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杰出的第3点:未来的弱引力透镜数据挑战

GREAT3: The next weak lensing data challenge
课程网址: http://videolectures.net/nipsworkshops2011_rowe_lensing/  
主讲教师: Barnaby Rowe
开课单位: 伦敦大学学院
开课时间: 2012-01-23
课程语种: 英语
中文简介:
现代宇宙学中最深奥的奥秘之一是宇宙的加速膨胀(这一发现导致了2011年的诺贝尔物理学奖)。弱引力透镜是一种观测方法,有可能揭示这个谜,它依靠对数百万个星系形状的精确测量来揭示星系和我们之间物质造成的微小扭曲。然而,由于大气、望远镜光学、探测器和像素噪声的大变形,精确推断真实的星系形状是复杂的。随着数据量的增加,对测量精度的要求越来越严格,弱透镜化现在必须迎接前所未有的图像分析挑战。这一需求推动了形状测量算法的不断改进,并导致了公共数据分析挑战的产生,其中step1、step2、great08和great10挑战是最近的例子。一些方法已经被天文学家们成功地磨练和测试过,但是在机器学习社区也发现了获奖者。在这张海报中,我们总结了从以前的挑战中学到的关于形状测量系统学的知识,并强调了近期内该领域的关键问题,这些问题将在下一个弱透镜数据挑战(目前正在开发中)中进行测试。
课程简介: One of the most profound mysteries in modern cosmology is the accelerated expansion of the universe (the discovery of which led to the 2011 physics Nobel Prize). Weak gravitational lensing, an observational method that has the potential to shed the most light on this mystery, relies on accurate measurement of the shapes of millions of galaxies to uncover tiny distortions caused by matter between the galaxies and us. However, accurately inferring the true galaxy shapes is complicated due to large distortions from the atmosphere, telescope optics, detector and pixel noise. As data arrives in greater quantities, requirements on measurement accuracy become more stringent, and weak lensing must now meet unprecedented image analysis challenges. This need has driven ongoing improvements to shape measurement algorithms, and led to the creation of public data analysis challenges, of which the STEP1, STEP2, GREAT08 and GREAT10 challenges are recent examples. Some approaches have been successfully honed and tested by astronomers, but winning entrants have also been found from the machine learning community. In this poster we summarize what has been learned about shape measurement systematics from previous challenges, and highlight critical issues for the field in the near future, which will be tested in the next weak lensing data challenge (currently under development).
关 键 词: 现代宇宙学; 宇宙加速膨胀; 弱引力透镜效应
课程来源: 视频讲座网
最后编审: 2020-10-22:chenxin
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