The Shapes of Galaxy Groups

TL;DR

This study analyzes the shapes of galaxy groups using probability density functions for their projected axial ratios, revealing a shift from prolate to oblate ellipsoids after correction, and finds good agreement with $ ext{Lambda}$CDM simulations.

Contribution

It provides the first detailed comparison of galaxy group shapes with mock data, showing a transition from prolate to oblate distributions after correction and confirming consistency with cosmological simulations.

Findings

Raw data best fits a prolate ellipsoid with Gaussian axial ratio distribution.

Corrected data favors an oblate ellipsoid with different axial ratio parameters.

Higher multiplicity groups tend to be more spherical.

Abstract

We derive probability density functions for the projected axial ratios of the real and mock 2PIGG galaxy groups, and use this data to investigate the intrinsic three dimensional shape of the dark matter ellipsoids that they trace. As well as analysing the raw data for groups of varying multiplicities, a convolution corrected form of the data is also considered which weights the probability density function according to the results of multiple Monte-Carlo realizations of discrete samples from the input spatial distributions. The important effect observed is that the best fit distribution for all the raw data is a prolate ellipsoid with a Gaussian distribution of axial ratios with $\bar{\beta}=0.36$ and $\sigma=0.14$, whilst for the convolved data the best fit solution is that of an oblate ellipsoid $\bar{\beta}=0.22$ and $\sigma=0.1$. Previously only prolate distributions were thought compatible with the data, this being interprated as evidence of filamentary collapse at nodes. We also find that even after allowing for the sampling effects, the corrected data is better fit using separate multiplicity bins, which display a trend towards more spherical halos in higher multiplicity groups. Finally, we find that all results in the real data are in good agreement with the mock data from $\Lambda$CDM simulations, KS tests showing that all comparative data have been drawn from the same distributions within the $1\sigma$ confidence limits.