The Spectroscopic Data Processing Pipeline for the Dark Energy Spectroscopic Instrument

TL;DR

The paper details the DESI spectroscopic data processing pipeline, which efficiently produces calibrated spectra and accurate redshifts for millions of celestial objects, supporting precise cosmological measurements.

Contribution

It introduces a comprehensive data pipeline for DESI, demonstrating high efficiency, stability, and accuracy in processing large-scale spectroscopic data for cosmology.

Findings

Pipeline achieves >99% purity in target classification

Processed data available by the next morning

Pipeline exceeds redshift accuracy requirements

Abstract

We describe the spectroscopic data processing pipeline of the Dark Energy Spectroscopic Instrument (DESI), which is conducting a redshift survey of about 40 million galaxies and quasars using a purpose-built instrument on the 4-m Mayall Telescope at Kitt Peak National Observatory. The main goal of DESI is to measure with unprecedented precision the expansion history of the Universe with the Baryon Acoustic Oscillation technique and the growth rate of structure with Redshift Space Distortions. Ten spectrographs with three cameras each disperse the light from 5000 fibers onto 30 CCDs, covering the near UV to near infrared (3600 to 9800 Angstrom) with a spectral resolution ranging from 2000 to 5000. The DESI data pipeline generates wavelength- and flux-calibrated spectra of all the targets, along with spectroscopic classifications and redshift measurements. Fully processed data from each night are typically available to the DESI collaboration the following morning. We give details about the pipeline's algorithms, and provide performance results on the stability of the optics, the quality of the sky background subtraction, and the precision and accuracy of the instrumental calibration. This pipeline has been used to process the DESI Survey Validation data set, and has exceeded the project's requirements for redshift performance, with high efficiency and a purity greater than 99 percent for all target classes.