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École Euclid de cosmologie 2017

Date: June 27 - July 8 2017

Venue: Fréjus, France

Website: http://ecole-euclid.cnrs.fr/programme-2017


Lecture ``Weak gravitational lensing'' (Le lentillage gravitationnel), Martin Kilbinger.

Find here links to the lecture notes, TD exercises, "tables rondes" topics, and other information.

  • Resources.
    • A great and detailed introduction to (weak) gravitational lensing are the 2005 Saas Fee lecture notes by Peter Schneider. Download Part I (Introduction to lensing) and Part III (Weak lensing) from my homepage.
    • Check out Sarah Bridle's video lectures on WL from 2014.
  • TD cycle 1+2, Data analysis.
    1.  We will work on a rather large (150 MB) weak-lensing catalogue from the public CFHTLenS web page. During the TD I will show instructions how to create and download this catalogue. For faster access, it will be available on the server during the school, and I will bring a few USB sticks.
      If you like, you can however download the catalogue on your laptop at home. Please have a look at the instructions (available soon).
    2. If you want to do the TD on your laptop, you'll need to download and install athena (the newest version 1.7).
    3.  For one of the bonus TD you'll need a new version of pallas.py (v 1.8beta). Download it here.
  • Lecture notes and exercise classes:
1703.06066_plot

PSF field learning based on Optimal Transport Distances

 

Authors: F. Ngolè Mboula, J-L. Starck
Journal: arXiv
Year: 2017
Download: ADS | arXiv

 


Abstract

Context: in astronomy, observing large fractions of the sky within a reasonable amount of time implies using large field-of-view (fov) optical instruments that typically have a spatially varying Point Spread Function (PSF). Depending on the scientific goals, galaxies images need to be corrected for the PSF whereas no direct measurement of the PSF is available. Aims: given a set of PSFs observed at random locations, we want to estimate the PSFs at galaxies locations for shapes measurements correction. Contributions: we propose an interpolation framework based on Sliced Optimal Transport. A non-linear dimension reduction is first performed based on local pairwise approximated Wasserstein distances. A low dimensional representation of the unknown PSFs is then estimated, which in turn is used to derive representations of those PSFs in the Wasserstein metric. Finally, the interpolated PSFs are calculated as approximated Wasserstein barycenters. Results: the proposed method was tested on simulated monochromatic PSFs of the Euclid space mission telescope (to be launched in 2020). It achieves a remarkable accuracy in terms of pixels values and shape compared to standard methods such as Inverse Distance Weighting or Radial Basis Function based interpolation methods.