2 papers
astro-ph.GA2026
Galaxy mergers classification using CNNs trained on Sérsic models, residuals and raw images
D. M. Chudy, W. J. Pearson, A. Pollo +5
Galaxy mergers are crucial for understanding galaxy evolution, and with large upcoming datasets, automated methods such as Convolutional Neural Networks (CNNs) are essential for ef…
astro-ph.GA2025
Observationally derived change in the star formation rate as mergers progress
W. J. Pearson, L. Wang, V. Rodriguez-Gomez +2
Galaxy mergers can change the rate at which stars are formed. We can trace when these changes occur in simulations of galaxy mergers. However, for observed galaxies we do not know…