Cluster analyses of gigahertz-peaked spectrum sources with self-organising maps

Abstract

Context. Gigahertz-peaked spectrum (GPS) sources and high frequency peakers (HFPs) are among the smallest of active galactic nuclei currently believed to represent the earliest phases in the evolution of extragalactic radio sources. Recently there has been evidence of contamination by other types of radio sources among the GPS and HFP samples, but the confirmed GPS sources or HFPs also seem to form a very heterogeneous population. Aims. We study the statistical clustering of the GPS sources and the HFPs by taking as many source parameters as possible to find homogeneous groups among the sources. We expect the clustering to give us insight into the physical parameters that play a role in different source populations. Methods. We have collected a sample of 206 GPS sources and HFPs from the literature and gathered a massive database of various source properties, such as the redshift, the size, the polarization, the magnitudes, and the properties of the radio continuum. To visualize and to cluster these multidimensional data we used self-organising maps (SOM), which are neural networks trained by an unsupervised algorithm. We have classified the sources with an auxiliary classification to trace the locations of different types of radio continuum spectra on the map. Results. The sources form distinctive clusters on the map, which is supported by the accordant organisation of the non-numerical parameters not used in the analysis, such as the radio morphology and the optical identification. Our results confirm that the blazars contaminating the GPS and the HFP samples are physically different from the genuine GPS sources and HFPs, and they should be excluded from the samples. The genuine GPS sources form various clusters, which indicates the existence of different subpopulations, besides the expected galaxy-quasar dualism.