Abstract

Context. Recent years have given rise to numerous methods of detecting the cosmic web elements in the large-scale structure of the Universe. All of these methods describe more or less the same features, but each with its nuance. The Bisous filament finder is a stochastic tool for identifying the spines of filaments using galaxy positions. Aims. This work provides an analysis of how the galaxy number density of the input data affects the filaments detected with the Bisous model and gives estimates of the reliability of the method itself to assess the robustness of the results. Methods. We applied the Bisous filament finder to MultiDark-Galaxies data, using various magnitude cuts from the catalogue to study the effects of different galaxy number densities on the results and different parameters of the model. We compared the structures by the fraction of galaxies in filaments and the volume filled by filaments, and we analysed the similarities between the results from different cuts based on the overlap between detected filamentary structures. The filament finder was also applied to the exact same data 200 times with the same parameters to study the stochasticity of the results and the correlation between different runs was calculated. Results. Multiple samples show that galaxies in filaments have preferentially higher luminosity. We found that when a galaxy is in a filament there is a 97% chance that the same galaxy would be in a filament with even more complete input data and about 85% of filaments are persistent when detecting the filamentary network with higher-density input data. Lower galaxy number density inputs mean the Bisous model finds fewer filaments, but the filaments found are persistent even if we use more complete input data for the detection. We calculated the correlation coefficient between 200 Bisous runs on the exact same input, which is 0.98. Conclusions. This study confirms that increased number density of galaxies is important to obtain a more complete picture of the cosmic web. To overcome the limitation of the spectroscopic surveys, we will develop the Bisous model further to apply this tool to combined spectroscopic and narrow-band photometric redshift surveys, such as the J-PAS.

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