20,660 research outputs found
Sunyaev-Zel'dovich clusters reconstruction in multiband bolometer camera surveys
We present a new method for the reconstruction of Sunyaev-Zel'dovich (SZ)
galaxy clusters in future SZ-survey experiments using multiband bolometer
cameras such as Olimpo, APEX, or Planck. Our goal is to optimise SZ-Cluster
extraction from our observed noisy maps. We wish to emphasize that none of the
algorithms used in the detection chain is tuned on prior knowledge on the SZ
-Cluster signal, or other astrophysical sources (Optical Spectrum, Noise
Covariance Matrix, or covariance of SZ Cluster wavelet coefficients). First, a
blind separation of the different astrophysical components which contribute to
the observations is conducted using an Independent Component Analysis (ICA)
method. Then, a recent non linear filtering technique in the wavelet domain,
based on multiscale entropy and the False Discovery Rate (FDR) method, is used
to detect and reconstruct the galaxy clusters. Finally, we use the Source
Extractor software to identify the detected clusters. The proposed method was
applied on realistic simulations of observations. As for global detection
efficiency, this new method is impressive as it provides comparable results to
Pierpaoli et al. method being however a blind algorithm. Preprint with full
resolution figures is available at the URL:
w10-dapnia.saclay.cea.fr/Phocea/Vie_des_labos/Ast/ast_visu.php?id_ast=728Comment: Submitted to A&A. 32 Pages, text onl
Adaptive Langevin Sampler for Separation of t-Distribution Modelled Astrophysical Maps
We propose to model the image differentials of astrophysical source maps by
Student's t-distribution and to use them in the Bayesian source separation
method as priors. We introduce an efficient Markov Chain Monte Carlo (MCMC)
sampling scheme to unmix the astrophysical sources and describe the derivation
details. In this scheme, we use the Langevin stochastic equation for
transitions, which enables parallel drawing of random samples from the
posterior, and reduces the computation time significantly (by two orders of
magnitude). In addition, Student's t-distribution parameters are updated
throughout the iterations. The results on astrophysical source separation are
assessed with two performance criteria defined in the pixel and the frequency
domains.Comment: 12 pages, 6 figure
SZ and CMB reconstruction using Generalized Morphological Component Analysis
In the last decade, the study of cosmic microwave background (CMB) data has
become one of the most powerful tools to study and understand the Universe.
More precisely, measuring the CMB power spectrum leads to the estimation of
most cosmological parameters. Nevertheless, accessing such precious physical
information requires extracting several different astrophysical components from
the data. Recovering those astrophysical sources (CMB, Sunyaev-Zel'dovich
clusters, galactic dust) thus amounts to a component separation problem which
has already led to an intense activity in the field of CMB studies. In this
paper, we introduce a new sparsity-based component separation method coined
Generalized Morphological Component Analysis (GMCA). The GMCA approach is
formulated in a Bayesian maximum a posteriori (MAP) framework. Numerical
results show that this new source recovery technique performs well compared to
state-of-the-art component separation methods already applied to CMB data.Comment: 11 pages - Statistical Methodology - Special Issue on Astrostatistics
- in pres
Reconstructing the Stellar Mass Distributions of Galaxies Using S4G IRAC 3.6 and 4.5 μm Images. I. Correcting for Contamination by Polycyclic Aromatic Hydrocarbons, Hot Dust, and Intermediate-age Stars
With the aim of constructing accurate two-dimensional maps of the stellar mass distribution in nearby galaxies from Spitzer Survey of Stellar Structure in Galaxies 3.6 and 4.5 μm images, we report on the separation of the light from old stars from the emission contributed by contaminants. Results for a small sample of six disk galaxies (NGC 1566, NGC 2976, NGC 3031, NGC 3184, NGC 4321, and NGC 5194) with a range of morphological properties, dust content, and star formation histories are presented to demonstrate our approach. To isolate the old stellar light from contaminant emission (e.g., hot dust and the 3.3 μm polycyclic aromatic hydrocarbon (PAH) feature) in the IRAC 3.6 and 4.5 μm bands we use an independent component analysis (ICA) technique designed to separate statistically independent source distributions, maximizing the distinction in the [3.6]-[4.5] colors of the sources. The technique also removes emission from evolved red objects with a low mass-to-light ratio, such as asymptotic giant branch (AGB) and red supergiant (RSG) stars, revealing maps of the underlying old distribution of light with [3.6]-[4.5] colors consistent with the colors of K and M giants. The contaminants are studied by comparison with the non-stellar emission imaged at 8 μm, which is dominated by the broad PAH feature. Using the measured 3.6 μm/8 μm ratio to select individual contaminants, we find that hot dust and PAHs together contribute between ~5% and 15% to the integrated light at 3.6 μm, while light from regions dominated by intermediate-age (AGB and RSG) stars accounts for only 1%-5%. Locally, however, the contribution from either contaminant can reach much higher levels; dust contributes on average 22% to the emission in star-forming regions throughout the sample, while intermediate-age stars contribute upward of 50% in localized knots. The removal of these contaminants with ICA leaves maps of the old stellar disk that retain a high degree of structural information and are ideally suited for tracing stellar mass, as will be the focus in a companion paper
Wavelets, ridgelets and curvelets on the sphere
We present in this paper new multiscale transforms on the sphere, namely the
isotropic undecimated wavelet transform, the pyramidal wavelet transform, the
ridgelet transform and the curvelet transform. All of these transforms can be
inverted i.e. we can exactly reconstruct the original data from its
coefficients in either representation. Several applications are described. We
show how these transforms can be used in denoising and especially in a Combined
Filtering Method, which uses both the wavelet and the curvelet transforms, thus
benefiting from the advantages of both transforms. An application to component
separation from multichannel data mapped to the sphere is also described in
which we take advantage of moving to a wavelet representation.Comment: Accepted for publication in A&A. Manuscript with all figures can be
downloaded at http://jstarck.free.fr/aa_sphere05.pd
Compact source detection in multi-channel microwave surveys: from SZ clusters to polarized sources
In this paper we describe the state-of-the art status of multi-frequency
detection techniques for compact sources in microwave astronomy. From the
simplest cases where the spectral behaviour is well-known (i.e. thermal SZ
clusters) to the more complex cases where there is little a priori information
(i.e. polarized radio sources) we will review the main advances and the most
recent results in the detection problem.Comment: 13 pages, 4 figures. Accepted for publication in the Special Issue
"Astrophysical Foregrounds in Microwave Surveys" of the journal Advances in
Astronom
Sparsity and adaptivity for the blind separation of partially correlated sources
Blind source separation (BSS) is a very popular technique to analyze
multichannel data. In this context, the data are modeled as the linear
combination of sources to be retrieved. For that purpose, standard BSS methods
all rely on some discrimination principle, whether it is statistical
independence or morphological diversity, to distinguish between the sources.
