14 citations · 33 across the 9 of their papers we have counts for
9 papers
Semiresolved Stellar Populations as Distance Indicators
Ignacio Martín-Navarro, Patricia Iglesias Navarro, Francesco La Barbera +13
Galaxy distances are central to our understanding of the Universe. Despite the success of existing approaches, independent and complementary methods remain valuable for testing sys…
FASTAR -- II. Semi-resolved evolutionary stellar population models
Ignacio Martín-Navarro, Alexandre Vazdekis, Luis Peralta de Arriba +12
Standard evolutionary synthesis models rely on the assumption of a fully sampled stellar initial mass function (IMF). Under this assumption, the age, chemical composition, and IMF…
FASTAR -- I. Continuous and differentiable evolutionary stellar population models
Ignacio Martín-Navarro, Alexandre Vazdekis, Luis Peralta de Arriba +11
The development of evolutionary stellar population models is central to interpreting observations of galaxies in terms of astrophysical quantities. Stellar population models must t…
The spatially-resolved effect of mergers on the stellar mass assembly of MaNGA galaxies
Eirini Angeloudi, Marc Huertas-Company, Jesús Falcón-Barroso +3
Understanding the origin of stars within a galaxy - whether formed in-situ or accreted from other galaxies (ex-situ) - is key to constraining its evolution. Spatially resolving the…
Simulation-based inference of the 2D ex-situ stellar mass fraction distribution of galaxies using variational autoencoders
Eirini Angeloudi, Marc Huertas-Company, Jesús Falcón-Barroso +4
Galaxies grow through star formation (in-situ) and accretion (ex-situ) of other galaxies. Reconstructing the relative contribution of these two growth channels is crucial for const…
Constraints on the in-situ and ex-situ stellar masses in nearby galaxies with Artificial Intelligence
Eirini Angeloudi, Jesús Falcón-Barroso, Marc Huertas-Company +4
The hierarchical model of galaxy evolution suggests that the impact of mergers is substantial on the intricate processes that drive stellar assembly within a galaxy. However, accur…
AstroPT: Scaling Large Observation Models for Astronomy
Michael J. Smith, Ryan J. Roberts, Eirini Angeloudi +1
This work presents AstroPT, an autoregressive pretrained transformer developed with astronomical use-cases in mind. The AstroPT models presented here have been pretrained on 8.6 mi…
ERGO-ML: Comparing IllustrisTNG and HSC galaxy images via contrastive learning
Lukas Eisert, Connor Bottrell, Annalisa Pillepich +5
Modern cosmological hydrodynamical galaxy simulations provide tens of thousands of reasonably realistic synthetic galaxies across cosmic time. However, quantitatively assessing the…
ERGO-ML: Towards a robust machine learning model for inferring the fraction of accreted stars in galaxies from integral-field spectroscopic maps
Eirini Angeloudi, Jesús Falcón-Barroso, Marc Huertas-Company +4
Quantifying the contribution of mergers to the stellar mass of galaxies is key for constraining the mechanisms of galaxy assembly across cosmic time. However, the mapping between o…