The Characterised Noise Hi source finder: Detecting Hi galaxies using a novel implementation of matched filtering

TL;DR

This paper introduces the CNHI source finder, a novel, optimized matched filtering method for automated detection of Hi galaxies in large 3-D spectral line datacubes from ASKAP's WALLABY survey, enabling efficient processing of massive data.

Contribution

The paper presents a new implementation of matched filtering tailored for 3-D data and a sparse representation technique for large datacubes, improving automated Hi galaxy detection.

Findings

Optimized for WALLABY's 3-D spectral data

Employs sparse representation for large datacubes

Expected to detect ~500,000 Hi galaxies up to z~0.2

Abstract

The spectral line datacubes obtained from the Square Kilometre Array (SKA) and its precursors, such as the Australian SKA Pathfinder (ASKAP), will be sufficiently large to necessitate automated detection and parametrisation of sources. Matched filtering is widely acknowledged as the best possible method for the automated detection of sources. This paper presents the Characterised Noise Hi (CNHI) source finder, which employs a novel implementation of matched filtering. This implementation is optimised for the 3-D nature of the planned Wide-field ASKAP Legacy L-band All- sky Blind surveY's (WALLABY) Hi spectral line observations. The CNHI source finder also employs a novel sparse representation of 3-D objects, with a high compression rate, to implement Lutz one-pass algorithm on datacubes that are too large to process in a single pass. WALLABY will use ASKAP's phenomenal 30 square degree field of view to image \sim 70% of the sky. It is expected that WALLABY will find 500 000 Hi galaxies out to z \sim 0.2.