A new method for the extraction of mid-infrared gamma-ray emitting candidate blazars

TL;DR

This paper introduces a refined three-dimensional infrared color space method, using Principal Component analysis, to identify gamma-ray emitting blazar candidates with high completeness and efficiency.

Contribution

The paper presents a novel 3D locus-based method using PCA for blazar candidate selection, improving upon previous 2D approaches.

Findings

Achieved 81% completeness in identifying blazar candidates.

Attained 97% efficiency in candidate selection.

Enhanced the accuracy of gamma-ray blazar identification.

Abstract

We present a new method for identifying blazar candidates by examining the locus, i.e. the region occupied by the Fermi gamma-ray blazars in the three-dimensional color space defined by the WISE infrared colors. This method is a refinement of our previous approach that made used of the two-dimensional projection of the the distribution of WISE gamma-ray emitting blazars (the Strip) in the three WISE color-color planes. In this paper, we define the three-dimensional locus by means of a Principal Component analysis of the the colors distribution of a large sample of blazars composed by all the ROMA-BZCAT sources with counterparts in the WISE All-Sky Catalog and associated to a gamma-ray source in the second Fermi LAT catalog (2FGL) (the WISE Fermi Blazars sample, WFB). Our new procedure, as reported in [D'Abrusco et al. 2013], yields a total completeness of c=81% and total efficiency of e=97%.