S. Veliz Astudillo’s scientific contributions

Context. Although the influence of galaxy clusters on galaxy evolution is relatively well understood, the impact of the dynamical states of these clusters is less clear. This series of papers explores how the dynamical state of galaxy clusters affects their galaxy populations’ physical and morphological properties. Aims. The primary aim of this first paper is to evaluate the dynamical state of 87 massive ( M 500 ≥ 1.5 × 10 ¹⁴ M ⊙ ) galaxy clusters at low redshifts (0.10 ≤ z ≤ 0.35). This allowed us to obtain a well-characterized sample for analyzing the relevant physical and morphological properties, planned for our next work. Methods. We employed six dynamical state proxies that utilize optical and X-ray imaging data. We applied a principal component analysis to integrate these proxies effectively, allowing for a robust classification of galaxy clusters into relaxed, intermediate, and disturbed states based on their dynamical characteristics. Results. The methodology successfully segregates the clusters of galaxies into the three dynamical states. An examination of the projected galaxy distributions in optical wavelengths and gas distributions in X-ray further confirms the consistency of these classifications. The dynamical states of the clusters are statistically distinguishable, providing a clear categorization for further analysis.

While the influence of galaxy clusters on galaxy evolution is relatively well-understood, the impact of the dynamical states of these clusters is less clear. This paper series explores how the dynamical state of galaxy clusters affects their galaxy populations' physical and morphological properties. The primary aim of this first paper is to evaluate the dynamical state of 87 massive ($M_{500} \geq 1.5 \times 10^{14} M_{\odot}$) galaxy clusters at low redshifts ($0.10 \leq z \leq 0.35$). This will allow us to have a well-characterized sample for analyzing physical and morphological properties in our next work. We employ six dynamical state proxies utilizing optical and X-ray imaging data. Principal Component Analysis (PCA) is applied to integrate these proxies effectively, allowing for robust classification of galaxy clusters into relaxed, intermediate, and disturbed states based on their dynamical characteristics. The methodology successfully segregates the galaxy clusters into the three dynamical states. Examination of the galaxy distributions in optical wavelengths and gas distributions in X-ray further confirms the consistency of these classifications. The clusters' dynamical states are statistically distinguishable, providing a clear categorization for further analysis.