The Data Reduction Pipeline for the Apache Point Observatory Galactic Evolution Experiment
David L. Nidever, Jon A. Holtzman, Carlos Allende Prieto, Stephane, Beland, Chad Bender, Dmitry Bizyaev, Adam Burton, Rohit Desphande, Scott W., Fleming, Ana Elia Garcia Perez, Fred R. Hearty, Steven R. Majewski, Szabolcs, Meszaros, Demitri Muna, Duy Nguyen, Ricardo P. Schiavon

TL;DR
The paper details the data reduction pipeline for APOGEE, a survey that captures high-resolution near-infrared spectra of over 150,000 stars to study the Milky Way's stellar populations.
Contribution
It introduces the software pipeline that processes raw APOGEE data into calibrated spectra, addressing challenges like sky subtraction and telluric correction.
Findings
Processed over 150,000 stellar spectra with high S/N ratios.
Achieved radial velocity accuracy of ~0.1 km/s.
Provided detailed chemical abundances for multiple elements.
Abstract
The Apache Point Observatory Galactic Evolution Experiment (APOGEE), part of the Sloan Digital Sky Survey III, explores the stellar populations of the Milky Way using the Sloan 2.5-m telescope linked to a high resolution (R~22,500), near-infrared (1.51-1.70 microns) spectrograph with 300 optical fibers. For over 150,000 predominantly red giant branch stars that APOGEE targeted across the Galactic bulge, disks and halo, the collected high S/N (>100 per half-resolution element) spectra provide accurate (~0.1 km/s) radial velocities, stellar atmospheric parameters, and precise (~0.1 dex) chemical abundances for about 15 chemical species. Here we describe the basic APOGEE data reduction software that reduces multiple 3D raw data cubes into calibrated, well-sampled, combined 1D spectra, as implemented for the SDSS-III/APOGEE data releases (DR10, DR11 and DR12). The processing of the near-IR…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
