Examinando por Autor "Gómez, Facundo A."
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Ítem Galactic archaeology in the 21st century : unveiling accretion in the MW disc(Universidad Andrés Bello, 2022) Tronrud, Thorold; Tissera, Patricia; Gómez, Facundo A.; Gómez, Matías; Bignone, Lucas; Facultad de Ciencias ExactasThe evolution of large galaxies such as the Milky Way (MW) in Λ Cold Dark Matter (ΛCDM) cosmology is driven by interactions with other galaxies. These interactions affect the structure of the galaxy in long-lasting ways, not only forming the stellar halo, and modifying the size and characteristics of the stellar disc, but also contributing gas that fuels star formation and depositing stars directly into the galaxy. This stellar debris, formed outside the galaxy in which they now reside (a.k.a. ex-situ), retain the chemical fingerprint of the environment in which they formed, leaving them distinct from the stars that were formed within the primary galaxy (a.k.a. in-situ). If these ex-situ stars are located beyond the disc, in the stellar halo, the distributions they occupy in space — based on the kinematics of their progenitor object — may be readily apparent as streams or great circles surrounding the primary galaxy. A population of ex-situ stars are also expected to reside in the stellar disc, even at high circularities. These stars have been found in simulations to be deposited by relatively few massive mergers, but finding them poses a challenge in this dense region. I propose a method, based on training and utilizing neural networks, to classify disc stars as in- or ex-situ based on their chemical parameters. The use of this method is motivated by my research into the effects mergers and accretion have on the galactic stellar disc of a suite of simulated MW-like galaxies, in which I demonstrate that accretion events and accreted stars cause observable changes to calculated metallicity gradients, and can cause disagreements in correlations between observed parameters based on the ages of the stars being used. Galactic discs form inside-out, starting small and slowly expanding with new star formation at the outer edges. This imparts a natural negative age gradient. Stars that have been deposited onto the disc will not necessarily follow this age gradient, which is one of the primary drivers of the stellar disc’s metallicity gradient. These ex-situ stars drive several age-specific correlations between metallicity gradient and 𝑅 −1 eff and 𝜆 ★ gal that vanish entirely once these contaminants are removed. A chemistry-based method for flagging potentially-accreted stars will allow researchers to remove the bulk of these from their samples, which will allow them to examine the evolution of the galactic disc more finely. Furthermore, these flagged, ex-situ stars can be grouped by their characteristics, for attempts to discern early progenitors of the primary galaxy with significantly less noise from stars formed in-situ. I demonstrate that the Galactic Archaeology Neural Network (GANN) recovers usable fractions of nearly every contributor to the suite of simulated stellar discs. Thus, a catalogue of stars flagged by GANN will contain most of the merger information that is present in the stellar disc of a galaxy. Future applications of this method could aid in the discovery of many ancient remnants, and broaden our understanding of how our galaxy formed.Ítem Galaxy evolution in compact groups: II. Witnessing the influence of major structures in their evolution(EDP Sciences, 2025-04) Montaguth, Gissel P.; Monachesi, Antonela; Torres-Flores, Sergio; Gómez, Facundo A.; Lima-Dias, Ciria; Cortesi, Arianna; Mendes De Oliveira, Claudia; Telles, Eduardo; Panda, Swayamtrupta; Grossi, Marco; Lopes, Paulo A. A.; O'Mill, Ana Laura; Hernandez-Jimenez, Jose A.; Olave-Rojas, Daniela E.; Demarco, Ricardo; Kanaan, Antonio; Ribeiro, Tiago; Schoenell, WilliamCompact groups (CGs) of galaxies are an extreme environment for the morphological transformations and the cessation of star formation in galaxies. However, despite initially being conceived as isolated systems, it is now widely recognised that many of them are not as isolated as expected. Our objective is to understand the dynamics of CGs, as well as how the environment surrounding CGs impacts their morphological and physical properties. To achieve this, we selected a sample of 316 CGs in the Stripe 82 region, with a total of 1011 galaxies, and a sample of 2281 field galaxies as a control sample. We find that at least 41% of our sample of CGs are part of major structures, i.e. non-isolated CGs. We find a bimodality in the effective radius (Re)-Sérsic index (n) plane for all transition galaxies (those with (u - r) > 2:3 and n < 2:5) in CGs. Additionally, transition galaxies in isolated CGs populate more densely the Re-n plane for n < 1:75. In contrast, transition galaxies in non-isolated CGs show a bimodal distribution in the Re-n plane, with the n values smoothly increasing towards higher values, and 62% of these galaxies having n > 1:5. This indicates that the majority of these galaxies have already undergone a morphological transformation and primarily contribute to the population of more compact galaxies in the Re-n plane. We find that galaxies in our sample of CGs have a lower mean specific star formation rate (sSFR) compared to the control sample, with non-isolated CGs showing even lower sSFR values, indicating that dense environments suppress star formation. Additionally, non-isolated CGs have a higher fraction of quenched galaxies relative to isolated CGs and the control sample. Based on our results, we propose an evolutionary scenario where the major structures in which the CGs are embedded accelerate the morphological transformations of their galaxy members, and also facilitates preprocessing. Our findings highlight the importance of considering the larger structures in which CGs may be located, when analysing the properties of their galaxy members, as this can significantly affect the evolution of CGs and their galaxies. © The Authors 2025.Ítem Machine learning for galactic archaeology: a chemistry-based neural network method for identification of accreted disc stars(Oxford University Press, 2022-09) Tronrud, Thorold; Tissera, Patricia B.; Gómez, Facundo A.; Grand, Robert J. J.; Pakmor, Ruediger; Marinacci, Federico; Simpson, Christine M.We develop a method ('Galactic Archaeology Neural Network', gann) based on neural network models (NNMs) to identify accreted stars in galactic discs by only their chemical fingerprint and age, using a suite of simulated galaxies from the Auriga Project. We train the network on the target galaxy's own local environment defined by the stellar halo and the surviving satellites. We demonstrate that this approach allows the detection of accreted stars that are spatially mixed into the disc. Two performance measures are defined - recovery fraction of accreted stars, frecov and the probability that a star with a positive (accreted) classification is a true-positive result, P(TP). As the NNM output is akin to an assigned probability (Pa), we are able to determine positivity based on flexible threshold values that can be adjusted easily to refine the selection of presumed-accreted stars. We find that gann identifies accreted disc stars within simulated galaxies, with high frecov and/or high P(TP). We also find that stars in Gaia-Enceladus-Sausage (GES) mass systems are over 50 per cent recovered by our NNMs in the majority (18/24) of cases. Additionally, nearly every individual source of accreted stars is detected at 10 per cent or more of its peak stellar mass in the disc. We also demonstrate that a conglomerated NNM, trained on the halo and satellite stars from all of the Auriga galaxies provides the most consistent results, and could prove to be an intriguing future approach as our observational capabilities expand. © 2022 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.