The n-point streaming model: how velocities shape correlation functions in redshift space

DOI10.1088/1475-7516/2020/07/043zbMath1492.85018arXiv2005.05331OpenAlexW3105950889MaRDI QIDQ5070285

Cristiano Porciani, Joseph Kuruvilla

Publication date: 11 April 2022

Published in: Journal of Cosmology and Astroparticle Physics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2005.05331

zbMATH Keywords

galaxy clusteringredshift surveyscosmic flows

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Diffraction, scattering (78A45) Group rings of finite groups and their modules (group-theoretic aspects) (20C05) Electromagnetic fields in general relativity and gravitational theory (83C50) Galactic and stellar structure (85A15) Set functions and measures and integrals in infinite-dimensional spaces (Wiener measure, Gaussian measure, etc.) (28C20) Cluster sets, prime ends, boundary behavior (30D40) Mathematical modeling or simulation for problems pertaining to relativity and gravitational theory (83-10)

Uses Software

• SciPy
• NumPy
• Matplotlib
• GADGET
• Cython

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Divergence measures based on the Shannon entropy
• Statistical Physics of Particles
• Exploring redshift-space distortions in large-scale structure

This page was built for publication: The n-point streaming model: how velocities shape correlation functions in redshift space