377 research outputs found
CMB map restoration
Estimating the cosmological microwave background is of utmost importance for
cosmology. However, its estimation from full-sky surveys such as WMAP or more
recently Planck is challenging: CMB maps are generally estimated via the
application of some source separation techniques which never prevent the final
map from being contaminated with noise and foreground residuals. These spurious
contaminations whether noise or foreground residuals are well-known to be a
plague for most cosmologically relevant tests or evaluations; this includes CMB
lensing reconstruction or non-Gaussian signatures search. Noise reduction is
generally performed by applying a simple Wiener filter in spherical harmonics;
however this does not account for the non-stationarity of the noise. Foreground
contamination is usually tackled by masking the most intense residuals detected
in the map, which makes CMB evaluation harder to perform. In this paper, we
introduce a novel noise reduction framework coined LIW-Filtering for Linear
Iterative Wavelet Filtering which is able to account for the noise spatial
variability thanks to a wavelet-based modeling while keeping the highly desired
linearity of the Wiener filter. We further show that the same filtering
technique can effectively perform foreground contamination reduction thus
providing a globally cleaner CMB map. Numerical results on simulated but
realistic Planck data are provided
PRISM: Sparse Recovery of the Primordial Power Spectrum
The primordial power spectrum describes the initial perturbations in the
Universe which eventually grew into the large-scale structure we observe today,
and thereby provides an indirect probe of inflation or other
structure-formation mechanisms. Here, we introduce a new method to estimate
this spectrum from the empirical power spectrum of cosmic microwave background
(CMB) maps.
A sparsity-based linear inversion method, coined \textbf{PRISM}, is
presented. This technique leverages a sparsity prior on features in the
primordial power spectrum in a wavelet basis to regularise the inverse problem.
This non-parametric approach does not assume a strong prior on the shape of the
primordial power spectrum, yet is able to correctly reconstruct its global
shape as well as localised features. These advantages make this method robust
for detecting deviations from the currently favoured scale-invariant spectrum.
We investigate the strength of this method on a set of WMAP 9-year simulated
data for three types of primordial power spectra: a nearly scale-invariant
spectrum, a spectrum with a small running of the spectral index, and a spectrum
with a localised feature. This technique proves to easily detect deviations
from a pure scale-invariant power spectrum and is suitable for distinguishing
between simple models of the inflation. We process the WMAP 9-year data and
find no significant departure from a nearly scale-invariant power spectrum with
the spectral index .
A high resolution primordial power spectrum can be reconstructed with this
technique, where any strong local deviations or small global deviations from a
pure scale-invariant spectrum can easily be detected
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&
Joint Planck and WMAP CMB Map Reconstruction
We present a novel estimate of the cosmological microwave background (CMB)
map by combining the two latest full-sky microwave surveys: WMAP nine-year and
Planck PR1. The joint processing benefits from a recently introduced component
separation method coined "local-generalized morphological component analysis''
(LGMCA) based on the sparse distribution of the foregrounds in the wavelet
domain. The proposed estimation procedure takes advantage of the IRIS 100
micron as an extra observation on the galactic center for enhanced dust
removal. We show that this new CMB map presents several interesting aspects: i)
it is a full sky map without using any inpainting or interpolating method, ii)
foreground contamination is very low, iii) the Galactic center is very clean,
with especially low dust contamination as measured by the cross-correlation
between the estimated CMB map and the IRIS 100 micron map, and iv) it is free
of thermal SZ contamination.Comment: Astronomy and Astrophysics, accepte
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
PRISM: Recovery of the primordial spectrum from Planck data
The primordial power spectrum describes the initial perturbations that seeded
the large-scale structure we observe today. It provides an indirect probe of
inflation or other structure-formation mechanisms. In this letter, we recover
the primordial power spectrum from the Planck PR1 dataset, using our recently
published algorithm PRISM. PRISM is a sparsity-based inversion method, that
aims at recovering features in the primordial power spectrum from the empirical
power spectrum of the cosmic microwave background (CMB). This ill-posed inverse
problem is regularised using a sparsity prior on features in the primordial
power spectrum in a wavelet dictionary. Although this non-parametric method
does not assume a strong prior on the shape of the primordial power spectrum,
it is able to recover both its general shape and localised features. As a
results, this approach presents a reliable way of detecting deviations from the
currently favoured scale-invariant spectrum. We applied PRISM to 100 simulated
Planck data to investigate its performance on Planck-like data. We also tested
the algorithm's ability to recover a small localised feature at
Mpc, which caused a large dip at in the angular power
spectrum. We then applied PRISM to the Planck PR1 power spectrum to recover the
primordial power spectrum. We find no significant departures from the fiducial
Planck PR1 near scale-invariant primordial power spectrum with
and .Comment: 4 pages, 2 figures, Accepted in A&A; Updated to match the final
accepted versio
WMAP 9-year CMB estimation using sparsity
Recovering the Cosmic Microwave Background (CMB) from WMAP data requires
galactic foreground emissions to be accurately separated out. Most component
separation techniques rely on second order statistics such as Internal Linear
Combination (ILC) techniques. In this paper, we present a new WMAP 9-year CMB
map, with 15 arcmin resolution, which is reconstructed using a recently
introduced sparse component separation technique, coined Local Generalized
Morphological Component Analysis (LGMCA). LGMCA emphasizes on the sparsity of
the components to be retrieved in the wavelet domain. We show that although
derived from a radically different separation criterion ({i.e. sparsity), the
LGMCA-WMAP 9 map and its power spectrum are fully consistent with their more
recent estimates from WMAP 9.Comment: Submitted to A&A (revised
Hepatitis B virus receptors and molecular drug targets
Chronic hepatitis B virus (HBV) infection is a leading cause of liver disease worldwide. Virus-induced diseases include cirrhosis, liver failure and hepatocellular carcinoma. Current therapeutic strategies may at best control infection without reaching cure. Complementary antiviral strategies aimed at viral cure are therefore urgently needed. HBV entry is the first step of the infection cycle, which leads to the formation of cccDNA and the establishment of chronic infection. Viral entry may thus represent an attractive target for antiviral therapy. This review summarizes the molecular virology and cell biology of HBV entry, including the discovery and development of new HBV entry inhibitors, and discusses their potential in future treatment of HBV infection
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