{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/rj-plots-an-improved-method-to-classify","title":"RJ-plots: An improved method to classify structures objectively","arxiv_id":"2208.07509","date":"2022-08-16","proceeding":null,"authors":["Seamus D. Clarke","Sarah E. Jaffa","Anthony P. Whitworth"],"abstract":"The interstellar medium is highly structured, presenting a range of morphologies across spatial scales. The large data sets resulting from observational surveys and state-of-the-art simulations studying these hierarchical structures means that identification and classification must be done in an automated fashion to be efficient. Here we present RJ-plots, an improved version of the automated morphological classification technique J-plots developed by Jaffa et al. (2018). This method allows clear distinctions between quasi-circular/elongated structures and centrally over/under-dense structures. We use the recent morphological SEDIGISM catalogue of Neralwar et al. (2022) to show the improvement in classification resulting from RJ-plots, especially for ring-like and concentrated cloud types. We also find a strong correlation between the central concentration of a structure and its star formation efficiency and dense gas fraction, as well as a lack of correlation with elongation. Furthermore, we use the accreting filament simulations of Clarke et al. (2020) to highlight a multi-scale application of RJ-plots, finding that while spherical structures become more common at smaller scales they are never the dominant structure down to $r\\sim0.03$ pc.","url_abs":"https://arxiv.org/abs/2208.07509v1","url_pdf":"https://arxiv.org/pdf/2208.07509v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"rj-plots-an-improved-method-to-classify","repo_url":"https://github.com/seamusclarke/rjplots","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}