Value Added Catalogs

In addition to the primary SDSS photometry and spectroscopy, there are a few extra catalogs created by our collaborators that are distributed through the SAS. These Value-Added Catalogs (VACs) are listed below, and include catalogs that were released in earlier data releases.

MaNGA Morphology Deep Learning DR17 catalog

Scientific Analysis Catalog
MaNGA
GALAXY
Marvin
DR17DR15

Catalog of morphologies based on deep learning models for MaNGA DR17 galaxies.

Helena Domínguez Sanchez, Berta Margalef Bentabol, Mariangela Bernardi

Abstract

This is a morphological catalog of MaNGA galaxies obtained with Deep learning models. The models have been trained and tested on SDSS-DR7 images with great success(Domínguez Sánchez et al. 2018). The DR17 morphological catalog Domínguez Sánchez et al. 2021) contains a series of Galaxy Zoo like attributes (edge-on, barred, projected pairs, bugle prominence and roundness), as well as a T-Type and a finer separation between pure elliptical and S0 galaxies. All the T-Type values in this catalog have been eye-balled, and modified if necessary, for additional reliability (see Fischer et al. 2019). This catalog complements the set of parameters provided by the MaNGA PyMorph DR17 photometric catalog (Domínguez Sánchez et al. 2021)). It also complements the Galaxy Zoo MaNGA catalog by providing a T-Type and a finer separation between S0s and pure ellipticals. There are some differences with respect to the previous version (DR15) of the MaNGA DL morphological catalogue presented in Fischer et al. (2019). Namely, the low-end of the T-Types are better recovered in this new version. In addition, we provide a binary classification which separates early type galaxies (ETGs) from late types (LTGs) in a cleaner way, especially at the intermediate types (-1 < T-Type < 2), where the T-Type values show a large scatter. Moreover, we have trained 10 models for each classification task (15 for the T-Type classification) and the value provided in the catalogue is their average. We also report the standard deviation, which can be used as a proxy for the uncertainty in the classification. We recommend that you always use the latest updated catalog (DR17). The DR15 version of this VAC is still available here.

Catalog last modified: 2021-12-06 07:47:05

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