WARP：WINERED光谱仪的数据缩减流水线
WARP: The Data Reduction Pipeline for the WINERED spectrograph
AI总结：
本文介绍了用于WINERED近红外光谱仪的Python数据缩减流水线WARP，包含定标和科学两种模式，能高效高质量提取光谱并支持实时查看。
摘要：
我们介绍了一个用Python编写的数据缩减流水线，用于处理近红外交叉色散阶梯光栅光谱仪WINERED获取的数据。该光谱仪根据观测模式不同，可生成0.91至1.35 $μ$m波段、分辨率为$R_{\text{max}} \equiv λ/ Δλ= 28,000$或70,000的光谱。开发该流水线旨在从原始数据中高效、高质量地提取光谱。它包含两种模式：定标模式和科学模式。定标模式可根据一组定标数据自动生成平场图像、坏像素图、阶梯光栅图畸变图和色散解。利用定标图像和参数，可通过科学模式自动缩减天体的科学数据。科学模式还可用于观测期间对数据进行实时快速查看。本文展示了使用WARP缩减的光谱示例，并讨论了高度倾斜的狭缝图像对光谱分辨率的影响。
英文摘要：
We present a data reduction pipeline written in Python for data obtained with the near-infrared cross-dispersed echelle spectrograph, WINERED, which yields a 0.91$-$1.35 $μ$m spectrum with the resolving power of $R_{\text{max}} \equiv λ/ Δλ= 28,000$ or 70,000 depending on the observing mode. The pipeline was developed to efficiently extract the spectrum from the raw data with high quality. It comprises two modes: the calibration and the science mode. The calibration mode automatically produces the flat-fielding image, bad pixel map, echellogram distortion map and the dispersion solution from the set of the calibration data. Using calibration images and parameters, the science data of astronomical objects can be reduced automatically using the science mode. The science mode is also used for the real-time quick look at the data during observations. An example of the spectra reduced with WARP is presented. The effect of the highly inclined slit image on the spectral resolution is discussed.
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