The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria
We summarize the experience of studying 2D features in the galaxy distribution of galaxy cluster fields. For the detailed study of the inner structure of galaxy clusters, algorithms were developed for detecting various types of regular substructures inside such objects automatically. Substructures i...
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2025-07-01
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| author | Elena Panko |
| author_facet | Elena Panko |
| author_sort | Elena Panko |
| collection | DOAJ |
| description | We summarize the experience of studying 2D features in the galaxy distribution of galaxy cluster fields. For the detailed study of the inner structure of galaxy clusters, algorithms were developed for detecting various types of regular substructures inside such objects automatically. Substructures in galaxy clusters arise from interactions as well as the evolution of the cosmic web, but cannot be described according to the schemes of morphological classification, both classical and modern, because some regular substructures are not present. Our algorithms are based on numerical criteria that permit the determination of classical morphological types, connected with parameters such as the degree of concentration to the cluster center and/or to a straight line, on a statistically significant level. Other types of substructures can also be detected with corresponding algorithms. As a result, we can analyze intracluster features, such as crosses, semi-crosses, complex crosses, and compact dense chains. All algorithms are realized in the “Cluster Cartography” tool and can be used with data taken from different catalogs. The algorithms and their realization in program code must simplify, standardize, and speed up the analysis of 2D distributions of galaxies in clusters. It is possible in future to adapt the algorithms for the 3D case. The results of statistically valid morphological classification are useful for studies of the evolution of galaxy clusters. |
| format | Article |
| id | doaj-art-ba5fa32aed4546f49ddc915eca0f710c |
| institution | Kabale University |
| issn | 2218-1997 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | MDPI AG |
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| series | Universe |
| spelling | doaj-art-ba5fa32aed4546f49ddc915eca0f710c2025-08-20T03:32:16ZengMDPI AGUniverse2218-19972025-07-0111723810.3390/universe11070238The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical CriteriaElena Panko0Physics and Astronomy Department, Odessa I.I. Mechnikov National University, Vsevoloda Zmiienka St., 2, 65082 Odessa, UkraineWe summarize the experience of studying 2D features in the galaxy distribution of galaxy cluster fields. For the detailed study of the inner structure of galaxy clusters, algorithms were developed for detecting various types of regular substructures inside such objects automatically. Substructures in galaxy clusters arise from interactions as well as the evolution of the cosmic web, but cannot be described according to the schemes of morphological classification, both classical and modern, because some regular substructures are not present. Our algorithms are based on numerical criteria that permit the determination of classical morphological types, connected with parameters such as the degree of concentration to the cluster center and/or to a straight line, on a statistically significant level. Other types of substructures can also be detected with corresponding algorithms. As a result, we can analyze intracluster features, such as crosses, semi-crosses, complex crosses, and compact dense chains. All algorithms are realized in the “Cluster Cartography” tool and can be used with data taken from different catalogs. The algorithms and their realization in program code must simplify, standardize, and speed up the analysis of 2D distributions of galaxies in clusters. It is possible in future to adapt the algorithms for the 3D case. The results of statistically valid morphological classification are useful for studies of the evolution of galaxy clusters.https://www.mdpi.com/2218-1997/11/7/238galaxy clustersmorphologymethodsdata analysisstatistical |
| spellingShingle | Elena Panko The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria Universe galaxy clusters morphology methods data analysis statistical |
| title | The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria |
| title_full | The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria |
| title_fullStr | The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria |
| title_full_unstemmed | The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria |
| title_short | The Morphological Classification of Galaxy Clusters: Algorithms for Applying the Numerical Criteria |
| title_sort | morphological classification of galaxy clusters algorithms for applying the numerical criteria |
| topic | galaxy clusters morphology methods data analysis statistical |
| url | https://www.mdpi.com/2218-1997/11/7/238 |
| work_keys_str_mv | AT elenapanko themorphologicalclassificationofgalaxyclustersalgorithmsforapplyingthenumericalcriteria AT elenapanko morphologicalclassificationofgalaxyclustersalgorithmsforapplyingthenumericalcriteria |