a given
density field can be expressed as the sum of a linear and a nonlinear component
which are tightly coupled to each other by the tidal field tensor within the
LPT framework. The linear component corresponds to the initial density field in
Eulerian coordinates, and its mean relation with the total field can be
approximated by a logarithm (giving theoretical support to recent attempts to
find such component). We also propose to use a combination of the linearisation
method and the continuity equation to find the mapping between Eulerian and
Lagrangian coordinates. In addition, we note that this method opens the
possibility of use directly higher order LPT on nonlinear fields. We test our
linearization scheme by applying it to the z~0.5 density field from an N-body
simulation. We find that the linearised version of the full density field can
be successfully recovered on >~5 h^{-1}Mpc, reducing the skewness and kurtosis
of the distribution by about one and two orders of magnitude, respectively.
This component can also be successfully traced back in time, converging towards
the initial unevolved density field at z~100. We anticipate a number of
applications of our results, from predicting velocity fields to estimates of
the initial conditions of the universe, passing by improved constraints on
cosmological parameters derived from galaxy clustering via reconstruction
methods.Comment: 14 pages, 8 figure
Scalar dark matter vortex stabilization with black holes
Galaxies and their dark-matter halos are commonly presupposed to spin. But it
is an open question how this spin manifests in halos and soliton cores made of
scalar dark matter (SDM, including fuzzy/wave/ultralight-axion dark matter).
One way spin could manifest in a necessarily irrotational SDM velocity field is
with a vortex. But recent results have cast doubt on this scenario, finding
that vortices are generally unstable except with substantial repulsive
self-interaction. In this paper, we introduce an alternative route to
stability: in both (non-relativistic) analytic calculations and simulations, a
black hole or other central mass at least as massive as a soliton can stabilize
a vortex within it. This conclusion may also apply to AU-scale halos bound to
the sun and stellar-mass-scale Bose stars.Comment: Accepted by JCAP. 22 pages, 5 figures. Supplementary animations at
https://doi.org/10.5281/zenodo.7675830 or
https://www.youtube.com/playlist?list=PLHrf0iQS5SY7Xt2sjqskF3kmHd00Hrdf
Probing dark energy with cluster counts and cosmic shear power spectra: including the full covariance
(Abridged) Combining cosmic shear power spectra and cluster counts is
powerful to improve cosmological parameter constraints and/or test inherent
systematics. However they probe the same cosmic mass density field, if the two
are drawn from the same survey region, and therefore the combination may be
less powerful than first thought. We investigate the cross-covariance between
the cosmic shear power spectra and the cluster counts based on the halo model
approach, where the cross-covariance arises from the three-point correlations
of the underlying mass density field. Fully taking into account the
cross-covariance as well as non-Gaussian errors on the lensing power spectrum
covariance, we find a significant cross-correlation between the lensing power
spectrum signals at multipoles l~10^3 and the cluster counts containing halos
with masses M>10^{14}Msun. Including the cross-covariance for the combined
measurement degrades and in some cases improves the total signal-to-noise
ratios up to plus or minus 20% relative to when the two are independent. For
cosmological parameter determination, the cross-covariance has a smaller effect
as a result of working in a multi-dimensional parameter space, implying that
the two observables can be considered independent to a good approximation. We
also discuss that cluster count experiments using lensing-selected mass peaks
could be more complementary to cosmic shear tomography than mass-selected
cluster counts of the corresponding mass threshold. Using lensing selected
clusters with a realistic usable detection threshold (S/N~6 for a ground-based
survey), the uncertainty on each dark energy parameter may be roughly halved by
the combined experiments, relative to using the power spectra alone.Comment: 32 pages, 15 figures. Revised version, invited original contribution
to gravitational lensing focus issue, New Journal of Physic
ZOBOV: a parameter-free void-finding algorithm
ZOBOV (ZOnes Bordering On Voidness) is an algorithm that finds density
depressions in a set of points, without any free parameters, or assumptions
about shape. It uses the Voronoi tessellation to estimate densities, which it
uses to find both voids and subvoids. It also measures probabilities that each
void or subvoid arises from Poisson fluctuations. This paper describes the
ZOBOV algorithm, and the results from its application to the dark-matter
particles in a region of the Millennium Simulation. Additionally, the paper
points out an interesting high-density peak in the probability distribution of
dark-matter particle densities.Comment: 10 pages, 8 figures, MNRAS, accepted. Added explanatory figures, and
better edge-detection methods. ZOBOV code available at
http://www.ifa.hawaii.edu/~neyrinck/vobo
A Dynamical Classification of the Cosmic Web
A dynamical classification of the cosmic web is proposed. The large scale
environment is classified into four web types: voids, sheets, filaments and
knots. The classification is based on the evaluation of the deformation tensor,
i.e. the Hessian of the gravitational potential, on a grid. The classification
is based on counting the number of eigenvalues above a certain threshold,
lambda_th at each grid point, where the case of zero, one, two or three such
eigenvalues corresponds to void, sheet, filament or a knot grid point. The
collection of neighboring grid points, friends-of-friends, of the same web
attribute constitutes voids, sheets, filaments and knots as web objects.
A simple dynamical consideration suggests that lambda_th should be
approximately unity, upon an appropriate scaling of the deformation tensor. The
algorithm has been applied and tested against a suite of (dark matter only)
cosmological N-body simulations. In particular, the dependence of the volume
and mass filling fractions on lambda_th and on the resolution has been
calculated for the four web types. Also, the percolation properties of voids
and filaments have been studied.
