The road toward a full, high resolution Molecular Cloud catalog of the Galaxy

TL;DR

This paper introduces SCIMES, a graph theory-based algorithm for identifying and cataloging molecular clouds in the Galaxy, enabling systematic and high-resolution mapping of molecular features.

Contribution

The paper presents a novel segmentation algorithm, SCIMES, that improves molecular cloud identification by leveraging graph theory, applied to high-resolution survey data.

Findings

Robust decomposition of over 12,000 molecular objects in the Galactic Plane.

SCIMES overcomes survey design limitations in cloud segmentation.

Facilitates systematic cataloging of molecular clouds in the Galaxy.

Abstract

The statistical description of Giant Molecular Cloud (GMC) properties relies heavily on the performance of automatic identification algorithms, which are often seriously affected by the survey design. The algorithm we designed, SCIMES (Spectral Clustering for Interstellar Molecular Emission Segmentation), is able to overcome some of these limitations by considering the cloud segmentation problem in the broad framework of the graph theory. The application of the code on the CO(3-2) High Resolution Survey (COHRS) data allowed for a robust decomposition of more than 12,000 objects in the Galactic Plane. Together with the wealth of Galactic Plane surveys of the recent years, this approach will help to open the door to a future, systematic cataloging of all discrete molecular features of our own Galaxy.