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Detecting cosmic filamentary network with stochastic Bisous model

Published online by Cambridge University Press:  20 January 2023

Moorits Mihkel Muru Open the ORCID record for Moorits Mihkel Muru [Opens in a new window]
Moorits Mihkel Muru*
Affiliation:
Tartu Observatory, University of Tartu, Observatooriumi 1, 61602 Tõravere, Estonia email: [email protected]
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Abstract

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The Bisous model is a tool that uses stochastic methods to detect the network of galactic filaments. This model is explicitly developed to detect the structure from observational data, using only galaxy positions as input. This paper shows that the Bisous model gives reliable results and including photometric data improves the resulting filamentary network. We used MultiDark-Galaxies catalogue to create a mock with photometric redshifts and samples with different galaxy number densities. We found that the filaments detected with the Bisous model are reliable; 85% of the detected filaments are unchanged compared to results with more complete input data. Adding photometric data improves the fraction of galaxies in filaments. Using the confusion matrix technique, we found the false discovery rate to always be below 5% when using photometric data.

Keywords

methods: data analysismethods: statisticalgalaxies: statisticslarge-scale structure of the Universe
Type
Poster Paper
Information
Proceedings of the International Astronomical Union , Volume 16 , Symposium S362: The Predictive Power of Computational Astrophysics as a Discovery Tool , June 2020 , pp. 54 - 55
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of International Astronomical Union

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