Overview of the NEID-DRP

Data Handling

The NEID Data Reduction Pipeline (NEID-DRP) processes data obtained with the NEID Precision Radial Velocity Spectrometer at 3.5 m WIYN Observatory on Kitt Peak.

Three levels of data products are generated:

  • Level 0: Raw data produced by the NEID instrument control system at the WIYN observatory

  • Level 1: Extracted, wavelength calibrated spectra

  • Level 2: Derived products, including radial velocites, activity indicators, and telluric models

NEID GTO and GO data is obtained at night by professional observers operating the spectrometer in a Queue based mode.

During daytime hours, from 9:30 to 15:30 MST, the spectrograph uses its solar telescope feed to automatically obtain a continuous stream of solar spectra, with a cadence of 55 s/exposure, followed by ~30 s of readout.

Calibration data is primarily obtained in two large blocks each day from 16:00 - 18:30 MST, and from 6:30 - 9:00 MST. Data transfers automatically from Kitt Peak to NExScI twice per day, following completion of these calibration seqeuences. After arrival at NExScI, validation checks are performed to ensure data integrity, and the data is ingested into the NExScI archive.

Pipeline Runs

Data is processed by NExScI as either a night or a day packet. Each packet includes the before and after bracketing calibration sequences and all of the science frames obtained between them. Several locations in this documentation refer to this night or day/solar processing. There is no option in the current implementation of the NEID-DRP to process a single frame, because several pipeline calibration steps (e.g., flat fielding, wavelength calibration) are designed around the concept of a time series of calibrations, and depend on this time series to provide the highest quality output. Each processing run generates Level 1 and Level 2 data products, which are ingested into the NExScI archive and distributed to PIs through various NExScI frontends.

The NEID-SpecSoft Team

The NEID-DRP was created by the following individuals:

  • Chad Bender, University of Arizona, NEID Software Lead

  • Joe Ninan, Tata Institute of Fundamental Research

  • Ryan Terrien, Carleton College

  • Arpita Roy, Schmidt Futures

  • Daniel Krolikowski, University of Arizona

  • Leonardo Paredes, University of Arizona

  • Taran Esplin, University of Arizona

  • Sam Halverson, JPL

  • Kyle Kaplan, University of Arizona

  • Caleb Canas, NASA Goddard

  • Noah Rivera, Cal Poly San Luis Obispo

  • Gudmundur Stefansson, Princeton University

  • Shubham Kanodia, Carnegie

  • Andrea Lin, Penn State University

  • Sai Krishanth Pulikesi Mannan, University of Arizona

  • Jacob Luhn, University of California, Irvine

For questions regarding pipeline algorithms or data products, contact cbender@arizona.edu

Last Updated: 2023-08-30, CFB