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

TL;DR

This paper introduces an enhanced data reduction pipeline for Keck/NIRSPEC, integrated into PypeIt, enabling improved calibration, telluric correction, and spectrum coaddition for high-resolution infrared data.

Contribution

The paper presents major improvements to PypeIt, including manual wavelength calibration and order-by-order coadded spectra, tailored for Keck/NIRSPEC data post-2018 upgrade.

Findings

Effective telluric correction using standard star spectra.

Accurate wavelength calibration for multi-order data.

Coadded spectra produced order-by-order with high fidelity.

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.