27 citations · 82 across the 9 of their papers we have counts for
7 papers · 1 filter
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…
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…
Galaxy Morphology from through the eyes of JWST
M. Huertas-Company, K. G. Iyer, E. Angeloudi +26
We analyze the Near Infrared (m) rest-frame morphologies of galaxies with in the redshift range , compare with previous HST-based results an…
MaNGIA: 10,000 mock galaxies for stellar population analysis
Regina Sarmiento, Marc Huertas-Company, Johan H. Knapen +4
Modern astronomical observations give unprecedented access to the physical properties of nearby galaxies, including spatially resolved stellar populations. However, observations ca…
The Seventeenth Data Release of the Sloan Digital Sky Surveys: Complete Release of MaNGA, MaStar and APOGEE-2 Data
Abdurro'uf, Katherine Accetta, Conny Aerts +337
This paper documents the seventeenth data release (DR17) from the Sloan Digital Sky Surveys; the fifth and final release from the fourth phase (SDSS-IV). DR17 contains the complete…
Capturing the physics of MaNGA galaxies with self-supervised Machine Learning
Regina Sarmiento, Marc Huertas-Company, Johan H. Knapen +4
As available data sets grow in size and complexity, advanced visualization tools enabling their exploration and analysis become more important. In modern astronomy, integral field…