摘要翻译：
引力透镜精度测试2008(GREAT08)挑战集中在一个对未来宇宙学观测至关重要的问题上。遥远星系的形状可以用来确定暗能量的性质和引力的性质，因为来自这些星系的光被来自中间暗物质的引力弯曲。观测到的星系图像虽然只是轻微的扭曲，但它们的形状必须与像素化、卷积和噪声的影响精确地分离开来。世界范围内的引力透镜界已经在通过剪切测试计划(STEP)来测量这些畸变的技术上取得了重大进展。通过STEP，我们在自己的社区中进行了挑战，并认识到这个特殊的图像分析问题非常适合统计推断、逆问题和计算学习方面的专家。因此，为了继续近年来取得的进展，我们正在寻求这些社区注入新的思想。本文件为潜在的参与者详细介绍了GREAT08挑战。有关最新信息，请访问http://www.great08challenge.info。
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英文标题：
《Handbook for the GREAT08 Challenge: An image analysis competition for
  cosmological lensing》
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作者：
Sarah Bridle, John Shawe-Taylor, Adam Amara, Douglas Applegate,
  Sreekumar T. Balan, Joel Berge, Gary Bernstein, Hakon Dahle, Thomas Erben,
  Mandeep Gill, Alan Heavens, Catherine Heymans, F. William High, Henk
  Hoekstra, Mike Jarvis, Donnacha Kirk, Thomas Kitching, Jean-Paul Kneib,
  Konrad Kuijken, David Lagatutta, Rachel Mandelbaum, Richard Massey, Yannick
  Mellier, Baback Moghaddam, Yassir Moudden, Reiko Nakajima, Stephane
  Paulin-Henriksson, Sandrine Pires, Anais Rassat, Alexandre Refregier, Jason
  Rhodes, Tim Schrabback, Elisabetta Semboloni, Marina Shmakova, Ludovic van
  Waerbeke, Dugan Witherick, Lisa Voigt, David Wittman
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最新提交年份：
2009
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分类信息：

一级分类：Statistics        统计学
二级分类：Statistics Theory        统计理论
分类描述：stat.TH is an alias for math.ST. Asymptotics, Bayesian Inference, Decision Theory, Estimation, Foundations, Inference, Testing.
Stat.Th是Math.St的别名。渐近，贝叶斯推论，决策理论，估计，基础，推论，检验。
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一级分类：Statistics        统计学
二级分类：Applications        应用程序
分类描述：Biology, Education, Epidemiology, Engineering, Environmental Sciences, Medical, Physical Sciences, Quality Control, Social Sciences
生物学，教育学，流行病学，工程学，环境科学，医学，物理科学，质量控制，社会科学
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英文摘要：
  The GRavitational lEnsing Accuracy Testing 2008 (GREAT08) Challenge focuses on a problem that is of crucial importance for future observations in cosmology. The shapes of distant galaxies can be used to determine the properties of dark energy and the nature of gravity, because light from those galaxies is bent by gravity from the intervening dark matter. The observed galaxy images appear distorted, although only slightly, and their shapes must be precisely disentangled from the effects of pixelisation, convolution and noise. The worldwide gravitational lensing community has made significant progress in techniques to measure these distortions via the Shear TEsting Program (STEP). Via STEP, we have run challenges within our own community, and come to recognise that this particular image analysis problem is ideally matched to experts in statistical inference, inverse problems and computational learning. Thus, in order to continue the progress seen in recent years, we are seeking an infusion of new ideas from these communities. This document details the GREAT08 Challenge for potential participants. Please visit http://www.great08challenge.info for the latest information.
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PDF链接：
https://arxiv.org/pdf/802.1214