Cardiff University | Prifysgol Caerdydd ORCA
Online Research @ Cardiff 
WelshClear Cookie - decide language by browser settings

Graph-based interpretation of the molecular interstellar medium segmentation

Colombo, D., Rosolowsky, E., Ginsburg, A., Duarte Cabral, Ana ORCID: https://orcid.org/0000-0002-5259-4774 and Hughes, A. 2015. Graph-based interpretation of the molecular interstellar medium segmentation. Monthly Notices of the Royal Astronomical Society 454 (2) , pp. 2067-2091. 10.1093/mnras/stv2063

[thumbnail of stv2063.pdf]
Preview
PDF - Published Version
Download (14MB) | Preview

Abstract

We present a generalization of the Giant Molecular Cloud (GMC) identification problem based on cluster analysis. The method we designed, SCIMES (Spectral Clustering for Interstellar Molecular Emission Segmentation) considers the dendrogram of emission in the broader framework of graph theory and utilizes spectral clustering to find discrete regions with similar emission properties. For Galactic molecular cloud structures, we show that the characteristic volume and/or integrated CO luminosity are useful criteria to define the clustering, yielding emission structures that closely reproduce 'by-eye' identification results. SCIMES performs best on well-resolved, high-resolution data, making it complementary to other available algorithms. Using 12CO(1-0) data for the Orion-Monoceros complex, we demonstrate that SCIMES provides robust results against changes of the dendrogram-construction parameters, noise realizations and degraded resolution. By comparing SCIMES with other cloud decomposition approaches, we show that our method is able to identify all canonical clouds of the Orion-Monoceros region, avoiding the over-division within high resolution survey data that represents a common limitation of several decomposition algorithms. The Orion-Monoceros objects exhibit hierarchies and size-line width relationships typical to the turbulent gas in molecular clouds, although 'the Scissors' region deviates from this common description. SCIMES represents a significant step forward in moving away from pixel-based cloud segmentation towards a more physical-oriented approach, where virtually all properties of the ISM can be used for the segmentation of discrete objects.

Item Type: Article
Date Type: Publication
Status: Published
Schools: Physics and Astronomy
Publisher: Oxford University Press
ISSN: 0035-8711
Date of First Compliant Deposit: 19 September 2019
Date of Acceptance: 3 September 2015
Last Modified: 05 May 2023 00:43
URI: https://orca.cardiff.ac.uk/id/eprint/102821

Citation Data

Cited 56 times in Scopus. View in Scopus. Powered By Scopus® Data

Actions (repository staff only)

Edit Item Edit Item

Downloads

Downloads per month over past year

View more statistics