Galaxy Structural Parameters in Source Extractor

TL;DR

This paper integrates standardized structural galaxy parameters into Source Extractor to enhance automatic galaxy classification, comparing computed parameters with previous fits and discussing limitations.

Contribution

The paper introduces computed structural parameters into Source Extractor v2.5, aligning with current definitions to improve galaxy classification in large surveys.

Findings

Computed parameters are close to fitted versions for bright objects

Noise affects faint object measurements

Type classification remains challenging with current parameters

Abstract

Over the last decade, the Concentration, Asymmetry and Smoothness (CAS), as well as the M20 and GINI parameters have become popular to automatically classify distant galaxies in images. Ellipticals, spirals and irregular galaxies all appear to occupy different regions of this parameter space. At the same time, the Source Extractor (SE) program has become the mainstay to produce ob ject catalogs from large image surveys. A logical next step would be to incorporate the structural parameters into the Source Extractor software. There are however several problems that arise: 1) the CAS parameters are fits to the images and Source Extractor eschews fits in the interest of speed, 2) the definition of the structural parameters changed over time. Now that there is a clear and agreed-upon definition of the structural parameters, I am incorporating computed versions in the Source Extractor code (v2.5). The fitted CAS parameters are available for the GOODS-N/S fields and I compare the computed structural parameters to those found by the previous fits. My goal is to expand the source structure information in Source Extractor catalogs in order to improve automatic identification of sources, specifically of distant galaxies. The computed parameters perform reasonably close to the fitted versions but noise appears in faint ob jects due to a lack of information. For a subset of objects, the asymmetry signal is outside the SE boundaries and Smoothness still fails to compute for many ob jects. Type classification based on the SE parameters still lacks resolving power.