Tools for data-driven spectra models with Gaussian processes. Pronounced "soap."
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attic Simplified orbit files. Jun 13, 2017


Pronounced "soap."

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Precision Spectroscopic Orbits A-Parametrically

PSOAP is a package for simultaneously inferring stellar (and/or exoplanet) orbits and stellar spectra using Gaussian processes. Some uses include:

  • Fitting for radial velocities in a template-free manner
  • Inferring orbits of single-lined spectroscopic binaries (e.g., exoplanets/their host stars)
  • Generation of high-fidelity stellar templates (for use with traditional RV cross-correlation measurements, variability searches)
  • Inferring orbits and spectra of double-lined spectroscopic binaries (see gif below)

Documentation and installation instructi ons are available at

disentangling loop

If you use our paper, code, or a derivative of it in your research, we would really appreciate a citation to Czekala et al. 2017:

    author = {{Czekala}, I. and {Mandel}, K.~S. and {Andrews}, S.~M. and {Dittmann}, J.~A. and
    {Ghosh}, S.~K. and {Montet}, B.~T. and {Newton}, E.~R.},
    title = "{Disentangling Time-series Spectra with Gaussian Processes: Applications to Radial Velocity Analysis}",
    journal = {\apj},
    archivePrefix = "arXiv",
    eprint = {1702.05652},
    primaryClass = "astro-ph.SR",
    keywords = {binaries: spectroscopic, celestial mechanics, stars: fundamental parameters, stars: individual: LP661-13, techniques: radial velocities, techniques: spectroscopic},
     year = 2017,
    month = may,
    volume = 840,
      eid = {49},
    pages = {49},
      doi = {10.3847/1538-4357/aa6aab},
    adsurl = {},
    adsnote = {Provided by the SAO/NASA Astrophysics Data System}

Copyright Ian Czekala and collaborators 2016-17.

Papers using PSOAP

  • Disentangling Time-series Spectra with Gaussian Processes: Applications to Radial Velocity Analysis, Czekala et al. 2017
  • The Architecture of the GW Ori Young Triple Star System and Its Disk: Dynamical Masses, Mutual Inclinations, and Recurrent Eclipses, Czekala et al. 2017