SearcharxivSearch

arXiv subjects

V. Mesa

Publications and source records attributed to V. Mesa.

2 recordsLinked to original sources

The role of bars in triggering active galactic nuclei galaxies

Bars are considered an efficient mechanism for transporting gas toward the central regions of galaxies, potentially enhancing nuclear activity. However, the extent to which bars influence active galactic nuclei (AGNs), and whether their efficiency varies with environment, remain open questions. In this study, we aim to quantify the role of bars in triggering AGNs by comparing the AGN fraction in barred and non-barred galaxies across different environments. We constructed a sample from the Galaxy Zoo DECaLS catalog, ensuring a control selection where both samples share similar distributions in stellar mass, redshift, magnitude, concentration index, and local density parameter. AGNs were identified using spectroscopic data from the Sloan Digital Sky Survey, yielding 1330 barred AGNs and 1651 unbarred AGNs. We use the [OIII]5007 luminosity (Lum[OIII]) and the accretion rate parameter R as indicators of nuclear activity. Based on these, we applied criteria to distinguish powerful from weak AGNs, allowing a more precise assessment of the bar's impact on the supermassive black hole. Our analysis reveals that barred galaxies tend to host a higher fraction of powerful AGNs. From Lum[OIII], we find that more active nuclei reside in massive, blue galaxies with young stellar populations. We also observe a slight tendency for barred galaxies to host less massive black holes accreting more efficiently. The classification of strong and weak bars shows that more prominent bars correlate with higher nuclear activity. While this trend shows no significant differences in intermediate-density environments, it becomes evident in both low- and high-density regions, where galaxies with strong bars show enhanced AGN activity.

astro-ph.GA

La Serena School for Data Science and the Spanish Virtual Observatory Schools: Initiatives Based on Hands on Experience

The worlds of Data Science (including big and/or federated data, machine learning, etc) and Astrophysics started merging almost two decades ago. For instance, around 2005, international initiatives such as the Virtual Observatory framework rose to standardize the way we publish and transfer data, enabling new tools such as VOSA (SED Virtual Observatory Analyzer) to come to existence and remain relevant today. More recently, new facilities like the Vera Rubin Observatory, serve as motivation to develop efficient and extremely fast (very often deep learning based) methodologies in order to fully exploit the informational content of the vast Legacy Survey of Space and Time (LSST) dataset. However, fundamental changes in the way we explore and analyze data cannot permeate in the "astrophysical sociology and idiosyncrasy" without adequate training. In this talk, I will focus on one specific initiative that has been extremely successful and is based on "learning by doing": the La Serena School for Data Science. I will also briefly touch on a different successful approach: a series of schools organized by the Spanish Virtual Observatory. The common denominator among the two kinds of schools is to present the students with real scientific problems that benefit from the concepts / methodologies taught. On the other hand, the demographics targeted by both initiatives vary significantly and can represent examples of two "flavours" to be followed by others.

astro-ph.IM