图 书 馆
一切理论Theories of Everything |
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| 课程网址: | http://videolectures.net/nipsworkshops2011_hogg_theories/ |
| 主讲教师: | David W. Hogg |
| 开课单位: | 纽约大学 |
| 开课时间: | 2012-01-23 |
| 课程语种: | 英语 |
| 中文简介: |  当今，宇宙学可用于静态目录（例如星系）和基本物理量的点估计（例如，大多数宇宙学所基于的两个点函数）。下一代宇宙学实验正在寻找越来越大的数据集中越来越细微的影响。他们将不会提供他们所能提供的所有宇宙学信息，除非我们能够开发出概率方法，以尽可能最佳地将原始数据中的所有信息传输到感兴趣的数量（例如，原始密度波动的频谱或质量暗物质粒子）。我将展示一些简单的步骤，以创建整个系统的概率生成模型，其中宇宙学参数在顶部，原始图像像素在底部。部分工作是与Fergus（NYU），Lang（Princeton），Marshall（Oxford）和Murray（Edinburgh）合作完成的。 |
| 课程简介: | Cosmology, at the present day, works with static catalogs (of, say, galaxies) and point estimates of fundamental physical quantities (of, for example, two-point functions, on which most cosmological science is based). Next-generation cosmological experiments are looking for ever more subtle effects in larger and larger data sets; they will not provide all the cosmological information of which they are capable unless we can develop probabilistic approaches that transmit as best as possible all the information in the raw data to the quantities of interest (for example, the spectrum of primordial density fluctuations or the mass of the dark-matter particle). I will show some baby steps towards creating a probabilistic generative model of the full system, with cosmological parameters at the top and raw image pixels at the bottom. Parts of this work have been performed in collaboration with Fergus (NYU), Lang (Princeton), Marshall (Oxford), and Murray (Edinburgh). |
| 关 键 词: | 一切理论; 宇宙学 |
| 课程来源: | 视频讲座网 |
| 数据采集: | 2020-09-28：zkj |
| 最后编审: | 2020-10-22：zyk |
| 阅读次数: | 43 |