Morpho-statistical characterisation of the spatial galaxy distribution through Gibbs point processes

TL;DR

This paper introduces a morpho-statistical approach using Gibbs point processes to model and analyze the spatial distribution of galaxies, capturing their filamentary structures and interactions for better understanding of cosmic structures.

Contribution

It presents a novel application of inhomogeneous Gibbs point processes combined with the ABC Shadow algorithm for detailed galaxy distribution analysis.

Findings

Successful modeling of galaxy filamentary patterns

Quantitative analysis of galaxy interactions

Enhanced statistical inference of galaxy spatial structures

Abstract

This paper proposes a morpho-statistical characterisation of the galaxy distribution through spatial statistical modelling based on inhomogeneous Gibbs point processes. The galaxy distribution is supposed to exhibit two components. The first one is related to the major geometrical features exhibited by the observed galaxy field, here, its corresponding filamentary pattern. The second one is related to the interactions exhibited by the galaxies. Gibbs point processes are statistical models able to integrate these two aspects in a probability density, controlled by some parameters. Several such models are fitted to real observational data via the ABC Shadow algorithm. This algorithm provides simultaneous parameter estimation and posterior based inference, hence allowing the derivation of the statistical significance of the obtained results.