S. Bridle
Results of the GREAT08 Challenge : an image analysis competition for cosmological lensing
Bridle, S.; Balan, S.T.; Bethge, M.; Gentile, M.; Harmeling, S.; Heymans, C.; Hirsch, M.; Hosseini, R.; Jarvis, M.; Kirk, D.; Kitching, T.; Kuijken, K.; Lewis, A.; Paulin-Henriksson, S.; Schölkopf, B.; Velander, M.; Voigt, L.; Witherick, D.; Amara, A.; Bernstein, G.; Courbin, F.; Gill, M.; Heavens, A.; Mandelbaum, R.; Massey, R.; Moghaddam, B.; Rassat, Anais; Réfrégier, A.; Rhodes, J.; Schrabback, T.; Shawe-Taylor, J.; Shmakova, M.; van Waerbeke, L.; Wittman, D.
Authors
S.T. Balan
M. Bethge
M. Gentile
S. Harmeling
C. Heymans
M. Hirsch
R. Hosseini
M. Jarvis
D. Kirk
T. Kitching
K. Kuijken
A. Lewis
S. Paulin-Henriksson
B. Schölkopf
M. Velander
L. Voigt
D. Witherick
A. Amara
G. Bernstein
F. Courbin
M. Gill
A. Heavens
R. Mandelbaum
Professor Richard Massey r.j.massey@durham.ac.uk
Professor
B. Moghaddam
Anais Rassat
A. Réfrégier
J. Rhodes
T. Schrabback
J. Shawe-Taylor
M. Shmakova
L. van Waerbeke
D. Wittman
Abstract
We present the results of the Gravitational LEnsing Accuracy Testing 2008 (GREAT08) Challenge, a blind analysis challenge to infer weak gravitational lensing shear distortions from images. The primary goal was to stimulate new ideas by presenting the problem to researchers outside the shear measurement community. Six GREAT08 Team methods were presented at the launch of the Challenge and five additional groups submitted results during the 6-month competition. Participants analyzed 30 million simulated galaxies with a range in signal-to-noise ratio, point spread function ellipticity, galaxy size and galaxy type. The large quantity of simulations allowed shear measurement methods to be assessed at a level of accuracy suitable for currently planned future cosmic shear observations for the first time. Different methods perform well in different parts of simulation parameter space and come close to the target level of accuracy in several of these. A number of fresh ideas have emerged as a result of the Challenge including a re-examination of the process of combining information from different galaxies, which reduces the dependence on realistic galaxy modelling. The image simulations will become increasingly sophisticated in future GREAT Challenges, meanwhile the GREAT08 simulations remain as a benchmark for additional developments in shear measurement algorithms.
Citation
Bridle, S., Balan, S., Bethge, M., Gentile, M., Harmeling, S., Heymans, C., …Wittman, D. (2010). Results of the GREAT08 Challenge : an image analysis competition for cosmological lensing. Monthly Notices of the Royal Astronomical Society, 405(3), 2044-2061. https://doi.org/10.1111/j.1365-2966.2010.16598.x
Journal Article Type | Article |
---|---|
Publication Date | Jul 1, 2010 |
Deposit Date | Mar 21, 2013 |
Publicly Available Date | Feb 19, 2015 |
Journal | Monthly Notices of the Royal Astronomical Society |
Print ISSN | 0035-8711 |
Electronic ISSN | 1365-2966 |
Publisher | Royal Astronomical Society |
Peer Reviewed | Peer Reviewed |
Volume | 405 |
Issue | 3 |
Pages | 2044-2061 |
DOI | https://doi.org/10.1111/j.1365-2966.2010.16598.x |
Keywords | Gravitational lensing: weak, Methods: data analysis, Methods: statistical, Techniques: image processing, Cosmology: observations, Large-scale structure of Universe. |
Public URL | https://durham-repository.worktribe.com/output/1463987 |
Files
Published Journal Article
(1.4 Mb)
PDF
Copyright Statement
This article has been accepted for publication in Monthly Notices of the Royal Astronomical Society ©: 2010 The Authors. Published by Oxford University Press on behalf of the Royal Astronomical Society. All rights reserved.
You might also like
RXJ0437+00: constraining dark matter with exotic gravitational lenses
(2023)
Journal Article
Abell 1201: detection of an ultramassive black hole in a strong gravitational lens
(2023)
Journal Article
PyAutoGalaxy: Open-Source Multiwavelength Galaxy Structure & Morphology
(2023)
Journal Article
Downloadable Citations
About Durham Research Online (DRO)
Administrator e-mail: dro.admin@durham.ac.uk
This application uses the following open-source libraries:
SheetJS Community Edition
Apache License Version 2.0 (http://www.apache.org/licenses/)
PDF.js
Apache License Version 2.0 (http://www.apache.org/licenses/)
Font Awesome
SIL OFL 1.1 (http://scripts.sil.org/OFL)
MIT License (http://opensource.org/licenses/mit-license.html)
CC BY 3.0 ( http://creativecommons.org/licenses/by/3.0/)
Powered by Worktribe © 2024
Advanced Search