A comparison of cosmological filaments catalogues

In this work, we compare three catalogues of cosmological filaments identified in the Sloan Digital Sky Survey by means of different algorithms by Tempel et al., Pereyra et al., and Martinez et al. We analyse how different identification techniques determine differences in the filament statistical p...

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Detalles Bibliográficos
Autores: Rost, Agustín Matías, Stasyszyn, Federico Andres, Pereyra, Luis Alberto, Martínez, Héctor J.
Tipo de recurso: artículo
Estado:Versión publicada
Fecha de publicación:2020
País:Argentina
Institución:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/140903
Acceso en línea:http://hdl.handle.net/11336/140903
Access Level:acceso abierto
Palabra clave:COSMOLOGY: OBSERVATIONS
GALAXIES: STATISTICS
LARGE-SCALE STRUCTURE OF UNIVERSE
METHODS: OBSERVATIONAL
https://purl.org/becyt/ford/1.3
https://purl.org/becyt/ford/1
Descripción
Sumario:In this work, we compare three catalogues of cosmological filaments identified in the Sloan Digital Sky Survey by means of different algorithms by Tempel et al., Pereyra et al., and Martinez et al. We analyse how different identification techniques determine differences in the filament statistical properties: length, elongation, redshift distribution, and abundance. We find that the statistical properties of the filaments strongly depend on the identification algorithm. We use a volume-limited sample of galaxies to characterize other properties of filaments such as: galaxy overdensity, luminosity function of galaxies, mean galaxy luminosity, filament luminosity, and the overdensity profile of galaxies around filaments. In general, we find that these properties primarily depended on filament length. Shorter filaments have larger overdensities, are more populated by red galaxies, and have better defined galaxy overdensity profiles, than longer filaments. Concluding that galaxies belonging to filaments have characteristic signatures depending on the identification algorithm used.