IFS-RedEx，积分场摄谱仪的红移提取软件：对MUSE数据的应用
IFS-RedEx, a redshift extraction software for integral-field spectrographs: Application to MUSE data
摘要：
我们提出了IFS-RedEx，积分场光谱仪的光谱和红移提取管道。该工具的一个关键特征是基于小波的频谱清洁器。它识别可靠的光谱特征，重建它们的形状，并抑制光谱噪声。这使得该技术比传统方法（如高斯滤波）更具优势，后者只会模糊信号。因此，基于小波的清洗允许快速识别真实的光谱特征。我们使用降级的MUSE光谱测试了清洁技术，发现它可以检测到低至S/N = 8的光谱峰值，同时报告没有虚假检测。我们将IFS-RedEx应用于强透镜星系团MACSJ1931.8-2635的MUSE数据，提取了54个光谱红移。我们确定了29个星系团成员和22个背景星系，z >= 0.4。IFS-RedEx是开源的，可公开使用。
英文摘要：
We present IFS-RedEx, a spectrum and redshift extraction pipeline for integral-field spectrographs. A key feature of the tool is a wavelet-based spectrum cleaner. It identifies reliable spectral features, reconstructs their shapes, and suppresses the spectrum noise. This gives the technique an advantage over conventional methods like Gaussian filtering, which only smears out the signal. As a result, the wavelet-based cleaning allows the quick identification of true spectral features. We test the cleaning technique with degraded MUSE spectra and find that it can detect spectrum peaks down to S/N = 8 while reporting no fake detections. We apply IFS-RedEx to MUSE data of the strong lensing cluster MACSJ1931.8-2635 and extract 54 spectroscopic redshifts. We identify 29 cluster members and 22 background galaxies with z >= 0.4. IFS-RedEx is open source and publicly available.
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