2,454 research outputs found
Simulation of a method to directly image exoplanets around multiple stars systems
Direct imaging of extra-solar planets has now become a reality, especially
with the deployment and commissioning of the first generation of specialized
ground-based instruments such as the GPI, SPHERE, P1640 and SCExAO. These
systems will allow detection of planets 1e7 times fainter than their host star.
For space-based missions, such as EXCEDE, EXO-C, EXO-S, WFIRST-AFTA,
different teams have shown in laboratories contrasts reaching 1e-10 within a
few diffraction limits from the star using a combination of a coronagraph to
suppress light coming from the host star and a wavefront control system. These
demonstrations use a deformable mirror (DM) to remove residual starlight
(speckles) created by the imperfections of telescope. However, all these
current and future systems focus on detecting faint planets around a single
host star or unresolved binaries/multiples, while several targets or planet
candidates are located around nearby binary stars such as our neighbor star
Alpha Centauri.
Until now, it has been thought that removing the light of a companion star is
impossible with the current technology, excluding binary star systems from
target lists of direct imaging missions. Direct imaging around binaries or
multiples systems at a level of contrast allowing Earth-like planets detection
is challenging because the region of interest, where a dark zone is essential,
is contaminated by the light coming from the host star's companion. We propose
a method to simultaneously correct aberration sand diffraction of light coming
from the target star. This method works even if the companion star is outside
the control region of the DM (beyond its half-Nyquist frequency), by taking
advantage of aliasing effects.Comment: 8 pages, 13 figures, SPIE Astronomical Telescope and Instrumentation
conferenc
Do remittances affect poverty and inequality ? Evidence from Mali.
Using a 2006 household survey in Mali, we compare current poverty rates and inequality levels with counterfactual ones in the absence of migration and remittances. With proper hypotheses on migrants and a selection model, we are able to impute a counterfactual income for households currently receiving remittances. We show that remittances reduce poverty rates by 5% to 11% and the Gini coefficient by about 5%. Households in the bottom quintiles are more dependent on remittances, which are less substitutable by additional workforce.Indicateurs de pauvreté; Mali; Envois de fonds; Travailleurs migrants;
Stochastic Low-Rank Kernel Learning for Regression
We present a novel approach to learn a kernel-based regression function. It
is based on the useof conical combinations of data-based parameterized kernels
and on a new stochastic convex optimization procedure of which we establish
convergence guarantees. The overall learning procedure has the nice properties
that a) the learned conical combination is automatically designed to perform
the regression task at hand and b) the updates implicated by the optimization
procedure are quite inexpensive. In order to shed light on the appositeness of
our learning strategy, we present empirical results from experiments conducted
on various benchmark datasets.Comment: International Conference on Machine Learning (ICML'11), Bellevue
(Washington) : United States (2011
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