I had the pleasure of joining an online panel alongside fellow award-winning scientists from the National Academy of Exact, Physical, and Natural Sciences (ANCEFN) to share insights from our research with the public. The panel was expertly coordinated by Dr. Gloria Dubner and moderated by esteemed science journalist Nora Bär.
The full conversation can be found in YouTube (in spanish). My participation stars at 1:01:59
I am honored to have received the Encouragement Award from the National Academy of Exact, Physical, and Natural Sciences (ANCEFN). This award recognizes the contributions of young professionals in Argentina, up to 40 years of age, in scientific and technological research. It’s a privilege to be acknowledged for my work, and I look forward to continuing my efforts in advancing our understanding of astronomy and science!
This year, I had the privilege of participating as a mentor in the NASA Space Apps Challenge, with the local event organized by CONAE, IBM, and CAECE. It was an inspiring experience to guide and support teams in Buenos Aires as they tackled real-world challenges. Over the course of 48 hours, participants worked on innovative solutions related to space exploration and Earth sciences. It was incredible to witness the creativity, collaboration, and passion of all participants.
I had the honor of contributing to a Congressional Report on Artificial Intelligence (AI) by the Biblioteca del Congreso de la Nación (BCN). The report explores AI’s transformative impact on Argentina, focusing on its use in health, scientific research, education, and governance. It also addresses critical issues such as data privacy, algorithmic bias, and cybersecurity, emphasizing the need for legislative updates to ensure ethical AI deployment.
You can read the full report here (in Spanish).
In December 2024, I will be co-organizing a hands-on session with Ting-yun (Sunny) Cheng titled “Machine Learning Uses in Astrophysics.” This session will be a part of the upcoming Deciphering the Cosmic Code for Galaxy Formation workshop, which will take place from December 9-13, 2024 in Puerto Varas, Chile.
We have a lot of exciting material to prepare and are looking forward to the challenge. Stay tuned for more updates as we get ready to explore the intersection of machine learning and astrophysics!
I had another virtual chat about galaxies and astrophysics with students from the Osiris Astronomy Club.
The club is based in Bariloche and El Bolsón, in the Argentinian Patagonia.
I am grateful to the students and their teacher, Marcelo Alvarez, for their interest and their excellent questions.
Primordial black holes (PBHs) have been proposed as potential candidates for dark matter (DM) and have garnered significant attention in recent years. Our objective is to delve into the distinct impact of PBHs on gas properties and their potential role in shaping the cosmic structure. Specifically, we aim to analyze the evolving gas properties while considering the presence of accreting PBHs with varying monochromatic masses and in different quantities. By studying the feedback effects produced by this accretion, our final goal is to assess the plausibility of PBHs as candidates for DM. We develop a semi-analytical model which works on top of the CIELO hydrodynamical simulation around \(z\sim23\). This model enables a comprehensive analysis of the evolution of gas properties influenced by PBHs. Our focus lies on the temperature and hydrogen abundances, placing specific emphasis on the region closest to the halo center. We explore PBH masses of 1, 33, and 100\(M_\odot\), located within mass windows where a substantial fraction of DM could exist in the form of PBHs. We investigate various DM fractions composed of these PBHs (\(f_{\rm{PBH}}>10^{-4}\)).Our findings suggest that the existence of PBHs with masses of \(1~M_\odot\) and fractions greater than or equal to approximately \(10^{-2}\) would be ruled out due to the significant changes induced in gas properties. The same applies to PBHs with a mass of \(33~M_\odot\) and \(100~M_\odot\) and fractions greater than approximately \(10^{-3}\). These effects are particularly pronounced in the region nearest to the halo center, potentially leading to delayed galaxy formation within haloes.
