The Next Generation Virgo Cluster Survey (NGVS). XL. The Morphological Classification of Virgo Cluster Galaxies

Abstract We present a study of morphologies, based on deep <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mrow> <mml:mi>u</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>*</mml:mo> </mml:mrow> </mml:msup> <mml:mi>g</mml:mi> <mml:mo accent="false">′</mml:mo> <mml:mi>i</mml:mi> <mml:mo accent="false">′</mml:mo> <mml:mi>z</mml:mi> <mml:mo accent="false">′</mml:mo> </mml:math> imaging of the Virgo Cluster from the Next Generation Virgo Cluster Survey, for 3689 Virgo cluster members spanning a mass range of ∼10 11 –10 5 M ⊙ . Our analysis introduces a new, two-component visual classification scheme developed to capture the morphological diversity of galaxies over more than 6 orders of magnitude in stellar mass. Our morphological classifications use two parameters to describe the global structure and star formation activity of each galaxy. Structural subcodes denote features such as spiral arms, bars, disks, shells, and streams, while star formation subcodes indicate the form and location of the current star formation activity (e.g., in cores, clumps, filaments). These visual classifications rely on deep <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mrow> <mml:mi>g</mml:mi> </mml:mrow> <mml:mrow> <mml:mo accent="true">′</mml:mo> </mml:mrow> </mml:msup> </mml:math> -band images, supplemented by <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" overflow="scroll"> <mml:msup> <mml:mrow> <mml:mi>u</mml:mi> </mml:mrow> <mml:mrow> <mml:mo>*</mml:mo> </mml:mrow> </mml:msup> <mml:mi>g</mml:mi> <mml:mo accent="false">′</mml:mo> <mml:mi>i</mml:mi> <mml:mo accent="false">′</mml:mo> </mml:math> ­ color images, as well as unsharp-masked images for a subset of objects. We compare our classifications to previous results for bright member galaxies that used more established schemes, finding good agreement. We also measure quantitative classification statistics (e.g., CASGM 20 ) for a subset of the brighter galaxies, and present catalogs for some galaxy types of special interest, including structurally compact galaxies, ultradiffuse galaxies, candidate ultracompact dwarf transition objects, as well as candidate postmerger systems. These morphological classifications may be useful as a training set in the application of machine learning tools to the next generation of wide-field imaging surveys.