Gaussian decomposition of HI surveys. V. Search for very cold clouds
Urmas Haud

TL;DR
This paper introduces a new algorithm for identifying very cold HI clouds in all-sky surveys, revealing their structure and potential relation to supernova shells, advancing understanding of neutral gas in the solar neighborhood.
Contribution
The paper presents a modified hierarchical clustering algorithm tailored for large HI survey data to effectively identify cold cloud structures.
Findings
Successfully detected the coldest known HI clouds.
Identified a long narrow ribbon of cold clouds.
Linked these clouds to a planar gas ring and supernova shells.
Abstract
In the previous papers of this series, we have decomposed into Gaussian components all the HI 21-cm line profiles of the Leiden-Argentina-Bonn (LAB) database, and studied statistical distributions of the obtained Gaussians. Now we are interested in separation from the general database of the components the "clouds" of closely spaced similar Gaussians. In this paper we describe the new cloud-finding algorithm. To separate the clouds of similar Gaussians, we start with the single-link hierarchical clustering procedure in five-dimensional (longitude, latitude, velocity, Gaussian width and height) space, but make some modifications to accommodate it to the large number of components. We also use the requirement that each cloud may be represented at any observed sky position by only one Gaussian and take into account the similarity of global properties of the merging clouds. As a test, we…
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Taxonomy
TopicsAstrophysics and Star Formation Studies · Gamma-ray bursts and supernovae · Stellar, planetary, and galactic studies
