One-point Statistics in various cosmic environments in the presence of massive neutrinos

TL;DR

This study analyzes the spatial distribution of cosmic structures in different environments under standard and extended cosmological models, demonstrating that certain statistical functions can differentiate these environments and potentially probe dark sector physics.

Contribution

It introduces the use of first-point statistics like the J-function in various cosmic environments within $ u \Lambda$CDM, extending previous methods to include massive neutrinos.

Findings

Statistical functions differentiate cosmic environments effectively.

Functions can distinguish between $ m u \Lambda$CDM and $ m \Lambda$CDM.

Potential of these statistics as complementary cosmological probes.

Abstract

Studying the structures (halos and galaxies) within the cosmic environments (void, sheet, filament, and node) where they reside is an ongoing attempt in cosmological studies. The link between the properties of structures and the cosmic environments may help to unravel the nature of the dark sector of the Universe. In this paper, we study the cosmic web environments from the spatial pattern perspective in the context of $ \Lambda $CDM and $ \nu \Lambda $CDM as an example of an extension to the vanilla model. To do this, we use the T-web classification method and classify the cosmic environments for the catalogues from the gevolution N-body simulations for $ \Lambda $CDM and $ \nu \Lambda $CDM cosmology. Then, we compute the first nearest neighbour cumulative distribution function, spherical contact cumulative distribution function, and $ J$-function for every cosmic environment. In the context of the standard model, the results indicate that these functions can differentiate the various cosmic environments. In association with distinguishing between extensions of the standard model of cosmologies, these functions within the cosmic environment seem beneficial as a complementary probe.