Quantifying the Poor Purity and Completeness of Morphological Samples Selected by Galaxy Colour

TL;DR

This study evaluates how galaxy colour-based selection methods are significantly impure and incomplete in accurately identifying galaxy morphologies, highlighting the limitations of using colour as a proxy.

Contribution

The paper quantifies the impurity and incompleteness of colour-based galaxy morphology samples using Galaxy Zoo labels across multiple bands.

Findings

Optical g-r colour threshold yields 56% purity and completeness.

NUV improves selection but still low purity for early-types.

Adding NIR bands does not significantly improve sample purity or completeness.

Abstract

The galaxy population is strongly bimodal in both colour and morphology, and the two measures correlate strongly, with most blue galaxies being late-types (spirals) and most early-types, typically ellipticals, being red. This observation has led to the use of colour as a convenient selection criteria to make samples which are then labelled by morphology. Such use of colour as a proxy for morphology results in necessarily impure and incomplete samples. In this paper, we make use of the morphological labels produced by Galaxy Zoo to measure how incomplete and impure such samples are, considering optical (ugriz), NUV and NIR (JHK) bands. The best single colour optical selection is found using a threshold of g-r = 0.742, but this still results in a sample where only 56% of red galaxies are smooth and 56% of smooth galaxies are red. Use of the NUV gives some improvement over purely optical bands, particularly for late-types, but still results in low purity/completeness for early-types. No significant improvement is found by adding NIR bands. With any two bands, including NUV, a sample of early-types with greater than two-thirds purity cannot be constructed. Advances in quantitative galaxy morphologies have made colour-morphology proxy selections largely unnecessary going forward; where such assumptions are still required, we recommend studies carefully consider the implications of sample incompleteness/impurity.