56 citations · 151 across the 7 of their papers we have counts for
7 papers
Galaxy 3D Shape Recovery using Mixture Density Network
Suk Yee Yong, K. E. Harborne, Caroline Foster +3
Since the turn of the century, astronomers have been exploiting the rich information afforded by combining stellar kinematic maps and imaging in an attempt to recover the intrinsic…
A morphological segmentation approach to determining bar lengths
Mitchell K. Cavanagh, Kenji Bekki, Brent A. Groves
Bars are important drivers of galaxy evolution, influencing many physical processes and properties. Characterising bars is a difficult task, especially in large-scale surveys. In t…
The redshift evolution of the S0 fraction for in COSMOS
Mitchell K. Cavanagh, Kenji Bekki, Brent A. Groves
Lenticular (S0) galaxies are galaxies that exhibit a bulge and disk component, yet lack any clear spiral features. With features considered intermediary between spirals and ellipti…
The galaxy morphology-density relation in the EAGLE simulation
Joel Pfeffer, Mitchell K. Cavanagh, Kenji Bekki +4
The optical morphology of galaxies is strongly related to galactic environment, with the fraction of early-type galaxies increasing with local galaxy density. In this work we prese…
The evolution of barred galaxies in the EAGLE simulations
Mitchell K. Cavanagh, Kenji Bekki, Brent A. Groves +1
We study the morphologies of 3,964 galaxies and their progenitors with in the reference EAGLE hydrodynamical simulation from redshifts to , c…
Morphological classification of galaxies with deep learning: comparing 3-way and 4-way CNNs
Mitchell K. Cavanagh, Kenji Bekki, Brent A. Groves
Classifying the morphologies of galaxies is an important step in understanding their physical properties and evolutionary histories. The advent of large-scale surveys has hastened…