The variations in metallicity and spatial patterns within star-forming regions of galaxies result from diverse physical processes unfolding throughout their evolutionary history, with a particular emphasis in recent events. Analysing MaNGA and \eagle~galaxies, we discovered an additional dependence of the mass-metallicity relation (MZR) on metallicity gradients (\(\nabla_{\rm (O/H)}\)). Two regimes emerged for low and high stellar mass galaxies, distinctly separated at approximately \(m_\odot > 10^{9.75}\). Low-mass galaxies with strong positive \(\nabla_{\rm (O/H)}\)~appear less enriched than the MZR median, while those with strong negative gradients are consistently more enriched in both simulated and observed samples. Interestingly, low-mass galaxies with strong negative \(\nabla_{\rm (O/H)}\)~exhibit high star-forming activity, regardless of stellar surface density or \(\nabla_{\rm (O/H)}\). In contrast, a discrepancy arises for massive galaxies between MaNGA and \eagle~datasets. The latter exhibit a notable anticorrelation between specific star formation rate and stellar surface density, independent of \(\nabla_{\rm (O/H)}\), while MaNGA galaxies show this trend mainly for strong positive \(\nabla_{\rm (O/H)}\). Further investigation indicates that galaxies with strong negative gradients tend to host smaller central black holes in observed datasets, a trend not replicated in simulations. These findings suggest disparities in metallicity recycling and mixing history between observations and simulations, particularly in massive galaxies with varying metallicity gradients. These distinctions could contribute to a more comprehensive understanding of the underlying physics.
In this work, we aim at investigating the morphology evolution of Milky Way mass-like dark matter haloes selected from the CIELO and IllustrisTNG Projects. The connection between halo shapes and their environment has been studied in previous works at z=0 but their connection remains yet to be fully understood. We focus on the evolution across cosmic time of the halo shapes and the relation with the infalling material, using hydrodynamical simulations. Our findings show that haloes tend to be more triaxial at earlier times as a consequence of stronger accretion in the direction of the filaments. As the haloes evolve towards a dominant isotropic accretion mode and relaxation, their shape at 20 percent of the virial mass becomes more spherical. In agreement with previous results, baryons have an important effect within the inner regions of the haloes, driving them from triaxial to rounder shapes. We also find a correlation between the strength of the quadrupole infalling mode and the degree of ellipticity of the haloes: as the filament strength decreases steadily with redshift, the haloes became more spherical and less elliptical.
Context. The morphological classification of galaxies is considered a relevant issue and can be approached from different points of view. The increasing growth in the size and accuracy of astronomical data sets brings with it the need for the use of automatic methods to perform these classifications.
Aims. The aim of this work is to propose and evaluate a method for automatic unsupervised classification of kinematic morphologies of galaxies that yields a meaningful clustering and captures the variations of the fundamental properties of galaxies.
Methods. We obtain kinematic maps for a sample of 2064 galaxies from the largest simulation of the eagle project that mimics integral field spectroscopy (IFS) images. These maps are the input of a dimensionality reduction algorithm followed by a clustering algorithm. We analyse the variation of physical and observational parameters among the clusters obtained from the application of this procedure to different inputs. The inputs studied in this paper are (a) line-of-sight velocity maps for the whole sample of galaxies observed at fixed inclinations, (b) line-of-sight velocity, dispersion, and flux maps together for the whole sample of galaxies observed at fixed inclinations, (c) line-of-sight velocity, dispersion, and flux maps together for two separate subsamples of edge-on galaxies with similar amount of rotation, and (d) line-of-sight velocity, dispersion, and flux maps together for galaxies from different observation angles mixed.
Results. The application of the method to solely line-of-sight velocity maps achieves a clear division between slow rotators (SRs) and fast rotators (FRs) and can differentiate rotation orientation. By adding the dispersion and flux information at the input, low rotation edge-on galaxies are separated according to their shapes and, at lower inclinations, the clustering using the three types of maps maintains the overall information obtained using only the line-of-sight velocity maps. This method still produces meaningful groups when applied to SRs and FRs separately, but, in the first case, the division into clusters is less clear than when the input includes a variety of morphologies. When applying the method to a mixture of galaxies observed from different inclinations, we obtain results that are similar to those in our previous experiments with the advantage that in this case the input is more realistic. In addition, our method has proven to be robust to consistently classify the same galaxies viewed from different inclinations