Our main findings are: (a) Already at lambda_th = 0.1 the resulting web
classification reproduces the visual impression of the cosmic web. (b) Between
0.2 < lambda_th < 0.4, a system of percolated voids coexists with a net of
interconected filaments. This suggests a reasonable choice for lambda_th as the
parameter that defines the cosmic web. (c) The dynamical nature of the
suggested classification provides a robust framework for incorporating
environmental information into galaxy formation models, and in particular the
semi-analytical ones.Comment: 11 pages, 6 figures, submitted to MNRA
Thinking Outside the Box: Effects of Modes Larger than the Survey on Matter Power Spectrum Covariance
Considering the matter power spectrum covariance matrix, it has recently been
found that there is a potentially dominant effect on mildly non-linear scales
due to power in modes of size equal to and larger than the survey volume. This
{\it beat coupling} effect has been derived analytically in perturbation theory
and while it has been tested with simulations, some questions remain
unanswered. Moreover, there is an additional effect of these large modes, which
has so far not been included in analytic studies, namely the effect on the
estimated {\it average} density which enters the power spectrum estimate. In
this article, we work out analytic, perturbation theory based expressions
including both the beat coupling and this {\it local average effect} and we
show that while, when isolated, beat coupling indeed causes large excess
covariance in agreement with the literature, in a realistic scenario this is
compensated almost entirely by the local average effect, leaving only of the excess. We test our analytic expressions by comparison to a suite of
large N-body simulations. For the variances, we find excellent agreement with
the analytic expressions for Mpc at , while the
correlation coefficients agree to beyond Mpc. As expected, the
range of agreement increases towards higher redshift and decreases slightly
towards . We finish by including the large-mode effects in a full
covariance matrix description for arbitrary survey geometry and confirming its
validity using simulations. This may be useful as a stepping stone towards
building an actual galaxy (or other tracer's) power spectrum covariance matrix.
[abridged]Comment: 24 pages, 10 figures. Version accepted for publication in JCAP. Added
Figure 5 and Appendix
Unfolding the Hierarchy of Voids
We present a framework for the hierarchical identification and
characterization of voids based on the Watershed Void Finder. The Hierarchical
Void Finder is based on a generalization of the scale space of a density field
invoked in order to trace the hierarchical nature and structure of cosmological
voids. At each level of the hierarchy, the watershed transform is used to
identify the voids at that particular scale. By identifying the overlapping
regions between watershed basins in adjacent levels, the hierarchical void tree
is constructed. Applications on a hierarchical Voronoi model and on a set of
cosmological simulations illustrate its potential.Comment: 5 pages, 2 figure
SubHaloes going Notts: The SubHalo-Finder Comparison Project
We present a detailed comparison of the substructure properties of a single
Milky Way sized dark matter halo from the Aquarius suite at five different
resolutions, as identified by a variety of different (sub-)halo finders for
simulations of cosmic structure formation. These finders span a wide range of
techniques and methodologies to extract and quantify substructures within a
larger non-homogeneous background density (e.g. a host halo). This includes
real-space, phase-space, velocity-space and time- space based finders, as well
as finders employing a Voronoi tessellation, friends-of-friends techniques, or
refined meshes as the starting point for locating substructure.A common
post-processing pipeline was used to uniformly analyse the particle lists
provided by each finder. We extract quantitative and comparable measures for
the subhaloes, primarily focusing on mass and the peak of the rotation curve
for this particular study. We find that all of the finders agree extremely well
on the presence and location of substructure and even for properties relating
to the inner part part of the subhalo (e.g. the maximum value of the rotation
curve). For properties that rely on particles near the outer edge of the
subhalo the agreement is at around the 20 per cent level. We find that basic
properties (mass, maximum circular velocity) of a subhalo can be reliably
recovered if the subhalo contains more than 100 particles although its presence
can be reliably inferred for a lower particle number limit of 20. We finally
note that the logarithmic slope of the subhalo cumulative number count is
remarkably consistent and <1 for all the finders that reached high resolution.
If correct, this would indicate that the larger and more massive, respectively,
substructures are the most dynamically interesting and that higher levels of
the (sub-)subhalo hierarchy become progressively less important.Comment: 16 pages, 7 figures, 2 tables, Accepted for MNRA
Lung transplantation for acute respiratory distress syndrome:A multicenter experience
Acute respiratory distress syndrome (ARDS) is a rapidly progressive lung disease with a high mortality rate. Although lung transplantation (LTx) is a well-established treatment for a variety of chronic pulmonary diseases, LTx for acute lung failure (due to ARDS) remains controversial. We reviewed posttransplant outcome of ARDS patients from three high-volume European transplant centers. Demographics and clinical data were collected and analyzed. Viral infection was the main reason for ARDS (n = 7/13, 53.8%). All patients were admitted to ICU and required mechanical ventilation, 11/13 were supported with ECMO at the time of listing. They were granted a median LAS of 76 (IQR 50-85) and waited for a median of 3 days (IQR 1.5-14). Postoperatively, median length of mechanical ventilation was 33 days (IQR 17-52.5), median length of ICU and hospital stay were 39 days (IQR 19.5-58.5) and 54 days (IQR 43.5-127). Prolongation of peripheral postoperative ECMO was required in 7/13 (53.8%) patients with a median duration of 2 days (IQR 2-7). 30-day mortality was 7.7%, 1 and 5-year survival rates were calculated as 71.6% and 54.2%, respectively. Given the lack of alternative treatment options, the herein presented results support the concept of offering live-saving LTx to carefully selected ARDS patients
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