[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121645-en":3,"doc-seo-121645-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},121645,1099513958762,"Logic","https://ap-avatar.wpscdn.com/avatar/1000023916a998db790?x-image-process=image/resize,m_fixed,w_180,h_180&k=1784791008015729253",8,"Research & Report","Galaxy pairs in The Three Hundred simulations II - studying bound ones and identifying them via machine learning","Using the Three Hundred dataset, which includes 324 hydrodynamical resimulations of cluster-sized haloes and surrounding 15 h−1 Mpc regions, the work investigates galaxy pairs in high-density environments. Galaxies are projected from 3D to 2D to apply observational pair-finding techniques, then classified as gravitationally bound (“true”) or unbound (“false”). Purity strongly depends on selection thresholds, while completeness drops in restrictive cases. A machine-learning model improves purity and completeness using galaxy properties such as size, mass, spin, gas content, and stellar shape.","arXiv :2304 .08898v1 [ astro-ph .GA] 18 Apr 2023  \nGalaxy pairs in The Three Hundred simulations II: studying bound ones and identifying them via machine learning  \nAna Contreras-Santos, 1★ Alexander Knebe, 1,2,3 Weiguang Cui, 1,4† Roan Haggar,5,6 Frazer Pearce,5 Meghan Gray,5 Marco De Petris,7,8 and Gustavo Yepes 1,2  \n1 Departamento de Física Teórica, Módulo 15, Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain  \n2 Centro de InvestigaciónAvanzada en Física Fundamental (CIAFF), Facultad de Ciencias, Universidad Autónoma de Madrid, 28049 Madrid, Spain  \n3 International Centre for Radio Astronomy Research, University of Western Australia, 35 Stirling Highway, Crawley, Western Australia 6009, Australia  \n4 Institute for Astronomy, University of Edinburgh, Royal Observatory, Edinburgh EH9 3HJ, United Kingdom  \n5 School of Physics & Astronomy, University of Nottingham, Nottingham NG7 2RD, United Kingdom  \n6 Waterloo Centre for Astrophysics, University of Waterloo, Waterloo, Ontario N2L 3G1, Canada  \n7 Dipartimento di Fisica, Sapienza Università di Roma, Piazzale Aldo Moro 5, 00185 Roma, Italy  \n8I.N.A.F. - Osservatorio Astronomico di Roma, Via Frascati 33, 00040 Monteporzio Catone, Roma, Italy  \nLast updated 2015 May 22; in original form 2013 September 5  \nABSTRACT  \nUsing the data set of The Three Hundred project, i.e. 324 hydrodynamical resimulations of cluster-sized haloes and the regions of radius 15 ℎ−1Mpc around them, we study galaxy pairs in high-density environments. By projecting the galaxies’ 3D coordinates onto a 2D plane, we apply observational techniques to find galaxy pairs. Based on a previous theoretical study on galaxy groups in the same simulations, we are able to classify the observed pairs into “true” or“false”, depending on whether they are gravitationally bound or not. We find that the fraction of true pairs (purity) crucially depends on the specific thresholds used to find the pairs, ranging from around 30 to more than 80 per cent in the most restrictive case. Nevertheless, in these very restrictive cases, we see that the completeness of the sample is low, failing to find asignificant number of true pairs. Therefore, we train a machine learning algorithm to help us to identify these true pairs based on the properties of the galaxies that constitute them. With the aid of the machine learning model trained with a set of properties of all the objects, we show that purity and completeness can be boosted significantly using the default observational thresholds. Furthermore, this machine learning model also reveals the properties that are most important when distinguishing true pairs, mainly the size and mass of the galaxies, their spin parameter, gas content and shape of their stellar components.  \nKey words: methods: numerical – galaxies: clusters: general – galaxies: general – galaxies: interactions  \n1 INTRODUCTION  \nEarly studies showed that most observed galaxies can be classified into different types according to their morphology (mainly ellipticals or spirals, see Hubble’s ‘tuning fork’, Hubble 1936; Sandage 1961). However, not all of them fit this sequence perfectly. An early attempt to study these galaxies was the Atlas of Peculiar Galaxies (Arp 1966), which consists of images of more than 300 galaxies that show different peculiarities such as perturbations and deformations. Interactions and mergers between galaxies, which can affect them in different ways, have been shown to be the main force causing these peculiarities. Numerical simulations performed in the follow-  \n★ Contact e-mail: [ana.contreras@uam.es](ana.contreras@uam.es)[ ](ana.contreras@uam.es)† Atracción de Talento fellow  \ning years have helped to clarify this situation (Toomre & Toomre 1972; Barnes & Hernquist 1992) and to acknowledge the crucial role that these interactions play in galaxy formation and evolution (see e.g. Conselice 2014, for a review). Today, the Λ cold dark matter (ΛCDM) growth paradigm for the Universe descri","cbCaibSbgVO50jBE","https://ap.wps.com/l/cbCaibSbgVO50jBE","pdf",807921,1,20,"English","en",105,"# Abstract\n# Introduction\n## Galaxy morphology and peculiar galaxies\n## Observational identification of merger candidates\n## Effects of close companions on galaxy properties","[{\"question\":\"How are galaxy pairs identified in this study?\",\"answer\":\"Galaxies are projected from 3D coordinates onto a 2D plane and paired using observational selection criteria such as projected separation, velocity separation, and mass ratio thresholds.\"},{\"question\":\"What determines whether a pair is classified as “true” or “false”?\",\"answer\":\"Pairs are labeled “true” if the galaxies are gravitationally bound, and “false” if they are not, allowing comparison with observational pair candidates.\"},{\"question\":\"Why is machine learning used, and what does it improve?\",\"answer\":\"Machine learning addresses low sample completeness in very restrictive observational thresholds by learning to recognize bound pairs from galaxy properties, substantially boosting both purity and completeness.\"}]","Galaxy pairs in The Three Hundred simulations II - studying bound ones and identifying them via machine learning | PDF",1785805902,50,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"galaxy-pairs-in-the-three-hundred-simulations-ii-studying-bound-ones-and-identifying-them-via-machine-learning","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/galaxy-pairs-in-the-three-hundred-simulations-ii-studying-bound-ones-and-identifying-them-via-machine-learning/121645/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-04",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"How are galaxy pairs identified in this study?","Question",{"text":75,"@type":76},"Galaxies are projected from 3D coordinates onto a 2D plane and paired using observational selection criteria such as projected separation, velocity separation, and mass ratio thresholds.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"What determines whether a pair is classified as “true” or “false”?",{"text":80,"@type":76},"Pairs are labeled “true” if the galaxies are gravitationally bound, and “false” if they are not, allowing comparison with observational pair candidates.",{"name":82,"@type":73,"acceptedAnswer":83},"Why is machine learning used, and what does it improve?",{"text":84,"@type":76},"Machine learning addresses low sample completeness in very restrictive observational thresholds by learning to recognize bound pairs from galaxy properties, substantially boosting both purity and completeness.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":29,"slug":113},6,"Technology","technology",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":21,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":127,"show_sort_weight":21,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":46,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":46,"category_name":135,"show_sort_weight":106,"slug":136},19,"General","general"]