793 research outputs found
Efficient data structures for masks on 2D grids
This article discusses various methods of representing and manipulating
arbitrary coverage information in two dimensions, with a focus on space- and
time-efficiency when processing such coverages, storing them on disk, and
transmitting them between computers. While these considerations were originally
motivated by the specific tasks of representing sky coverage and cross-matching
catalogues of astronomical surveys, they can be profitably applied in many
other situations as well.Comment: accepted by A&
ArtDeco: A beam deconvolution code for absolute CMB measurements
We present a method for beam deconvolution for cosmic microwave background
(CMB) anisotropy measurements. The code takes as input the time-ordered data,
along with the corresponding detector pointings and known beam shapes, and
produces as output the harmonic a_Tlm, a_Elm, and a_Blm coefficients of the
observed sky. From these one can further construct temperature and Q and U
polarisation maps. The method is applicable to absolute CMB measurements with
wide sky coverage, and is independent of the scanning strategy. We test the
code with extensive simulations, mimicking the resolution and data volume of
Planck 30GHz and 70GHz channels, but with exaggerated beam asymmetry. We apply
it to multipoles up to l=1700 and examine the results in both pixel space and
harmonic space. We also test the method also in presence of white noise.Comment: 15 page
Libsharp - spherical harmonic transforms revisited
We present libsharp, a code library for spherical harmonic transforms (SHTs),
which evolved from the libpsht library, addressing several of its shortcomings,
such as adding MPI support for distributed memory systems and SHTs of fields
with arbitrary spin, but also supporting new developments in CPU instruction
sets like the Advanced Vector Extensions (AVX) or fused multiply-accumulate
(FMA) instructions. The library is implemented in portable C99 and provides an
interface that can be easily accessed from other programming languages such as
C++, Fortran, Python etc. Generally, libsharp's performance is at least on par
with that of its predecessor; however, significant improvements were made to
the algorithms for scalar SHTs, which are roughly twice as fast when using the
same CPU capabilities. The library is available at
http://sourceforge.net/projects/libsharp/ under the terms of the GNU General
Public License
Cosmology inference at the field level from biased tracers in redshift-space
Cosmology inference of galaxy clustering at the field level with the EFT
likelihood in principle allows for extracting all non-Gaussian information from
quasi-linear scales, while robustly marginalizing over any astrophysical
uncertainties. A pipeline in this spirit is implemented in the
\texttt{LEFTfield} code, which we extend in this work to describe the
clustering of galaxies in redshift space. Our main additions are: the
computation of the velocity field in the LPT gravity model, the fully nonlinear
displacement of the evolved, biased density field to redshift space, and a
systematic expansion of velocity bias. We test the resulting analysis pipeline
by applying it to synthetic data sets with a known ground truth at increasing
complexity: mock data generated from the perturbative forward model itself,
sub-sampled matter particles, and dark matter halos in N-body simulations. By
fixing the initial-time density contrast to the ground truth, while varying the
growth rate , bias coefficients and noise amplitudes, we perform a stringent
set of checks. These show that indeed a systematic higher-order expansion of
the velocity bias is required to infer a growth rate consistent with the ground
truth within errors. Applied to dark matter halos, our analysis yields unbiased
constraints on at the level of a few percent for a variety of halo masses
at redshifts and for a broad range of cutoff scales
. Importantly,
deviations between true and inferred growth rate exhibit the scaling with halo
mass, redshift and cutoff that one expects based on the EFT of Large Scale
Structure. Further, we obtain a robust detection of velocity bias through its
effect on the redshift-space density field and are able to disentangle it from
higher-derivative bias contributions
Improved cosmic microwave background (de-)lensing using general spherical harmonic transforms
Deep cosmic microwave background polarization experiments allow a very
precise internal reconstruction of the gravitational lensing signal in
pricinple. For this aim, likelihood-based or Bayesian methods are typically
necessary, where very large numbers of lensing and delensing remappings on the
sphere are sometimes required before satisfactory convergence. We discuss here
an optimized piece of numerical code in some detail that is able to efficiently
perform both the lensing operation and its adjoint (closely related to
delensing) to arbitrary accuracy, using nonuniform fast Fourier transform
technology. Where applicable, we find that the code outperforms current
widespread software by a very wide margin. It is able to produce
high-resolution maps that are accurate enough for next-generation cosmic
microwave background experiments on the timescale of seconds on a modern
laptop. The adjoint operation performs similarly well and removes the need for
the computation of inverse deflection fields. This publicly available code
enables de facto efficient spherical harmonic transforms on completely
arbitrary grids, and it might be applied in other areas as well.Comment: 8 pages, 3 figures, final A&
Denoising, deconvolving and decomposing multi-domain photon observations- The D4PO algorithm
Astronomical imaging based on photon count data is a non-trivial task. In
this context we show how to denoise, deconvolve, and decompose multi-domain
photon observations. The primary objective is to incorporate accurate and well
motivated likelihood and prior models in order to give reliable estimates about
morphologically different but superimposed photon flux components present in
the data set. Thereby we denoise and deconvolve photon counts, while
simultaneously decomposing them into diffuse, point-like and uninteresting
background radiation fluxes. The decomposition is based on a probabilistic
hierarchical Bayesian parameter model within the framework of information field
theory (IFT). In contrast to its predecessor DPO, DPO reconstructs
multi-domain components. Thereby each component is defined over its own direct
product of multiple independent domains, for example location and energy.
