论文标题
重新访问整体场光谱数据中的排放线源检测问题
Revisiting the Emission Line Source Detection Problem in Integral Field Spectroscopic Data
论文作者
论文摘要
我们提出了一种三维匹配的过滤方法，用于在整体场光谱数据集中对微弱的发射线源进行盲目搜索。该过滤器的设计是为了考虑由于耗Wk的空光光谱而引起的频谱迅速变化的背景噪声。该匹配的过滤搜索的软件实现是在线路源检测目录工具（LSDCAT2.0）的更新版本中实现的。使用Muse范围的调查中的公共数据，我们显示了新的过滤器设计如何为埋在大气中的微弱发射线来源[oh] - bands $λ\ gtrsim 7000 $ \，Å提供更高的检测意义。我们还展示了如何，对于给定的源参数化，改进算法的选择函数可以从数据方差分析得出。我们在最近发布的Muse深度领域（MXDF）的数据集中验证了针对来源插入和恢复实验的分析解决方案。然后，我们说明如何将选择函数重新缩放到与模板不完全一致的3D发射线源配置文件中。该过程通过消除对计算繁琐的源插入和恢复实验的需求来减轻现实选择功能的构建。
We present a 3-dimensional matched filtering approach for the blind search of faint emission-line sources in integral-field spectroscopic datasets. The filter is designed to account for the spectrally rapidly varying background noise due to the telluric air glow spectrum. A software implementation of this matched filtering search is implemented in an updated version of the Line Source Detection Cataloguing tool (LSDCat2.0). Using public data from the MUSE-Wide survey we show how the new filter design provides higher detection significances for faint emission line sources buried in between atmospheric [OH]-bands at $λ\gtrsim 7000$\,Å. We also show how, for a given source parameterisation, the selection function of the improved algorithm can be derived analytically from the variances of the data. We verify this analytic solution against source insertion and recovery experiments in the recently released dataset of the MUSE eXtreme Deep Field (MXDF). We then illustrate how the selection function has to be re-scaled for 3D emission line source profiles that are not fully congruent with the template. This procedure alleviates the construction of realistic selection functions by removing the need for computationally cumbersome source insertion and recovery experiments.
