firefly (Fitting IteRativEly For Likelihood analYsis): a full spectral fitting code

Abstract We present a new spectral fitting code, firefly, for deriving the stellar population properties of stellar systems. firefly is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting...

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Veröffentlicht in:Monthly notices of the Royal Astronomical Society 2017-12, Vol.472 (4), p.4297-4326
Hauptverfasser: Wilkinson, David M., Maraston, Claudia, Goddard, Daniel, Thomas, Daniel, Parikh, Taniya
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Sprache:eng
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Zusammenfassung:Abstract We present a new spectral fitting code, firefly, for deriving the stellar population properties of stellar systems. firefly is a chi-squared minimization fitting code that fits combinations of single-burst stellar population models to spectroscopic data, following an iterative best-fitting process controlled by the Bayesian information criterion. No priors are applied, rather all solutions within a statistical cut are retained with their weight. Moreover, no additive or multiplicative polynomials are employed to adjust the spectral shape. This fitting freedom is envisaged in order to map out the effect of intrinsic spectral energy distribution degeneracies, such as age, metallicity, dust reddening on galaxy properties, and to quantify the effect of varying input model components on such properties. Dust attenuation is included using a new procedure, which was tested on Integral Field Spectroscopic data in a previous paper. The fitting method is extensively tested with a comprehensive suite of mock galaxies, real galaxies from the Sloan Digital Sky Survey and Milky Way globular clusters. We also assess the robustness of the derived properties as a function of signal-to-noise ratio (S/N) and adopted wavelength range. We show that firefly is able to recover age, metallicity, stellar mass, and even the star formation history remarkably well down to an S/N ∼ 5, for moderately dusty systems. Code and results are publicly available.1
ISSN:0035-8711
1365-2966
DOI:10.1093/mnras/stx2215