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

TL;DR

This study demonstrates that combining photometric and spectroscopic redshift data enhances the detection of galactic filaments using the Bisous model, overcoming limitations of spectroscopic data alone.

Contribution

The paper introduces a method to incorporate photometric redshift data into filament detection, improving large-scale structure mapping with the Bisous model.

Findings

Mixed data samples improve filament detection accuracy.

Photometric redshift uncertainties reduce detection recall.

False discovery rate remains below 5% across tests.

Abstract

Filament finders are limited, among other things, by the abundance of spectroscopic redshift data. As there are proportionally more photometric redshift data than spectroscopic, we aim to use photometric data to improve and expand the areas where we can detect the large-scale structure of the Universe. We present a proof of concept, showing that the Bisous filament finder can improve the detected filamentary network with photometric redshift data. We created mock data from the MultiDark-Galaxies 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. 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. 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.