Abstract
DBSP_DRP is a python package that provides fully automated data reduction of data taken by the Double Spectrograph (DBSP) at the 200-inch Hale Telescope at Palomar Observatory (Oke & Gunn, 1982). The underlying data reduction functionality to extract 1D spectra, perform flux calibration and correction for atmospheric absorption, and coadd spectra together is provided by PypeIt (Prochaska et al., 2020). The new functionality that DBSP_DRP brings is in orchestrating the complex data reduction process by making smart decisions so that no user input is required after verifying the correctness of the metadata in the raw FITS files in a table-like GUI. Though the primary function of DBSP_DRP is to automatically reduce an entire night of data without user input, it has the flexibility for astronomers to fine-tune the data reduction with GUIs for manually identifying the faintest objects, as well as exposing the full set of PypeIt parameters to be tweaked for users with particular science needs. DBSP_DRP also handles some of the occasional quirks specific to DBSP, such as swapping FITS header cards, adding (an) extra null byte/s to FITS files making them not conform to the FITS specification, and not writing the coordinates of the observation to file. Additionally, DBSP_DRP contains a quicklook script for making real-time decisions during an observing run, and can open a GUI displaying a minimally reduced exposure in under 15 seconds. Docker containers are available for ease of deploying DBSP_DRP in its quicklook configuration (without some large atmospheric model files) or in its full configuration.
Highlights
The spectrum of light emitted from astrophysical sources is of great use, allowing astronomers to classify objects and measure their properties
To measure the spectrum of a source, astronomers use spectrographs, in which dispersive elements spatially separate the incoming light by wavelength, and detectors, most commonly CCDs, image this dispersed light
Many spectrographs have multiple paths that light can go through, and multiple detectors, each measuring a particular part of the spectrum, to increase the wavelength range that can be captured in a single exposure, or to allow the high resolution observation of distinct wavelength ranges
Summary
The spectrum of light emitted from astrophysical sources is of great use, allowing astronomers to classify objects and measure their properties. This process of converting 2D CCD images into 1D spectra is called data reduction. DBSP_DRP is a python package that provides fully automated data reduction of data taken by the Double Spectrograph (DBSP) at the 200-inch Hale Telescope at Palomar Observatory (Oke & Gunn, 1982).
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