The Herschel Multi-Tiered Extragalactic Survey: Source Extraction and Cross-Identifications in Confusion-Dominated SPIRE Images

TL;DR

This paper introduces a new cross-identification and source extraction method for Herschel SPIRE images, improving detection of faint sources by minimizing blending effects and leveraging Spitzer MIPS 24 micron data.

Contribution

The authors develop a novel technique combining linear inversion and model selection for reliable source cross-identification in confusion-dominated SPIRE images, outperforming traditional methods in faint source recovery.

Findings

Robust cross-identification for sources as faint as 10 mJy at 250 microns.

Improved recovery of faint sources compared to traditional detection methods.

Incompleteness of 20-40% at faint levels due to reliance on 24 micron catalog depth.

Abstract

We present the cross-identification and source photometry techniques used to process Herschel SPIRE imaging taken as part of the Herschel Multi-Tiered Extragalactic Survey (HerMES). Cross-identifications are performed in map-space so as to minimise source blending effects. We make use of a combination of linear inversion and model selection techniques to produce reliable cross-identification catalogues based on Spitzer MIPS 24 micron source positions. Testing on simulations and real Herschel observations show that this approach gives robust results for even the faintest sources S250~10 mJy. We apply our new technique to HerMES SPIRE observations taken as part of the science demostration phase of Herschel. For our real SPIRE observations we show that, for bright unconfused sources, our flux density estimates are in good agreement with those produced via more traditional point source detection methods (SussExtractor; Savage & Oliver et al. 2006) by Smith et al. 2010. When compared to the measured number density of sources in the SPIRE bands, we show that our method allows the recovery of a larger fraction of faint sources than these traditional methods. However this completeness is heavily dependant on the relative depth of the existing 24 micron catalogues and SPIRE imaging. Using our deepest multi-wavelength dataset in GOODS-N, we estimate that the use of shallow 24 micron in our other fields introduces an incompleteness at faint levels of between 20-40 per cent at 250 micron.