66 citations · 597 across the 33 of their papers we have counts for
33 papers
The Radial Acceleration Relation in Galaxies and Clusters from a Two-Component, Virial-Motivated Framework
Christine C. Dantas, Andre L. B. Ribeiro, Hugo V. Capelato
We present a comparative analysis of acceleration data for gravitational systems drawn from multiple observational sources, including: (i) early-type galaxies (ETGs) (Lelli et al.…
Examining transitional galaxies to understand the role of clusters and their dynamical status in galaxy quenching
Douglas Brambila, Paulo A. A. Lopes, André L. B. Ribeiro +1
In this work, we consider four different galaxy populations and two distinct global environments in the local Universe (z ) to investigate the evolution of transitional…
Unveiling the internal structure of Hercules supercluster
R. Monteiro-Oliveira, D. F. Morell, V. M. Sampaio +2
We have investigated the structure of the Hercules supercluster (SCL160) based on data originally extracted from the Sloan Digital Sky Survey SDSS-DR7. We have traced the mass dist…
Investigating the Projected Phase Space of Gaussian and Non-Gaussian Clusters
V. M. Sampaio, R. R. de Carvalho, I. Ferreras +3
By way of the projected phase-space (PPS), we investigate the relation between galaxy properties and cluster environment in a subsample of groups from the Yang Catalog. The sample…
Probing Saraswati's heart: evaluating the dynamical state of the massive galaxy cluster A2631 through a comprehensive weak-lensing and dynamical analysis
R. Monteiro-Oliveira, A. C. Soja, A. L. B. Ribeiro +4
In this work, we investigate the dynamical state of the galaxy cluster Abell 2631, a massive structure located at the core of the Saraswati supercluster. To do this, we first solve…
Reliable Photometric Membership (RPM) of Galaxies in Clusters. I. A Machine Learning Method and its Performance in the Local Universe
P. A. A. Lopes, A. L. B. Ribeiro
We introduce a new method to determine galaxy cluster membership based solely on photometric properties. We adopt a machine learning approach to recover a cluster membership probab…