Unsupervised classification of the intrinsic and morphological properties of quasars through self‐organizing maps. Issue 4 (28th April 2020) - Karafistan, Aysel; Gemikonakli, Eser
Abstract: The aim of this paper is to unveil, by means of self‐organizing maps (SOMs), the connections between intrinsic properties of radio quasars, namely redshift ( z ), luminosity ( P ), continuum slope ( α ), and parameters characterizing radio morphology of the host galaxy: observed linear size and bending. The strong luminosity–redshift correlation established by a prior traditional principal component analysis (PCA) is confirmed for the same dataset that contains 36 nearby ( z < 1.5) and 44 distant ( z > 1.5) quasars with five parameters. The SOM visualizations disentangled the luminosity–linear size anti‐correlation, supporting a dimensionality of p = 2 for the quasar parameter space. The SOM also clustered radio quasars into subgroups with common physical properties. We expect this work to provide a new probe, leading to further clustering of nonlabeled data with respect to the evolution of morphological properties.