However, dealing with real-world data reveals that such assumptions are rarely
valid in practice: the signals of interest are more likely partially
correlated, which generally hampers the performances of standard BSS methods.
In this article, we introduce a novel sparsity-enforcing BSS method coined
Adaptive Morphological Component Analysis (AMCA), which is designed to retrieve
sparse and partially correlated sources. More precisely, it makes profit of an
adaptive re-weighting scheme to favor/penalize samples based on their level of
correlation. Extensive numerical experiments have been carried out which show
that the proposed method is robust to the partial correlation of sources while
standard BSS techniques fail. The AMCA algorithm is evaluated in the field of
astrophysics for the separation of physical components from microwave data.Comment: submitted to IEEE Transactions on signal processin
Sparse component separation for accurate CMB map estimation
The Cosmological Microwave Background (CMB) is of premier importance for the
cosmologists to study the birth of our universe. Unfortunately, most CMB
experiments such as COBE, WMAP or Planck do not provide a direct measure of the
cosmological signal; CMB is mixed up with galactic foregrounds and point
sources. For the sake of scientific exploitation, measuring the CMB requires
extracting several different astrophysical components (CMB, Sunyaev-Zel'dovich
clusters, galactic dust) form multi-wavelength observations. Mathematically
speaking, the problem of disentangling the CMB map from the galactic
foregrounds amounts to a component or source separation problem. In the field
of CMB studies, a very large range of source separation methods have been
applied which all differ from each other in the way they model the data and the
criteria they rely on to separate components. Two main difficulties are i) the
instrument's beam varies across frequencies and ii) the emission laws of most
astrophysical components vary across pixels. This paper aims at introducing a
very accurate modeling of CMB data, based on sparsity, accounting for beams
variability across frequencies as well as spatial variations of the components'
spectral characteristics. Based on this new sparse modeling of the data, a
sparsity-based component separation method coined Local-Generalized
Morphological Component Analysis (L-GMCA) is described. Extensive numerical
experiments have been carried out with simulated Planck data. These experiments
show the high efficiency of the proposed component separation methods to
estimate a clean CMB map with a very low foreground contamination, which makes
L-GMCA of prime interest for CMB studies.Comment: submitted to A&
Planck CMB Anomalies: Astrophysical and Cosmological Secondary Effects and the Curse of Masking
Large-scale anomalies have been reported in CMB data with both WMAP and
Planck data. These could be due to foreground residuals and or systematic
effects, though their confirmation with Planck data suggests they are not due
to a problem in the WMAP or Planck pipelines. If these anomalies are in fact
primordial, then understanding their origin is fundamental to either validate
the standard model of cosmology or to explore new physics. We investigate three
other possible issues: 1) the trade-off between minimising systematics due to
foreground contamination (with a conservative mask) and minimising systematics
due to masking, 2) astrophysical secondary effects (the kinetic Doppler
quadrupole and kinetic Sunyaev-Zel'dovich effect), and 3) secondary
cosmological signals (the integrated Sachs-Wolfe effect). We address the
masking issue by considering new procedures that use both WMAP and Planck to
produce higher quality full-sky maps using the sparsity methodology (LGMCA
maps). We show the impact of masking is dominant over that of residual
foregrounds, and the LGMCA full-sky maps can be used without further processing
to study anomalies. We consider four official Planck PR1 and two LGMCA CMB
maps. Analysis of the observed CMB maps shows that only the low quadrupole and
quadrupole-octopole alignment seem significant, but that the planar octopole,
Axis of Evil, mirror parity and cold spot are not significant in nearly all
maps considered. After subtraction of astrophysical and cosmological secondary
effects, only the low quadrupole may still be considered anomalous, meaning the
significance of only one anomaly is affected by secondary effect subtraction
out of six anomalies considered. In the spirit of reproducible research all
reconstructed maps and codes will be made available for download here
http://www.cosmostat.org/anomaliesCMB.html.Comment: Summary of results given in Table 2. Accepted for publication in
JCAP, 4th August 201
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