Photometric redshift galaxies as tracers of the filamentary network

Kruuse, Maarja; Tempel, Elmo; Kipper, Rain; Stoica, Radu

doi:10.1051/0004-6361/201935096

Cited by 6 publications

(6 citation statements)

References 46 publications

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“…We will develop the model further to combine the spectroscopic and photometric galaxies for improved performance. Kruuse et al (2019) shows that the photometric galaxies correlate with the Bisous filaments, and as shown in this paper, the higher the input number density the higher the quality of the detected filamentary network. For example, in SDSS DR12, the photometric galaxies outnumber the spectroscopic galaxies by 100 to 1 (Beck et al 2016).…”

Section: Discussionsupporting

confidence: 74%

Assessing the reliability of the Bisous filament finder

Muru

Tempel

2021

A&A

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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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Section: Discussionsupporting

confidence: 74%

Assessing the reliability of the Bisous filament finder

Muru

Tempel

2021

A&A

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“…Leclercq et al 2016;Porqueres et al 2018;Tsaprazi et al 2022a). Kruuse et al (2019) further showed that photometric redshifts are positively correlated with filaments detected in spectroscopic galaxy observations.…”

Section: C2 Gravitational Potentialmentioning

confidence: 83%

Higher-order statistics of the large-scale structure from photometric redshifts

Tsaprazi¹,

Jasche²,

Lavaux³

et al. 2023

Preprint

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Context. The large-scale structure is a major source of cosmological information. However, next-generation photometric galaxy surveys will only provide a distorted view of cosmic structures due to large redshift uncertainties. Aims. To address the need for accurate reconstructions of the large-scale structure in presence of photometric uncertainties, we present a framework that constrains the three-dimensional dark matter density jointly with galaxy photometric redshift probability density functions (PDFs), exploiting information from galaxy clustering. Methods. Our forward model provides Markov Chain Monte Carlo realizations of the primordial and present-day dark matter density, inferred jointly from data. Our method goes beyond 2-point statistics via field-level inference. It accounts for all observational uncertainties and the survey geometry. Results. We showcase our method using mock catalogs that emulate next-generation surveys with a worst-case redshift uncertainty, equivalent to ∼300 Mpc. On scales 150 Mpc, we improve the cross-correlation of the photometric galaxy positions with the ground truth from 28% to 86%. The improvement is significant down to 13 Mpc. On scales 150 Mpc, we achieve a cross-correlation of 80 − 90% with the ground truth for the dark matter density, radial peculiar velocities, tidal shear and gravitational potential. Conclusions. We achieve accurate inferences of the large-scale structure on scales smaller than the original redshift uncertainty. Despite the large redshift uncertainty, we recover individual cosmic structures. Owing to our structure growth model, we infer plausible initial conditions of structure formation. Finally, we constrain individual photometric redshift PDFs. This work opens up the possibility to extract information at the smallest cosmological scales with next-generation photometric surveys, going beyond approaches that compress information in the data.

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“…In SDSS DR12, there are about 100 times more photometric galaxies than spectroscopic ones and using those would help to increase input data density. The distance for photometric galaxies has high uncertainty but Kruuse et al (2019) show that photometric galaxies are correlated with the filamentary pattern. The fraction of galaxies in filaments with photometric and mixed samples in Figure 1 show that adding photometric galaxies improves the number of galaxies in filaments.…”

Section: Resultsmentioning

confidence: 99%

Detecting cosmic filamentary network with stochastic Bisous model

Muru

2020

Proc. IAU

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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.

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Photometric redshift galaxies as tracers of the filamentary network

Cited by 6 publications

References 46 publications

Assessing the reliability of the Bisous filament finder

Assessing the reliability of the Bisous filament finder

Higher-order statistics of the large-scale structure from photometric redshifts

Detecting cosmic filamentary network with stochastic Bisous model

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