The Impact of Cluster Mergers on Galaxy Properties

TL;DR

This study investigates whether major cluster mergers influence star formation in member galaxies by analyzing four nearby SAMI clusters with differing dynamical states using single-fibre spectroscopy. Galaxies are spectroscopically classified into passive, star-forming, and Hδ-strong populations, with SF activity tracked via the star-forming galaxy fraction $f_{SFG}$ and EW$(H\alpha)$, and their spatial and phase-space distributions are examined. The results show only a mild, statistically marginal increase in $f_{SFG}$ for merging clusters within $R_{200}$, with SFGs more mixed in mergers and little evidence for merger-triggered SF from EW$(H\alpha)$ distributions; simulations suggest the observed central SFGs arise from first infall rather than triggered SF. The findings imply that cluster mergers mainly drive dynamical mixing in an intermediate assembly stage, preserving the SF-density relation and highlighting the need for larger, resolved datasets to robustly quantify merger-driven effects on galaxy evolution.

Abstract

The impact of galaxy cluster mergers on the properties of the resident galaxies remains poorly understood. In this paper, we investigate the effects of merging environments on star formation (SF) activity in nearby clusters ($0.04<z<0.06$) from the SAMI Galaxy Survey - A168, A2399, A3380, and EDCC 0442 - which exhibit different dynamical activity. Using single-fibre spectroscopy from the SAMI Cluster Redshift Survey and Sloan Digital Sky Survey, we trace SF activity across the cluster sample by identifying the star-forming galaxy (SFG) population based on spectral features. We find a mild enhancement in the star-forming galaxy fraction ($f_{SFG}$) in merging clusters, although not statistically significant. The spatial and projected phase-space distributions show that SFGs in merging clusters are well-mixed with the passive population, while galaxy populations exhibit a clear segregation in the relaxed clusters. Analysis of the equivalent width of the $\rm Hα$ line, as a tracer of recent SF activity, does not reveal strong evidence of triggered SF activity as a function of dynamical state for both the global cluster environment and subsamples of galaxies selected near possible merger features. This suggests that the increase in $f_{SFG}$ is due to the mixing of galaxies in dynamically complex, young merging systems that are still forming, unlike their older, relaxed counterparts that have had longer to quench.

Figures (10)

• Figure 1: Legacy Survey imaging Dey2019 of the cluster sample used in this study, overlaid with X-ray emission (cyan contours) from XMM-Newton for A2399 and EDCC 0442 and Chandra for A168 and A3880. The top and bottom panels highlight the merging and relaxed clusters, respectively, with names and redshifts written in the upper left of each panel. In the top left panel, the gold contours show radio emission (170-231 MHz) from the GLEAM survey Hurley-Walker2017. The lime crosses and gold diamonds denote the BCGs and the adopted centres of each system, respectively. As shown by the arrows in the top left plot, the orientation is North up, East to the left, and this applies to all clusters. It is evident that X-ray and radio properties of merging clusters differ markedly from those of the relaxed clusters, highlighting the ongoing dynamical activity.
• Figure 2: Colour-mass diagram of members for each cluster. The red dots, cyan stars, and green squares represent the galaxies classified as "passive", "star-forming", and "H$\delta$-strong" based on the classification scheme outlined in Section \ref{['sec:Spectral classification']}. The magenta dashed, the black solid, and the red dashed lines represent the mass limits for log$(M_\ast/M_\odot)$ = 9.00, 9.25, and 9.50, respectively.
• Figure 3: Star-forming galaxy fractions for different cluster-centric regions - R $<$ R$_{200}$ and 1 $<$ R/R$_{200}$$<$ 2. The grey open symbols (i.e., pentagon, hexagon, thick cross, and diamond) show each cluster's fraction (i.e., A168, A2399, A3880, and EDCC 0442, respectively). The blue stars and the red squares represent the stacked samples based on similar cluster dynamics (i.e., merging and relaxed, respectively). The error bars show the uncertainties on the fractions estimated through the approach given in Cameron2011.
• Figure 4: Spatial distribution of cluster galaxies. Columns represent individual clusters, while rows highlight all, passive (red) and star-forming galaxies (blue) from top to bottom, respectively. The $16^{th}, \ 50^{th}, and \ 84^{th}$ percentile contours are generated from the smoothed kernel density estimate (KDE) for the population highlighted in the lower left of each panel using ks package Duong2012 in R. As indicated by the black arrows in the top row, North is up and East is to the left.
• Figure 5: Normalised cluster-centric distance distributions. The red and blue histograms highlight the distributions for PASG and SFGs, respectively. The vertical lines show the mean values for PASGs and SFGs, respectively, calculated via biweight estimation and given in the upper left of each panel alongside the biweighted dispersion and the skewness. The stripe density plots highlight exact values for each galaxy.