421 research outputs found
Multiple-Images in the Cluster Lens Abell 2218: Constraining the Geometry of the Universe ?
In this Letter we present a detailed study of the lensing configuration in
the cluster Abell 2218. Four multiple-images systems with measured
spectroscopic redshifts have been identified in this cluster. These multiple
images are very useful to constrain accurately the mass distribution in the
cluster core, but they are also sensitive to the value of the geometrical
cosmological parameters of the Universe. Using a simplified maximum likelihood
analysis we find 0 < Omega_M < 0.30 assuming a flat Universe, and 0 < Omega_M <
0.33 and w < -0.85 for a flat Universe with dark energy. Interestingly, an
Einstein-de Sitter model is excluded at more than 4sigma. These constraints are
consistent with the current constraints derived with CMB anisotropies or
supernovae studies. The proposed method constitutes an independent test of the
geometrical cosmological parameters of the Universe and we discuss the limits
of this method and this particular application to Abell 2218. Application of
this method with more sophisticated tools and to a larger number of clusters or
with more multiple images constraints, will put stringent constraints on the
geometrical cosmological parameters.Comment: 5 pages, 3 figures. Accepted for publication by Astronomy &
Astrophysic
Ringing effects reduction by improved deconvolution algorithm Application to A370 CFHT image of gravitational arcs
We develop a self-consistent automatic procedure to restore informations from
astronomical observations. It relies on both a new deconvolution algorithm
called LBCA (Lower Bound Constraint Algorithm) and the use of the Wiener
filter. In order to explore its scientific potential for strong and weak
gravitational lensing, we process a CFHT image of the galaxies cluster Abell
370 which exhibits spectacular strong gravitational lensing effects. A high
quality restoration is here of particular interest to map the dark matter
within the cluster. We show that the LBCA turns out specially efficient to
reduce ringing effects introduced by classical deconvolution algorithms in
images with a high background. The method allows us to make a blind detection
of the radial arc and to recover morphological properties similar to
thoseobserved from HST data. We also show that the Wiener filter is suitable to
stop the iterative process before noise amplification, using only the
unrestored data.Comment: A&A in press 9 pages 9 figure
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