Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging

Cheng, Ting-Yun; Conselice, Christopher J.; Arag�n-Salamanca, Alfonso; Li, Nan; Bluck, Asa F.L.; Hartley, Will G.; Annis, James; Brooks, David; Doel, Peter; Garc�a-Bellido, Juan; James, David J.; Kuehn, Kyler; Kuropatkin, Nikolay; Smith, Mathew; Sobreira, Flavia; Tarle, Gregory

doi:10.1093/mnras/staa501

All Outputs (8)

SDSS-IV MaNGA: when is morphology imprinted on galaxies? (2020)
Journal Article

It remains an open question as to how long ago the morphology that we see in a present-day galaxy was typically imprinted. Studies of galaxy populations at different redshifts reveal that the balance of morphologies has changed over time, but such sn... Read More about SDSS-IV MaNGA: when is morphology imprinted on galaxies?.

Formation of S0s in extreme environments II: the star-formation histories of bulges, discs and lenses (2020)
Journal Article

Different processes have been proposed to explain the formation of S0s, including mergers, disc instabilities, and quenched spirals. These processes are expected to dominate in different environments, and thus leave characteristic footprints in the k... Read More about Formation of S0s in extreme environments II: the star-formation histories of bulges, discs and lenses.

SDSS-IV MaNGA: Spatially resolved star formation in barred galaxies (2020)
Journal Article

A novel wave-energy device is presented. Both a preliminary proof-of-principle of a working, scaled laboratory version of the energy device is shown as well as the derivation and analysis of a comprehensive mathematical and numerical model of the new... Read More about SDSS-IV MaNGA: Spatially resolved star formation in barred galaxies.

SDSS-IV MaNGA: Excavating the fossil record of stellar populations in spiral galaxies (2020)
Journal Article

We perform a “fossil record” analysis for ≈800 low-redshift spiral galaxies, using STARLIGHT applied to integral field spectroscopic observations from the SDSS-IV MaNGA survey to obtain fully spatially-resolved high-resolution star formation historie... Read More about SDSS-IV MaNGA: Excavating the fossil record of stellar populations in spiral galaxies.

SDSS-IV MaNGA: spatially resolved dust attenuation in spiral galaxies (2020)
Journal Article

Mapping and characterization of cosmic filaments in galaxy cluster outskirts: strategies and forecasts for observations from simulations (2020)
Journal Article

Upcoming wide-field surveys are well-suited to studying the growth of galaxy clusters by tracing galaxy and gas accretion along cosmic filaments. We use hydrodynamic simulations of volumes surrounding 324 clusters from The ThreeHundred project to dev... Read More about Mapping and characterization of cosmic filaments in galaxy cluster outskirts: strategies and forecasts for observations from simulations.

Identifying Strong Lenses with Unsupervised Machine Learning using Convolutional Autoencoder (2020)
Journal Article

In this paper we develop a new unsupervised machine learning technique comprised of a feature extractor, a convolutional autoencoder (CAE), and a clustering algorithm consisting of a Bayesian Gaussian mixture model (BGM). We apply this technique to v... Read More about Identifying Strong Lenses with Unsupervised Machine Learning using Convolutional Autoencoder.

Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging (2020)
Journal Article

There are several supervised machine learning methods used for the application of automated morphological classification of galaxies; however, there has not yet been a clear comparison of these different methods using imaging data, or a investigation... Read More about Optimizing automatic morphological classification of galaxies with machine learning and deep learning using Dark Energy Survey imaging.