Issue |
A&A
Volume 630, October 2019
|
|
---|---|---|
Article Number | A62 | |
Number of page(s) | 21 | |
Section | Cosmology (including clusters of galaxies) | |
DOI | https://doi.org/10.1051/0004-6361/201936054 | |
Published online | 24 September 2019 |
The biasing phenomenon
1
Tartu Observatory, 61602 Tõravere, Estonia
e-mail: jaan.einasto@to.ee
2
ICRANet, Piazza della Repubblica 10, 65122 Pescara, Italy
3
Estonian Academy of Sciences, 10130 Tallinn, Estonia
Received:
9
June
2019
Accepted:
5
August
2019
Context. We study biasing as a physical phenomenon by analysing geometrical and clustering properties of density fields of matter and galaxies.
Aims. Our goal is to determine the bias function using a combination of geometrical and power spectrum analyses of simulated and real data.
Methods. We apply an algorithm based on the local densities of particles, δ, to form simulated, biased models using particles with δ ≥ δ0. We calculate the bias function of model samples as functions of the particle-density limit δ0. We compare the biased models with Sloan Digital Sky Survey (SDSS) luminosity-limited samples of galaxies using the extended percolation method. We find density limits δ0 of biased models that correspond to luminosity-limited SDSS samples.
Results. The power spectra of biased model samples allow estimation of the bias function b(> L) of galaxies of luminosity L. We find the estimated bias parameter of L* galaxies, b* = 1.85 ± 0.15.
Conclusions. The absence of galaxy formation in low-density regions of the Universe is the dominant factor of the biasing phenomenon. The second-largest effect is the dependence of the bias function on the luminosity of galaxies. Variations in gravitational and physical processes during the formation and evolution of galaxies have the smallest influence on the bias function.
Key words: large-scale structure of Universe / dark matter / cosmology: theory / galaxies: clusters: general / methods: numerical
© ESO 2019
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.