arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1503.00730astro-ph.COastro-ph.IMstat.AP
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基于决策理论的宇宙网络分类

Cosmic web-type classification using decision theory

Florent Leclercq, Jens Jasche, Benjamin Wandelt

摘要:

我们提出了一个决策标准分割成不同的结构类型(空隙,片,丝,和集群)的基础上,各自的概率和数据约束的强度的宇宙网络。我们的方法的灵感来自于分析的机会游戏,赌徒只玩,如果一个积极的预期净收益可以实现一定程度的特权信息的基础上。其结果是在面对不确定性时分类问题的一般解决方案,包括不提交候选对象的类的选项。作为一个例子,我们产生高分辨率的地图,在附近的宇宙中的网络型成分探测斯隆数字巡天主要星系样本。其他可能的应用包括在根据天文测量数据编制的目录中选择和标记天体。

英文摘要:

We propose a decision criterion for segmenting the cosmic web into different structure types (voids, sheets, filaments, and clusters) on the basis of their respective probabilities and the strength of data constraints. Our approach is inspired by an analysis of games of chance where the gambler only plays if a positive expected net gain can be achieved based on some degree of privileged information. The result is a general solution for classification problems in the face of uncertainty, including the option of not committing to a class for a candidate object. As an illustration, we produce high-resolution maps of web-type constituents in the nearby Universe as probed by the Sloan Digital Sky Survey main galaxy sample. Other possible applications include the selection and labelling of objects in catalogues derived from astronomical survey data.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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