期刊
ASTROPHYSICAL JOURNAL
卷 695, 期 1, 页码 747-754出版社
IOP PUBLISHING LTD
DOI: 10.1088/0004-637X/695/1/747
关键词
galaxies: statistics; methods: statistical
资金
- Gordon and Betty Moore Foundation [GBMF 554]
We present a rigorous mathematical solution to photometric redshift estimation and the more general inversion problem. The challenge we address is to meaningfully constrain unknown properties of astronomical sources based on given observables, usually multicolor photometry, with the help of a training set that provides an empirical relation between the measurements and the desired quantities. We establish a formalism that blurs the boundary between the traditional empirical and template-fitting algorithms, as both are just special cases that are discussed in detail to put them in context. The new approach enables the development of more sophisticated methods that go beyond the classic techniques to combine their advantages. We look at the directions for further improvement in the methodology, and examine the technical aspects of practical implementations. We show how training sets are to be constructed and used consistently for reliable estimation.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据