Automated derivation of stellar atmospheric parameters and chemical abundances: the MATISSE algorithm

By A. Recio-Blanco, A. Bijaoui, P. Laverny. 2006

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We present an automated procedure for the derivation of atmospheric parameters (T eff , log g, [M/H]) and individual chemical abundances from stellar spectra. The MATrix Inversion for Spectral SynthEsis (MATISSE) algorithm determines a basis, B θ (λ), allowing the derivation of a particular stellar parameter θ by projection of an observed spectrum. The Be(>.) function is determined from an optimal linear combination of theoretical spectra and it relates, in a quantitative way, the variations in the spectrum flux with variations in 6. An application of this method to the Gaia Radial Velocity Spectrograph spectral range is described, together with its performances for different types of stars of various metallicities. Blind tests with synthetic spectra of randomly selected parameters and observed input spectra are also presented. The method gives rapid, accurate and stable results and it can be efficiently applied to the study of stellar populations through the analysis of large spectral data sets, including moderate to low signal-to-noise ratio spectra.

Subfields: Astronomy and Astrophysics, Instrumentation, Statistical and Nonlinear Physics

View Paper: https://www.semanticscholar.org/paper/f45a7b6481bfb71f5454c11ee54d92caa0e648eb

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Citations in the corpus

Gaia FGK benchmark stars: Metallicity (2013, methodology): “…for Spectrum SynthEsis) which has been developed at the Observatoire de la Côte d’Azur primarily for use in Gaia RVS4 stellar parameterization pipeline (Recio-Blanco et al. 2006), but also for largescale projects such as AMBRE (Worley et al. 2012; de Laverny et al. 2012) and the Gaia-ESO Survey.”
THE CANNON: A DATA-DRIVEN APPROACH TO STELLAR LABEL DETERMINATION (2015, methodology): “The Cannon is similar to the MATrix Inversion for Spectral SythEsis (MATISSE) pro- cedure for derivation of stellar parameters (Recio-Blanco et al. 2006) in that it uses the full spectrum (and not just a line list) for label determination.”
The Gaia-ESO Survey: the analysis of high-resolution UVES spectra of FGK-type stars (2014, methodology): “…algorithm MATISSE (MATrix Inversion for Spectrum SynthEsis), developed at the Observatoire de la Côte d’Azur primarily for use in the Gaia RVS (Radial Velocity Spectrometer) stellar parametrization pipeline (Recio-Blanco et al. 2006), and the Gaia-ESO synthetic spectrum grid (see Sect.”
Estimating stellar birth radii and the time evolution of Milky Way’s ISM metallicity gradient (2018, methodology): “Stellar parameters are derived using the MATISSE algorithm (Recio-Blanco et al. 2006), as described in De Pascale et al. (2014).”
Automatic determination of stellar atmospheric parameters and construction of stellar spectral templates of the Guoshoujing Telescope (LAMOST) (2011, methodology): “There are many other typical works in this category, including Zwitter et al. (2005), MATISSE (Recio-Blanco et al. 2006), Allende Prieto et al. (2006), Shkedy et al. (2007), Jofŕe et al. (2010), as well as the SSPP (Lee et al. 2008a), in whicht ey employed various techniques in integrated…”
Coudé-feed stellar spectral library – atmospheric parameters (2010, background): “Other similar efforts include Bailer-Jones et al. (1997), Prugniel & Soubiran (2001), Snider et al. (2001), Willemsen et al. (2005), Recio-Blanco et al. (2006), Shkedy et al. (2007), Luo et al. (2008), Lefever et al. (2010), Zhang et al. (2009) and Jofré et al. (2010).”