We present a robust, efficient, and user-friendly algorithm for detecting faint emission line sources in large integral-field spectroscopic datacubes. together with the public release of the software package LSDCat (Line Source Detection and Cataloguing). LSDCat uses a 3-dimensional matched filter approach, combined with thresholding in signal-to-noise, to build a catalogue of individual line detections. In a second pass, the detected lines are grouped into distinct objects, and positions, spatial extents, and fluxes of the detected lines are determined. LSDCat requires only a small number of input parameters, and we provide guidelines for choosing appropriate values. The software is coded in Python and capable to process very large datacubes in a short time. We verify the implementation with a source insertion and recovery experiment utilising a real datacube taken with the MUSE instrument at the ESO Very Large Telescope.
E. Herenz and L. Wisotzki
Thu, 16 Mar 17
Comments: 14 pages. Accepted for publication in Astronomy & Astrophysics. The LSDCat software is available at this https URL