| Popis: |
In this paper, we study the dynamical and statistical properties of the cosmic web and investigate their ability to infer the corresponding cosmological model. Our definition of the cosmic web is based on the local dimensionality of the gravitational collapse that classifies the cosmic web into four categories: voids, walls, filaments, and nodes. Our results show that each category has its specific non-Gaussian evolution over time and that these non-Gaussianities depend on the cosmological parameters. Nonetheless, the non-Gaussianities in each category exist even at early epochs when the matter field has a Gaussian distribution. Additionally, by using deep learning techniques, we show that leveraging the cosmic web information engenders an improved inference of cosmological parameters, when compared to merely using the matter field. |
