5k citations · 5.2k across the 14 of their papers we have counts for
14 papers
EPOCHS XI: The Structure and Morphology of Galaxies in the Epoch of Reionization to z ~ 12.5
Lewi Westcott, Christopher J. Conselice, Thomas Harvey +29
We present a structural analysis of 521 galaxy candidates at 6.5 < z < 12.5, with in the F444W filter, taken from the EPOCHS v1 sample, consisting of uniformly reduced…
Galaxy evolution in the post-merger regime. III -- The triggering of active galactic nuclei peaks immediately after coalescence
Sara L. Ellison, Leonardo Ferreira, Robert Bickley +6
Galaxy mergers have been shown to trigger AGN in the nearby universe, but the timescale over which this process happens remains unconstrained. The Multi-Model Merger Identifier (MU…
Galaxy Mergers in UNIONS -- I: A Simulation-driven Hybrid Deep Learning Ensemble for Pure Galaxy Merger Classification
Leonardo Ferreira, Robert W. Bickley, Sara L. Ellison +7
Merging and interactions can radically transform galaxies. However, identifying these events based solely on structure is challenging as the status of observed mergers is not easil…
EPOCHS I. The Discovery and Star Forming Properties of Galaxies in the Epoch of Reionization at with PEARLS and Public JWST data
Christopher J. Conselice, Nathan Adams, Thomas Harvey +32
We present in this paper the discovery, properties, and a catalog of 1165 high redshift galaxies found in deep JWST NIRCam imaging from the GTO PEARLS survey combine…
EPOCHS III: Unbiased UV continuum slopes at 6.5<z<13 from combined PEARLS GTO and public JWST NIRCam imaging
Duncan Austin, Christopher J. Conselice, Nathan J. Adams +34
We present an analysis of rest-frame UV continuum slopes, , using a sample of 1011 galaxies at from the EPOCHS photometric sample collated from the GTO PEARLS and pub…
Dust Extinction Measures for Galaxies using Machine Learning on JWST Imaging
Kwan Lin Kristy Fu, Christopher J. Conselice, Leonardo Ferreira +4
We present the results of a machine learning study to measure the dust content of galaxies observed with JWST at z > 6 through the use of trained neural networks based on high-reso…