DS+: A method for the identification of cluster substructures

Benavides, José Antonio Chacón; Biviano, A.; Abadi, Mario G.

doi:10.1051/0004-6361/202245422

“…The ranges of g and h were calculated using the jackknife method on X-ray pixel data and error propagation (personal communication). Shectman (1988) test (DS+ 20 Benavides et al 2023) to find galaxy groups in and around galaxy clusters. We input R.A., decl., and the redshift from Section 2.2.…”

Section: Identification Of Substructuresmentioning

confidence: 99%

Distribution of Merging and Post-merger Galaxies in Nearby Galaxy Clusters

Kim,

Sheen,

Jaffé

et al. 2024

ApJ

0

View full text Add to dashboard Cite

We study the incidence and spatial distribution of galaxies that are currently undergoing gravitational merging (M) or that have signs of being post-merger (PM) in six galaxy clusters (A754, A2399, A2670, A3558, A3562, and A3716) within the redshift range of 0.05 ≲ z ≲0.08. To this aim, we obtained Dark Energy Camera mosaics in the u ′ , g ′ , and r ′ bands covering up to 3 × R 200 of the clusters, reaching 28 mag arcsec−2 surface brightness limits. We visually inspect u ′ g ′ r ′ color-composite images of volume-limited (M r < −20) cluster member galaxies to identify whether galaxies are of M or PM type. We find 4% M-type and 7% PM-type galaxies in the galaxy clusters studied. By adding spectroscopic data and studying the projected phase-space diagram (PPSD) of the projected clustocentric radius and the line-of-sight velocity, we find that PM-type galaxies are more virialized than M-type galaxies, having a 1%–5% higher fraction within the escape-velocity region, while the fraction of M-type was ∼10% higher than the PM type in the intermediate environment. Similarly, on a substructure analysis, M types were found in groups in the outskirts, while PM-type populated groups were found in ubiquitous regions of the PPSD. Adopting literature-derived dynamical state indicator values, we observed a higher abundance of M types in dynamically relaxed clusters. This finding suggests that galaxies displaying post-merger features within clusters likely merged in low-velocity environments, including clusters outskirts and dynamically relaxed clusters.

show abstract

“…Many previous studies have used the properties of cluster galaxies to ascertain the dynamical state. For example, some previous studies used the BCG (Kim et al 2017;Lopes et al 2018;Raouf et al 2019;De Luca et al 2021), redshift distribution (Dressler & Shectman 1988;Sampaio et al 2021), spatial distribution (Aguerri & Sánchez-Janssen 2010;Einasto et al 2012;Wen & Han 2013;Lopes et al 2018), or both redshift and spatial distributions (Diaferio et al 2005;Benavides et al 2023). These properties were combined to produce dynamical state indicators for their clusters.…”

Section: Introductionmentioning

confidence: 99%

“…Other observational studies have used a variety of other dynamical state indicators, such as the magnitude gap between the BCG and the second-brightest galaxy (Raouf et al 2019;Zhoolideh Haghighi et al 2020), the center-of-mass offset between the X-ray-and luminosity-weighted centers (Yuan & Han 2020;De Luca et al 2021), the concentration parameter defined by Navarro-Frenk-White profile (Navarro et al 1996) fitting (Okabe et al 2019), and the detection of substructures using both positional and redshift information (Benavides et al 2023).…”

Section: Introductionmentioning

confidence: 99%

New Observational Recipes for Measuring Dynamical States of Galaxy Clusters

Kim,

Smith,

Ko

et al. 2024

ApJ

0

View full text Add to dashboard Cite

During cluster assembly, a cluster’s virialization process leaves behind signatures that can provide information on its dynamical state. However, no clear consensus yet exists on the best way to achieve this. Therefore, we attempt to derive improved recipes for classifying the dynamical states of clusters in observations using cosmological simulations. The cluster halo mass and their subhalos’ mass are used to 1014 M ⊙ h −1 and 1010 M ⊙ h −1 to calculate five independent dynamical state indicators. We experiment with recipes by combining two to four indicators for detecting specific merger stages, like recent and ancient mergers. These recipes are made by plotting merging clusters and a control sample of relaxed clusters in multiple-indicator parameter space, then applying a rotation matrix method to derive the best way to separate mergers from the control sample. The success of the recipe is quantified using the success rate and overlap percentage of the merger and control histograms along the newly rotated x-axis. This provides us with recipes using different numbers of combined indicators and for different merger stages. Among the recipes, the stellar mass gap and center offset are the first and second most dominant of the indicators, and using more indicators improves the effectiveness of the recipe. When applied to observations, our results show good agreement with literature values of cluster dynamical states.

show abstract

The effect of cluster dynamical state on ram-pressure stripping

Lourenço,

Jaffé,

Vulcani

et al. 2023

Monthly Notices of the Royal Astronomical Society

View full text Add to dashboard Cite

Theoretical and observational studies have suggested that ram-pressure stripping by the intracluster medium can be enhanced during cluster interactions, boosting the formation of the ”jellyfish” galaxies. In this work, we study the incidence of galaxies undergoing ram-pressure stripping in 52 clusters of different dynamical states. We use optical data from the WINGS/OmegaWINGS surveys and archival X-ray data to characterise the dynamical state of our cluster sample, applying eight different proxies. We then compute the number of ram-pressure stripping candidates relative to the infalling population of blue late-type galaxies within a fixed circular aperture in each cluster. We find no clear correlation between the fractions of ram-pressure stripping candidates and the different cluster dynamical state proxies considered. These fractions also show no apparent correlation with cluster mass. To construct a dynamical state classification closer to a merging ”sequence”, we perform a visual classification of the dynamical states of the clusters, combining information available in optical, X-ray, and radio wavelengths. We find a mild increase in the RPS fraction in interacting clusters with respect to all other classes (including post-mergers). This mild enhancement could hint at a short-lived enhanced ram-pressure stripping in ongoing cluster mergers. However, our results are not statistically significant due to the low galaxy numbers. We note this is the first homogeneous attempt to quantify the effect of cluster dynamical state on ram-pressure stripping using a large cluster sample, but even larger (especially wider) multi-wavelength surveys are needed to confirm the results.

show abstract

DS+: A method for the identification of cluster substructures

Cited by 3 publications

References 134 publications

Distribution of Merging and Post-merger Galaxies in Nearby Galaxy Clusters

Distribution of Merging and Post-merger Galaxies in Nearby Galaxy Clusters

New Observational Recipes for Measuring Dynamical States of Galaxy Clusters

The effect of cluster dynamical state on ram-pressure stripping

Contact Info

Product

Resources

About