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In this study, we obtain the size distribution of voids as a 3-parameter redshift independent log-normal void probability function (VPF) directly from the Cosmic Void Catalog (CVC). Although many statistical models of void distributions are based on the counts in randomly placed cells, the log-normal VPF that we here obtain is independent of the shape of the voids due to the parameter-free void finder of the CVC. We use three void populations drawn from the CVC generated by the Halo Occupation Distribution (HOD) Mocks which are tuned to three mock SDSS samples to investigate the void distribution statistically and the effects of the environments on the size distribution. As a result, it is shown that void size distributions obtained from the HOD Mock samples are satisfied by the 3-parameter log-normal distribution. In addition, we find that there may be a relation between hierarchical formation, skewness and kurtosis of the log-normal distribution for each catalog. We also show that the shape of the 3-parameter distribution from the samples is strikingly similar to the galaxy log-normal mass distribution obtained from numerical studies. This similarity of void size and galaxy mass distributions may possibly indicate evidence of nonlinear mechanisms affecting both voids and galaxies, such as large scale accretion and tidal effects. Considering in this study all voids are generated by galaxy mocks and show hierarchical structures in different levels, it may be possible that the same nonlinear mechanisms of mass distribution affect the void size distribution.
Following up on previous studies, we here complete a full analysis of the void size distributions of the Cosmic Void Catalog (CVC) based on three different simulation and mock catalogs; dark matter, haloes and galaxies. Based on this analysis, we att
Two separate statistical tests are described and developed in order to test un-binned data sets for adherence to the power-law form. The first test employs the TP-statistic, a function defined to deviate from zero when the sample deviates from the po
In this paper, we propose an abstract procedure for debiasing constrained or regularized potentially high-dimensional linear models. It is elementary to show that the proposed procedure can produce $frac{1}{sqrt{n}}$-confidence intervals for individu
Distribution function is essential in statistical inference, and connected with samples to form a directed closed loop by the correspondence theorem in measure theory and the Glivenko-Cantelli and Donsker properties. This connection creates a paradig
We study the formation and evolution of the cosmic web, using the high-resolution CosmoGrid $Lambda$CDM simulation. In particular, we investigate the evolution of the large-scale structure around void halo groups, and compare this to observations of