Monday, April 8, 2013

1304.1666 (Pierre Cruzalèbes et al.)

SPIDAST: a new modular software to process spectro-interferometric measurements    [PDF]

Pierre Cruzalèbes, Yves Rabbia, Alain Jorissen, Alain Spang, Stéphane Sacuto, Ester Pasquato, Andrea Chiavassa, Olivier Chesneau, Patrick Fréville
Extracting stellar fundamental parameters from SPectro-Interferometric (SPI) data requires reliable estimates of observables and with robust uncertainties (visibility, triple product, phase closure). A number of fine calibration procedures is necessary throughout the reduction process. Testing departures from centro-symmetry 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 spectro-interferograms 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 (sub-pixel 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 Centro-Symmetry Parameter (CSP) 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 catalogs, 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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