Using photometric redshift data to improve the detection of galactic filaments with the Bisous model

Context. Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. This limits the sky areas and depth where we can detect the filamentary network. Aims. As there are proportionally more photometric redshift data than spectroscopic, we aim to use data with ph...

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Veröffentlicht in:Astronomy and astrophysics (Berlin) 2023-02, Vol.670, p.A77
Hauptverfasser: Muru, M. M., Tempel, E.
Format: Artikel
Sprache:eng
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Zusammenfassung:Context. Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. This limits the sky areas and depth where we can detect the filamentary network. Aims. As there are proportionally more photometric redshift data than spectroscopic, we aim to use data with photometric redshifts to improve and expand the areas where we can detect the large-scale structure of the Universe. The Bisous model is a filament finder that uses only the galaxy positions. We present a proof of concept, showing that the Bisous filament finder can improve the detected filamentary network with photometric redshift data. Methods. We created mock data from the M ULTI D ARK -G ALAXIES catalogue. Galaxies with spectroscopic redshifts were given exact positions from the simulation. Galaxies with photometric redshifts were given uncertainties along one coordinate. The errors were generated with different Gaussian distributions for different samples. We sample the photometric galaxy positions for each Bisous run based on the uncertainty distribution. In some runs, the sampled positions are closer to the true positions and produce persistent filaments; other runs produce noise, which is suppressed in the post-processing. Results. There are three different types of samples: spectroscopic only, photometric only, and mixed samples of galaxies with photometric and spectroscopic redshifts. In photometric-only samples, the larger the uncertainty for photometric redshifts, the fewer filaments are detected, and the filaments strongly align along the line of sight. Using mixed samples improves the number of filaments detected and decreases the alignment bias of those filaments. The results are compared against the full spectroscopic sample. The recall for photometric-only samples depends heavily on the size of uncertainty and dropped close to 20%; for mixed samples, the recall stayed between 40% and 80%. The false discovery rate stayed below 5% in every sample tested in this work. Mixed samples showed better results than corresponding photometric-only or spectroscopic-only samples for every uncertainty size and number of spectroscopic galaxies in mixed samples. Conclusions. Mixed samples of galaxies with photometric and spectroscopic redshifts help us to improve and extend the large-scale structure further than possible with only spectroscopic samples. Although the uncertainty sizes tested in this work are smaller than those for the available photometric data, up
ISSN:0004-6361
1432-0746
DOI:10.1051/0004-6361/202244883