LSDCat：积分场spectroscopy数据管中发射线源的探测和编目
LSDCat: Detection and cataloguing of emission-line sources in integral-field spectroscopy datacubes
摘要：
我们提出了一个强大的，高效的，用户友好的算法，用于检测微弱的发射线源在大型积分场光谱数据管连同软件包LSDCat（线源检测和编目）的公开发布。LSDCat使用3维匹配滤波器方法，结合信噪比阈值，构建单个线检测的目录。在第二遍中，将检测到的线分组为不同的对象，并且确定检测到的线的位置、空间范围和通量。LSDCat只需要少量的输入参数，我们提供了选择适当值的指导。该软件是用Python编写的，能够在短时间内处理非常大的数据立方体。我们验证的实施与源插入和恢复实验，利用一个真正的数据立方体采取的MUSE仪器在ESO甚大望远镜。
英文摘要：
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.
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