# LSDCat: Detection and cataloguing of emission-line sources in integral-field spectroscopy datacubes

## TL;DR

LSDCat is a Python software package that efficiently detects and catalogs faint emission-line sources in large 3D spectroscopic datacubes using a matched filter approach, suitable for instruments like MUSE.

## Contribution

The paper introduces LSDCat, a new robust, efficient, and user-friendly algorithm and software for detecting emission-line sources in integral-field spectroscopy datacubes, with a focus on large datasets.

## Key findings

- Successfully detects faint emission-line sources in real datacubes.
- Processes large datacubes quickly with minimal input parameters.
- Verifies detection accuracy through source insertion and recovery experiments.

## Abstract

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.