Identification of Grand-design and Flocculent Spirals from SDSS using Convolutional Neural network

S. Sarkar, G. Narayanan, A. Banerjee, P. Prakash

Published 2022-05-18Version 1

Spiral galaxies can be classified into the Grand-designs and Flocculents, based on the nature of their spiral arms. The Grand-designs exhibit almost continuous, high contrast spiral arms and are believed to be driven by density waves; the Flocculents, on the other hand, have patchy or discontinuous spiral features and are mostly stochastic in origin. We construct a convolutional neural network (CNN) model that classifies spirals into Grand-designs and Flocculents, with a testing accuracy of $\mathrm{97.2\%}$. We then use the above model for classifying $\mathrm{1,220}$ new spirals from the SDSS. Out of these, $\mathrm{721}$ are identified as Flocculents, the rest being Grand-designs. The mean asymptotic rotational velocity of our sample Grand-designs and Flocculents are $\mathrm{218 \; km \; s^{-1}}$ and $\mathrm{145 \; km \; s^{-1}}$ respectively, while their respective de Vaucouleur morphological type indices are $\mathrm{2.6}$ and $\mathrm{4.7}$. This possibly indicates that Grand-designs are mostly ordinary high surface brightness galaxies like our Milky Way, while Flocculents are intermediate-mass low surface brightness galaxies.