# The biasing phenomenon

## TL;DR

This paper investigates the physical origins of galaxy biasing by analyzing geometrical and clustering properties of matter and galaxy density fields, using simulations and SDSS data to estimate the bias function and its dependence on luminosity.

## Contribution

It introduces a method combining geometrical and power spectrum analysis to determine the galaxy bias function from simulated and real data, highlighting the role of low-density regions and luminosity.

## Key findings

- Bias parameter for L* galaxies estimated as 1.85 ± 0.15.
- Density limits in models correspond to SDSS luminosity samples.
- Galaxy formation in low-density regions is the main biasing factor.

## Abstract

{We study biasing as a physical phenomenon by analysing geometrical and clustering properties of density fields of matter and galaxies.} {Our goal is to determine the bias function using a combination of geometrical and power spectrum analysis of simulated and real data.} {We apply an algorithm based on local densities of particles, $\delta$, to form simulated biased models using particles with $\delta \ge \delta_0$. We calculate the bias function of model samples as functions of the particle density limit $\delta_0$. 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 $\delta_0$ of biased models, which correspond to luminosity limited SDSS samples.} {Power spectra of biased model samples allow to estimate the bias function $b(>L)$ of galaxies of luminosity $L$. We find the estimated bias parameter of $L_\ast$ galaxies, $b_\ast =1.85 \pm 0.15$. } {The absence of galaxy formation in low-density regions of the Universe is the dominant factor of the biasing phenomenon. 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 to the bias function. }