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.
@article{arxiv.1703.05166,
title = {LSDCat: Detection and cataloguing of emission-line sources in integral-field spectroscopy datacubes},
author = {Edmund Christian Herenz and Lutz Wisotzki},
journal= {arXiv preprint arXiv:1703.05166},
year = {2017}
}
Comments
14 pages. Accepted for publication in Astronomy & Astrophysics. The LSDCat software is available at https://bitbucket.org/Knusper2000/lsdcat, v2 corrected typos and language editing