高分辨率光谱学的夜空发射校正技术：以NIRPS为例的演示
Night-sky emission correction techniques for high-resolution spectroscopy: Demonstration with NIRPS
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中文总结 AI 辅助
本文开发的夜空发射校正算法已集成到NIRPS两套数据处理管道，可提升高分辨率光谱仪的径向速度测量精度，使NIRPS在近红外波段实现亚米每秒精度。
中文摘要 AI 辅助
近红外（NIR）波段的地面光谱仪受地球大气的多种吸收和发射特征干扰。尽管人们已投入大量精力消除大气吸收，但校正大气发射特征仍非易事，且会显著影响对暗弱目标的观测。我们旨在开发并实现适用于高分辨率光谱学的自动天空背景发射校正算法。这些基于经验的算法已正式集成到NIRPS的两套数据处理管道：NIRPS DRS和APERO DRS中。这些技术设计具有灵活性，可整合到任何高分辨率光谱仪的处理流程中，以提升径向速度（RV）性能。我们的方法为：首先，通过在公共波长网格上深度叠加NIRPS的天空校准帧，分别针对高精度和高效率仪器模式，计算每个像素的加权中值流量，创建参考天空光谱。该过程对所有光谱级次以及目标光纤A和天空校准光纤B重复执行。在该参考天空光谱中，可识别出天空发射线并用于构建静态库。在数据处理过程中，利用两种不同技术，针对两套DRS管道分别对库中的发射特征按流量进行单独缩放。最后，将这些特征从科学观测中局部减去，以最小化其噪声对最终光谱的影响。我们发现，该校正算法可显著提升使用互相关函数和逐线技术获得的RV测量结果，使NIRPS在近红外波段实现亚米每秒的精度。这些技术已成功得到验证和演示。
英文摘要
Ground-based spectrographs operating in the near-infrared (NIR) regime are hampered by various absorption and emission features of Earth's atmosphere. While considerable attention has been paid to mitigating telluric absorption, correcting telluric emission features remains non-trivial and can significantly affect the observation of faint targets. We aim to develop and implement automated algorithms for sky background emission correction in the context of high-resolution spectroscopy. These empirical-based algorithms have been officially integrated into both NIRPS data reduction pipelines: NIRPS DRS and APERO DRS. Designed for flexibility, these techniques can be incorporated into the reduction workflow of any high-resolution spectrograph to improve the radial velocity (RV) performance. In our approach, a reference sky spectrum is first created by deep-stacking NIRPS sky calibration frames on a common wavelength grid and calculating the weighted median flux per pixel, separately for both the high-accuracy and high-efficiency instrument modes. This process is repeated for all spectral orders and for both the object and sky-calibration fibres: fibre A and fibre B, respectively. In this reference sky spectrum, the sky emission lines can be identified and used to construct a static library. During the data reduction process, the emission features in the library are individually scaled in terms of flux using two distinct techniques, each specific to the two DRS pipelines. Finally, they are locally subtracted from the science observations to minimise their noise contribution to the final spectrum. We find that the correction algorithms significantly improve the RV measurements obtained using both the cross-correlation function and line-by-line techniques, enabling NIRPS to achieve submetre-per-second precision in the NIR. The techniques have been successfully validated and demonstrated.
发表机构
- Institut Trottier de recherche sur les exoplanètes, Département de Physique, Université de Montréal（蒙特利尔大学特罗蒂尔系外行星研究研究所）
- Observatoire de Genève, Département d’Astronomie, Université de Genève（日内瓦大学天文学系天文台）
- Observatoire du Mont-Mégantic（梅格antic山天文台）
- Instituto de Astrofísica e Ciências do Espaço, Universidade do Porto, CAUP（波尔图大学空间与天体物理研究所）
- Departamento de Física e Astronomia, Faculdade de Ciências, Universidade do Porto（波尔图大学理学院物理与天文学系）
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