Please use this identifier to cite or link to this item: https://hdl.handle.net/11147/5537
Title: Extended void merging tree algorithm for self-similar models
Authors: Russell, Esra
Keywords: Large-scale structure of universe
Cosmology
Algorithms
Einstein-de Sitter Universe
Issue Date: Mar-2014
Publisher: Oxford University Press
Source: Russell, E. (2014). Extended void merging tree algorithm for self-similar models. Monthly Notices of the Royal Astronomical Society, 438(2), 1630-1653. doi:10.1093/mnras/stt2309
Abstract: In hierarchical evolution, voids exhibit two different behaviours related with their surroundings and environments, they can merge or collapse. These two different types of void processes can be described by the two-barrier excursion set formalism based on Brownian random walks. In this study, the analytical approximate description of the growing void merging algorithm is extended by taking into account the contributions of voids that are embedded into overdense region(s) which are destined to vanish due to gravitational collapse. Following this, to construct a realistic void merging model that consists of both collapse and merging processes, the twobarrier excursion set formalism of the void population is used. Assuming spherical voids in the Einstein-de Sitter Universe, the void merging algorithm which allows us to consider the two main processes of void hierarchy in one formalism is constructed. In addition to this, the merger rates, void survival probabilities, void size distributions in terms of the collapse barrier and finally, the void merging tree algorithm in the self-similar models are defined and derived.
URI: https://doi.org/10.1093/mnras/stt2309
http://hdl.handle.net/11147/5537
ISSN: 1365-2966
0035-8711
Appears in Collections:Mathematics / Matematik
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Sürdürülebilir Yeşil Kampüs Koleksiyonu / Sustainable Green Campus Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Files in This Item:
File Description SizeFormat 
5537.pdfMakale2.4 MBAdobe PDFThumbnail
View/Open
Show full item record



CORE Recommender

SCOPUSTM   
Citations

3
checked on Feb 16, 2024

WEB OF SCIENCETM
Citations

3
checked on Feb 26, 2024

Page view(s)

60
checked on Feb 26, 2024

Download(s)

124
checked on Feb 26, 2024

Google ScholarTM

Check




Altmetric


Items in GCRIS Repository are protected by copyright, with all rights reserved, unless otherwise indicated.