📝 SummarXiv

Abstract

We present GDCluster, a fully automated algorithm for decomposing spectral-line datacube of interstellar gas into coherent structures. Assuming a multi-Gaussian nature of observed spectra, GDCluster employs and augments the derivative spectroscopy technique for precise parameter estimation, incorporates spatial-continuity constraints during spectral fitting, and extends these constraints to spatial clustering. This approach effectively resolves velocity blending structures in PPV space-particularly critical for ubiquitous HI spectra where emissions from multiple phases are severely blended. Applied to the all-sky HI4PI data, a 10 degree times 10 degree CRAFTS survey region, and a 45 degree times 10 degree MWISP survey region, GDCluster extracts 45,299, 2247, and 47,119 structures in HI and CO (1-0), respectively. Comparative analyses demonstrate GDCluster's superiority over DBSCAN in separating overlapping spectra with complex velocity components.