English

Using the Mark Weighted Correlation Functions to Improve the Constraints on Cosmological Parameters

Cosmology and Nongalactic Astrophysics 2020-09-02 v2

Abstract

We used the mark weighted correlation functions (MCFs), W(s)W(s), to study the large scale structure of the Universe. We studied five types of MCFs with the weighting scheme ρα\rho^\alpha, where ρ\rho is the local density, and α\alpha is taken as 1, 0.5, 0, 0.5-1,\ -0.5,\ 0,\ 0.5, and 1. We found that different MCFs have very different amplitudes and scale-dependence. Some of the MCFs exhibit distinctive peaks and valleys that do not exist in the standard correlation functions. Their locations are robust against the redshifts and the background geometry, however it is unlikely that they can be used as ``standard rulers'' to probe the cosmic expansion history. Nonetheless we find that these features may be used to probe parameters related with the structure formation history, such as the values of σ8\sigma_8 and the galaxy bias. Finally, after conducting a comprehensive analysis using the full shapes of the W(s)W(s)s and WΔs(μ)W_{\Delta s}(\mu)s, we found that, combining different types of MCFs can significantly improve the cosmological parameter constraints. Compared with using only the standard correlation function, the combinations of MCFs with α=0, 0.5, 1\alpha=0,\ 0.5,\ 1 and α=0, 1, 0.5, 0.5, 1\alpha=0,\ -1,\ -0.5,\ 0.5,\ 1 can improve the constraints on Ωm\Omega_m and ww by 30%\approx30\% and 50%50\%, respectively. We find highly significant evidence that MCFs can improve cosmological parameter constraints.

Keywords

Cite

@article{arxiv.2007.03150,
  title  = {Using the Mark Weighted Correlation Functions to Improve the Constraints on Cosmological Parameters},
  author = {Yizhao Yang and Haitao Miao and Qinglin Ma and Miaoxin Liu and Cristiano G. Sabiu and Jaime Forero-Romero and Yuanzhu Huang and Limin Lai and Qiyue Qian and Yi Zheng and Xiao-Dong Li},
  journal= {arXiv preprint arXiv:2007.03150},
  year   = {2020}
}

Comments

15pages, 17figures, APJ accepted

R2 v1 2026-06-23T16:54:13.775Z