Morphostatistical characterization of the spatial galaxy distribution through Gibbs point processes
Abstract
This paper proposes a morphostatistical characterization 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.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Aug 09, 2021
- Source ID
- 10.1093/mnras/stab2268
Entities
People
- Lluís Hurtado-gil
- Pablo Arnalte-Mur
- Radu S Stoica
- Vicent J Martínez
Organizations
- American Museum of Natural History
- Case Western Reserve University
- Chinese Academy of Sciences
- Drexel University
- Higher Education Funding Council for England
- Institute for Advanced Study
- Johns Hopkins University
- Los Alamos National Laboratory
- Max Planck Society
- National Aeronautics and Space Administration
- National Science Foundation
- New Mexico State University
- ODIGEO
- Ohio State University
- Princeton University
- United States Department of Energy
- United States Naval Observatory
- University of Basel
- University of Chicago
- University of Lorraine
- University of Pittsburgh
- University of Portsmouth
- University of Valencia
- University of Washington