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- Cruzalebes, P., et al.
(author)
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SPIDAST : a new modular software to process spectrointerferometric measurements
- 2013
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In: Monthly notices of the Royal Astronomical Society. - : Oxford University Press (OUP). - 0035-8711 .- 1365-2966. ; 432:2, s. 1658-1671
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Journal article (peer-reviewed)abstract
- Extracting stellar fundamental parameters from Spectrointerferometric (SPI) data requires reliable estimates of observables and with robust uncertainties (visibility, triple product, phase closure). A number of fine calibration procedures are necessary throughout the reduction process. Testing departures from centrosymmetry of brightness distributions is a useful complement. Developing a set of automatic routines called spidast (made available to the community) to reduce, calibrate and interpret raw data sets of instantaneous spectrointerferograms at the spectral channel level, we complement (and in some respects improve) the ones contained in the amdlib Data Reduction Software. Our new software spidast is designed to work in an automatic mode, free from subjective choices, while being versatile enough to suit various processing strategies. spidast performs the following automated operations: weighting of non-aberrant SPI data (visibility, triple product), fine spectral calibration (subpixel level), accurate and robust determinations of stellar diameters for calibrator sources (and their uncertainties as well), correction for the degradations of the interferometer response in visibility and triple product, calculation of the centrosymmetry parameter from the calibrated triple product, fit of parametric chromatic models on SPI observables, to extract model parameters. spidast is currently applied to the scientific study of 18 cool giant and supergiant stars, observed with the VLTI/AMBER facility at medium resolution in the K band. Because part of their calibrators have no diameter in the current catalogues, spidast provides new determinations of the angular diameters of all calibrators. Comparison of spidast final calibrated observables with amdlib determinations shows good agreement, under good and poor seeing conditions.
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