A full implementation of spectro-perfectionism for precise radial velocity exoplanet detection: A test case with the MINERVA reduction pipeline

  • Matthew A. Cornachione
  • , Adam S. Bolton
  • , Jason D. Eastman
  • , Maurice L. Wilson
  • , Sharon X. Wang
  • , Samson A. Johnson
  • , David H. Sliski
  • , Nate McCrady
  • , Jason T. Wright
  • , Peter Plavchan
  • , John Asher Johnson
  • , Jonathan Horner
  • , Robert A. Wittenmyer

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

We present a computationally tractable implementation of spectro-perfectionism, a method which minimizes error imparted by spectral extraction. We develop our method in conjunction with a full raw reduction pipeline for the MINiature Exoplanet Radial Velocity Array (MINERVA), capable of performing both optimal extraction and spectro-perfectionism. Although spectro-perfectionism remains computationally expensive, our implementation can extract a MINERVA exposure in approximately 30 minutes. We describe our localized extraction procedure and our approach to point-spread function (PSF) fitting. We compare the performance of both extraction methods on a set of 119 exposures on HD 122064, an RV standard star. Both the optimal extraction and spectroperfectionism pipelines achieve nearly identical RV precision under a six-exposure chronological binning. We discuss the importance of reliable calibration data for PSF fitting and the potential of spectro-perfectionism for future precise radial velocity exoplanet studies.

Original languageEnglish
Article number124503
JournalPublications of the Astronomical Society of the Pacific
Volume131
Issue number1006
DOIs
StatePublished - Dec 2019

Funding

Funding for MINERVA data-analysis software development is provided through a subaward under NASA award MT-13-EPSCoR-0011. M.A.C. acknowledges support from the National Science Foundation under grant AST-1614018. MINERVA is a collaboration among the Harvard-Smithso-nian Center for Astrophysics, The Pennsylvania State University, the University of Montana, and the University of Southern Queensland. MINERVA is made possible by generous contributions from its collaborating institutions and Mt. Cuba Astronomical Foundation, The David & Lucile Packard Foundation, National Aeronautics and Space Administration (EPSCOR grant NNX13AM97A), The Australian Research Council (LIEF grant LE140100050), and the National Science Foundation (grants 1516242 and 1608203). Any opinions, findings, and conclusions or recommendations expressed are those of the author and do not necessarily reflect the views of the National Science Foundation.

FundersFunder number
LE140100050
AST-1614018, 1516242, 1608203
David and Lucile Packard Foundation
National Aeronautics and Space AdministrationMT-13-EPSCoR-0011
NNX13AM97A
Australian Research Council

    Keywords

    • Planets and satellites: Detection
    • Techniques: Image processing
    • Techniques: Radial velocities
    • Techniques: Spectroscopic

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