Identifying AGN host galaxies with convolutional neural networks

no code implementations • 15 Dec 2022 • Ziting Guo, John F. Wu, Chelsea E. Sharon

Active galactic nuclei (AGN) are supermassive black holes with luminous accretion disks found in some galaxies, and are thought to play an important role in galaxy evolution.

Predicting galaxy spectra from images with hybrid convolutional neural networks

1 code implementation • 25 Sep 2020 • John F. Wu, J. E. G. Peek

Galaxies can be described by features of their optical spectra such as oxygen emission lines, or morphological features such as spiral arms.

Connecting optical morphology, environment, and HI mass fraction for low-redshift galaxies using deep learning

1 code implementation • 31 Dec 2019 • John F. Wu

A galaxy's morphological features encode details about its gas content, star formation history, and feedback processes which regulate its growth and evolution.

Astrophysics of Galaxies Instrumentation and Methods for Astrophysics

Using convolutional neural networks to predict galaxy metallicity from three-color images

1 code implementation • 30 Oct 2018 • John F. Wu, Steven Boada

We train a deep residual convolutional neural network (CNN) to predict the gas-phase metallicity ($Z$) of galaxies derived from spectroscopic information ($Z \equiv 12 + \log(\rm O/H)$) using only three-band $gri$ images from the Sloan Digital Sky Survey.

Astrophysics of Galaxies