CONSTRUCTING POLYNOMIAL SPECTRAL MODELS for STARS

Yuan Sen Ting, Hans Walter Rix, Charlie Conroy, David W. Hogg

    Research output: Contribution to journalArticle

    Abstract

    Stellar spectra depend on the stellar parameters and on dozens of photospheric elemental abundances. Simultaneous fitting of these no 1040 model labels to observed spectra has been deemed unfeasible because the number of ab initio spectral model grid calculations scales exponentially with n . We suggest instead the construction of a polynomial spectral model (PSM) of order for the model flux at each wavelength. Building this approximation requires a minimum of only &N& calculations: e.g., a quadratic spectral model (∂ = 2) to fit N = 20 labels simultaneously can be constructed from as few as 231 ab initio spectral model calculations; in practice, a somewhat larger number (3001000) of randomly chosen models lead to a better performing PSM. Such a PSM can be a good approximation only over a portion of label space, which will vary case-by-case. Yet, taking the APOGEE survey as an example, a single quadratic PSM provides a remarkably good approximation to the exact ab initio spectral models across much of this survey: for random labels within that survey the PSM approximates the flux to within 10?3 and recovers the abundances to within 0.02 dex rms of the exact models. This enormous speed-up enables the simultaneous many-label fitting of spectra with computationally expensive ab initio models for stellar spectra, such as non-LTE models. A PSM also enables the simultaneous fitting of observational parameters, such as the spectrums continuum or line-spread function.

    Original languageEnglish (US)
    Article numberL25
    JournalAstrophysical Journal Letters
    Volume826
    Issue number2
    DOIs
    StatePublished - Aug 1 2016

    Keywords

    • Methods: Data analysis
    • Stars: Abundances
    • Stars: Atmospheres
    • Techniques: Spectroscopic

    ASJC Scopus subject areas

    • Astronomy and Astrophysics
    • Space and Planetary Science

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