assessingtheperformanceofmoleculargasclumpidentificationalgorithms

doi:10.1088/1674–4527/20/3/31

	assessingtheperformanceofmoleculargasclumpidentificationalgorithms
	Li Chong 1; Wang Hongchi 1; Wu Yuanwei 2; Ma Yuehui 1; Lin Lianghao 1
	2020
发表期刊	researchinastronomyandastrophysics
ISSN	1674-4527
卷号	20 期号:3
摘要	The detection of clumps (cores) in molecular clouds is an important issue in sub-millimetre astronomy. However, the completeness of the identification and the accuracy of the returned parameters of the automated clump identification algorithms are still not clear. In this work, we test the performance and bias of the GaussClumps, ClumpFind, FellWalker, Reinhold, and Dendrograms algorithms in identifying simulated clumps. By designing the simulated clumps with various sizes, peak brightness, and crowdedness, we investigate the characteristics of the algorithms and their performance. In the aspect of detection completeness, FellWalker, Dendrograms, and GaussClumps are the first, second, and third best algorithms, respectively. The numbers of correct identifications of the six algorithms gradually increase as the size and signal-to-noise ratio (SNRs) of the simulated clumps increase and they decrease as the crowdedness increases. In the aspect of the accuracy of retrieved parameters, FellWalker and Dendrograms exhibit better performance than the other algorithms. The average deviations in clump parameters for all algorithms gradually increase as the size and SNR of clumps increase. Most of the algorithms except FellWalker exhibit significant deviation in extracting the total flux of clumps. Taken together, FellWalker, GaussClumps, and Dendrograms exhibit the best performance in detection completeness and extracting parameters. The deviation in virial parameter for the six algorithms is relatively low. When applying the six algorithms to the clump identification for the Rosette molecular cloud, ClumpFind1994, ClumpFind2006, GaussClumps, FellWalker, and Reinhold exhibit performance that is consistent with the results from the simulated test.
关键词	methods: data analysis methods: numerical ISM: structure
DOI	10.1088/1674–4527/20/3/31
语种	英语
引用统计
文献类型	期刊论文
条目标识符	http://210.72.145.45/handle/361003/9171
专题	高精度时间传递与精密测定轨研究室
作者单位	1.中国科学院紫金山天文台 2.中国科学院国家授时中心
推荐引用方式 GB/T 7714	Li Chong,Wang Hongchi,Wu Yuanwei,et al. assessingtheperformanceofmoleculargasclumpidentificationalgorithms[J]. researchinastronomyandastrophysics,2020,20(3).
APA	Li Chong,Wang Hongchi,Wu Yuanwei,Ma Yuehui,&Lin Lianghao.(2020).assessingtheperformanceofmoleculargasclumpidentificationalgorithms.researchinastronomyandastrophysics,20(3).
MLA	Li Chong,et al."assessingtheperformanceofmoleculargasclumpidentificationalgorithms".researchinastronomyandastrophysics 20.3(2020).