Analysis of cosmological bias within spherical collapse model


Sujata Mohanty, Rajesh Gopal

The goal of our research work is to analyze cosmological bias parameter. Parametric equations of spherical collapse model are used to calculate the values of spherical collapse over density and mass variance, which is further used in bias formulae to find the values of cosmological bias. Spherical collapse over density has been calculated in the range of redshift 0 to 1. Also, it is compared with the value according to the spherical collapse model. Bias is one of the parameters which are utilized to infer cosmological parameters. Extracting the cosmological parameters is very much useful to know and understand about the birth and evolution of our universe. As there is no direct probe to get the idea about the existence of dark matter. Bias factor helps to analyze about dark matter. The bias coefficient of higher order terms in Taylor series expansion are found to be in ascending order. Increasing values of bias indicate the large-scale structure formation at current epoch is more and more clustered. Values of bias are discussed in result. Also, bias values have been analyzed for redshift in the range 2 to 0. The graph has been plotted bias versus redshift. Let’s found bias decreases with decrease of redshift. That means bias evolves with redshift. Bias value less than one and negative value of bias implies that structure formation is in linear region and higher values of bias indicates the structure formation occurs in nonlinear region. Negative value of bias is also called as antibias. That means the structure formation has not started yet. It is still in linear region. The bias value nearly equal to one indicates that the structure formation has been transformed from linear region to nonlinear region. So, the result showing bias values greater than one indicates that evolution of structure formation occurs in nonlinear region.

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How to cite paper:

Mohanty, S, , Gopal, R, (2022). Analysis of cosmological bias within spherical collapse model. EUREKA: Physics and Engineering, 5, 3-11. doi:https://doi.org/10.21303/2461-4262.2022.002429