The Spectral Correlation Function: A New Tool for Analyzing Spectral Line Maps
The Spectral Correlation Function: A New Tool for Analyzing Spectral Line Maps
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谱相关函数：分析谱线图的新工具
DOI：
10.1086/307863
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发表时间：
1999
期刊：
影响因子：
--
通讯作者：
Jonathan P. Williams
中科院分区：
文献类型：
--
作者：
E. Rosolowsky;A. Goodman;D. Wilner;Jonathan P. Williams
本文介绍的“谱相关函数”分析是分析谱线数据立方体的一种新工具。我们的初步测试，进行了一套观察和模拟数据立方体，表明光谱相关函数（SCF）可能是一个更有区别的统计比其他统计方法通常应用。SCF是数据立方体中相邻光谱之间相似性的度量。当SCF用于比较由星际介质（ISM）的谱线观测组成的数据立方体与来自分子云的MHD模拟的数据立方体时，它可以发现其他分析所没有发现的差异。这里提出的初步结果表明，在数值模拟中包括自引力是至关重要的再生相关行为的光谱在恒星形成的分子云。
The "spectral correlation function" analysis we introduce in this paper is a new tool for analyzing spectral line data cubes. Our initial tests, carried out on a suite of observed and simulated data cubes, indicate that the spectral correlation function (SCF) is likely to be a more discriminating statistic than other statistical methods normally applied. The SCF is a measure of similarity between neighboring spectra in the data cube. When the SCF is used to compare a data cube consisting of spectral line observations of the interstellar medium (ISM) with a data cube derived from MHD simulations of molecular clouds, it can find differences that are not found by other analyses. The initial results presented here suggest that the inclusion of self-gravity in numerical simulations is critical for reproducing the correlation behavior of spectra in star-forming molecular clouds.