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一种全天文成像的综合模型

A Comprehensive Model of All Astronomical Imaging Ever Taken
课程网址: http://videolectures.net/cidu2011_hogg_astronomical_imaging/  
主讲教师: David W. Hogg
开课单位: 纽约大学
开课时间: 2012-06-27
课程语种: 英语
中文简介:
在天体物理学中,我们开始使用极大的数据集。然而,与大多数其他数据科学领域不同,我们对生成这些数据的物理过程有合理的处理:我们的工作模型可以很好地描述星系,恒星和电荷耦合器件的定量特性。特别是,我们对噪声源有很好的描述。由于这些原因,在天体物理学中进行的最灵敏和准确的测量是通过建立高度知情的概率数据模型来完成的。我展示了一些通过建模数据进行科学发现的例子,展望未来,当数据集达到peta规模并且模型有数十亿个免费参数时。
课程简介: In astrophysics we are beginning to work with extremely large data sets. However, unlike in most other data-science domains, we have a reasonable handle on the physical processes that generate those data: We have working models that do a fairly good job of describing the quantitative properties of galaxies, stars, and charge-coupled devices. In particular, we have pretty good descriptions of our sources of noise. For these reasons, the most sensitive and accurate measurements being made in astrophysics are made by building highly informed, probabilistic models of the data. I show some examples of scientific discoveries made by modeling data and look to the future, when data sets reach peta-scale and the models have billions of free parameters.
关 键 词: 数据集; 天体物理学; 数据科学领域; 电荷耦合器件; 建模数据
课程来源: 视频讲座网
最后编审: 2019-10-17:cwx
阅读次数: 27