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arXiv · 2410.19991

Robust support for semi-automated reductions of Keck/NIRSPEC data using PypeIt

Adolfo S. Carvalho·Greg Doppmann·Kyle B. Westfall·Debora Pelliccia·J. Xavier Prochaska·Joseph Hennawi·Frederick B. Davies·Max Brodheim·Feige Wang·Ryan Cooke
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Abstract

We present a data reduction pipeline (DRP) for Keck/NIRSPEC built as an addition to the PypeIt Python package. The DRP is capable of reducing multi-order echelle data taken both before and after the detector upgrade in 2018. As part of developing the pipeline, we implemented major improvements to the capabilities of the PypeIt package, including manual wavelength calibration for multi-order data and new output product that returns a coadded spectrum order-by-order. We also provide a procedure for correcting telluric absorption in NIRSPEC data by using the spectra of telluric standard stars taken near the time of the science spectra. At high resolutions, this is often more accurate than modeling-based approaches.

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Adolfo S. Carvalho, Greg Doppmann, Kyle B. Westfall, Debora Pelliccia, J. Xavier Prochaska, Joseph Hennawi, Frederick B. Davies, Max Brodheim, Feige Wang, Ryan Cooke. 2024-10-25. Robust support for semi-automated reductions of Keck/NIRSPEC data using PypeIt. https://arxiv.org/abs/2410.19991

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