Galaxy Colours in the AKARI Deep SEP Survey

TL;DR

This paper develops and applies color-based criteria using AKARI far-infrared and mid-infrared data to efficiently classify extragalactic sources into different galaxy types, reducing the need for extensive follow-up observations.

Contribution

It introduces a novel, simulation-based method for segregating galaxy populations by color criteria in the far-infrared, validated with AKARI survey data.

Findings

Successful segregation of normal, starburst, and ULIRG galaxies using AKARI FIS data.

Enhanced classification accuracy with additional MIR imaging from AKARI IRC.

Color criteria effectively produce source counts without extensive ground-based follow-up.

Abstract

We investigate the segregation of the extragalactic population via colour criteria to produce an efficient and inexpensive methodology to select specific source populations as a function of far-infrared flux. Combining galaxy evolution scenarios and a detailed spectral library of galaxies, we produce simulated catalogues incorporating segregation of the extragalactic population into component types (Normal, star-forming, AGN) via color cuts. As a practical application we apply our criteria to the deepest survey to be undertaken in the far-infrared with the AKARI (formerly ASTRO-F) satellite. Using the far-infrared wavebands of the Far-Infrared Surveyor (FIS, one of the focal-plane instruments on AKARI) we successfully segregate the normal, starburst and ULIRG populations. We also show that with additional MIR imaging from AKARI's Infrared Camera (IRC), significant contamination and/or degeneracy can be further decreased and show a particular example of the separation of cool normal galaxies and cold ULIRG sources. We conclude that our criteria provide an efficient means of selecting source populations (including rare luminous objects) and produce colour-segregated source counts without the requirement of time intensive ground-based follow up to differentiate between the general galaxy population.