39 citations · 56 across the 4 of their papers we have counts for
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Performance of morphological classifiers for galaxy mergers compared to current machine learning methods
Aidan P. Cotter, William J. Pearson, William J. pearson +4
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…
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…
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…
Morphological signatures of mergers in the TNG50 simulation and the Kilo-Degree Survey: the merger fraction from dwarfs to Milky Way-like galaxies
Alejandro Guzmán-Ortega, Vicente Rodriguez-Gomez, Gregory F. Snyder +2
Using the TNG50 cosmological simulation and observations from the Kilo-Degree Survey (KiDS), we investigate the connection between galaxy mergers and optical morphology in the loca…