Uncovering substructure with wavelets: proof of concept using Abell 2744

TL;DR

This paper introduces a wavelet-based method to identify substructures in galaxy cluster data, demonstrating that observed substructure in Abell 2744 aligns with LambdaCDM predictions when using this approach.

Contribution

A new wavelet transform technique is proposed to detect substructures directly from particle data, avoiding biases from subhalo finding algorithms.

Findings

Identified three Abell 2744 analogues in the MXXL simulation.

Observed substructure distribution is consistent with LambdaCDM predictions.

Discrepancies with previous methods are due to differing substructure definitions.

Abstract

A recent comparison of the massive galaxy cluster Abell 2744 with the Millennium XXL (MXXL) N-body simulation has hinted at a tension between the observed substructure distribution and the predictions of LambdaCDM. Follow-up investigations indicated that this could be due to the contribution from the host halo and the subhalo finding algorithm used. To be independent of any subhalo finding algorithm, we therefore investigate the particle data of the MXXL simulation directly. We propose a new method to find substructures in 2D mass maps using a wavelet transform, which treats the simulation and observations equally. Using the same criteria to define a subhalo in observations and simulated data, we find three Abell 2744 analogues in the MXXL simulation. Thus the observations in Abell 2744 are in agreement with the predictions of LambdaCDM. We investigate the reasons for the discrepancy between the results obtained from the SUBFIND and full particle data analyses. We find that this is due to incompatible substructure definitions in observations and SUBFIND.