3 papers
astro-ph.GA2026
Performance of morphological classifiers for galaxy mergers compared to current machine learning methods
Aidan P. Cotter, William J. pearson, Subhrata Dey +3
Aims. Non-parametric morphological statistics can be used for efficient classification of galaxy mergers. This work aims to compare the performance of morphological merger classifi…
astro-ph.GA2025
Synthetic JWST galaxy images in the TNG50 simulation - I. Model validation and comparison to observations
Alejandro Guzmán-Ortega, Gustavo Bruzual, Vicente Rodriguez-Gomez +1
We use the TNG50 cosmological simulation and three-dimensional radiative transfer post-processing to generate dust-aware synthetic observations of galaxies at a…
astro-ph.GA2024
Galaxy merger challenge: A comparison study between machine learning-based detection methods
B. Margalef-Bentabol, L. Wang, A. La Marca +14
Various galaxy merger detection methods have been applied to diverse datasets. However, it is difficult to understand how they compare. We aim to benchmark the relative performance…