DPO has the capability to reconstruct correlation structures over each of
the sub-domains of a component separately. Thereby the inferred correlations
implicitly define the morphologically different source components, except for
the spatial correlations of the point-like flux. Point-like source fluxes are
spatially uncorrelated by definition. The capabilities of the algorithm are
demonstrated by means of a synthetic, but realistic, mock data set, providing
spectral and spatial information about each detected photon. DPO
successfully denoised, deconvolved, and decomposed a photon count image into
diffuse, point-like and background flux, each being functions of location as
well as energy. Moreover, uncertainty estimates of the reconstructed fields as
well as of their correlation structure are provided employing their posterior
density function and accounting for the manifolds the domains reside on
Efficient wide-field radio interferometry response
Radio interferometers do not measure the sky brightness distribution directly
but rather a modified Fourier transform of it. Imaging algorithms, thus, need a
computational representation of the linear measurement operator and its
adjoint, irrespective of the specific chosen imaging algorithm. In this paper,
we present a C++ implementation of the radio interferometric measurement
operator for wide-field measurements which is based on "improved -stacking".
It can provide high accuracy (down to ), is based on a new
gridding kernel which allows smaller kernel support for given accuracy,
dynamically chooses kernel, kernel support and oversampling factor for maximum
performance, uses piece-wise polynomial approximation for cheap evaluations of
the gridding kernel, treats the visibilities in cache-friendly order, uses
explicit vectorisation if available and comes with a parallelisation scheme
which scales well also in the adjoint direction (which is a problem for many
previous implementations). The implementation has a small memory footprint in
the sense that temporary internal data structures are much smaller than the
respective input and output data, allowing in-memory processing of data sets
which needed to be read from disk or distributed across several compute nodes
before.Comment: 13 pages, 8 figure
Consistency tests of field level inference with the EFT likelihood
Analyzing the clustering of galaxies at the field level in principle promises
access to all the cosmological information available. Given this incentive, in
this paper we investigate the performance of field-based forward modeling
approach to galaxy clustering using the effective field theory (EFT) framework
of large-scale structure (LSS). We do so by applying this formalism to a set of
consistency and convergence tests on synthetic datasets. We explore the
high-dimensional joint posterior of LSS initial conditions by combining
Hamiltonian Monte Carlo sampling for the field of initial conditions, and slice
sampling for cosmology and model parameters. We adopt the Lagrangian
perturbation theory forward model from [1], up to second order, for the forward
model of biased tracers. We specifically include model mis-specifications in
our synthetic datasets within the EFT framework. We achieve this by generating
synthetic data at a higher cutoff scale , which controls which
Fourier modes enter the EFT likelihood evaluation, than the cutoff
used in the inference. In the presence of model mis-specifications, we find
that the EFT framework still allows for robust, unbiased joint inference of a)
cosmological parameters - specifically, the scaling amplitude of the initial
conditions - b) the initial conditions themselves, and c) the bias and noise
parameters. In addition, we show that in the purely linear case, where the
posterior is analytically tractable, our samplers fully explore the posterior
surface. We also demonstrate convergence in the cases of nonlinear forward
models. Our findings serve as a confirmation of the EFT field-based forward
model framework developed in [2-7], and as another step towards field-level
cosmological analyses of real galaxy surveys.Comment: 31 + 13 pages, 15 figures; Added 3 new figures, text cleanup and fix
typos; matching the version to be published in JCA
Acute symptomatic seizures in the emergency room: predictors and characteristics
Background: When treating patients with epileptic seizures in the emergency room (ER), it is of paramount importance to rapidly assess whether the seizure was acute symptomatic or unprovoked as the former points to a potentially life-threatening underlying condition. In this study, we seek to identify predictors and analyze characteristics of acute symptomatic seizures (ASS).
Methods: Data from patients presenting with seizures to highly frequented ERs of two sites of a university hospital were analyzed retrospectively. Seizures were classified as acute symptomatic or unprovoked according to definitions of the International League Against Epilepsy. Univariate and multivariate analysis were conducted to identify predictors; furthermore, characteristics of ASS were assessed.
Results: Finally, 695 patients were included, 24.5% presented with ASS. Variables independently associated with ASS comprised male sex (OR 3.173, 95% CI 1.972-5.104), no prior diagnosis of epilepsy (OR 11.235, 95% CI 7.195-17.537), and bilateral/generalized tonic-clonic seizure semiology (OR 2.982, 95% CI 1.172-7.588). Alcohol withdrawal was the most common cause of ASS (74.1%), with hemorrhagic stroke being the second most prevalent etiology. Neuroimaging was performed more often in patients with the final diagnosis of ASS than in those with unprovoked seizures (82.9% vs. 67.2%, p < 0.001). Patients with ASS were more likely to receive acute antiseizure medication in the ER (55.9% vs. 30.3%, p < 0.001).
Conclusions: In one quarter of patients presenting to the ER after an epileptic fit, the seizure had an acute symptomatic genesis. The independently associated variables may help to early identify ASS and initiate management of the underlying condition
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