Saoimage ds9 gaussian6/4/2023 ![]() ![]() These areas have to be inferior to the beam size (typically 1/4-1/5 of HPBW) in order to avoid discarding actual fluctuations from the source, but large enough so that they include a significant (typically >10) number of measurements. Meanwhile, we provided an efficient automated ‘spatial RFI flagging’ procedure that consists in splitting the map into sub-regions, which correspond to adjacent solid angles in the sky. In the next future, when a Roach-based spectro-polarimetric backend will be available also at Medicina, this will be the most effective method for RFI removal. A ‘spectral RFI flagging’ based on automated search for outliers in each scan-sample’s spectrum is available for SRT, but it is not possible when observing with 'Total-Intensity backends'. Our data analysis pipeline involves the following major steps/procedures: The core of our procedure is to fully exploit the availability of a significant number of measurements per beam (and then per pixel, typically chosen to be about 1/4 of the Half Power Beam Width), in order to have a straightforward evaluation of statistical errors (through standard deviation of the measurements in each pixel), efficient RFI (Radio Frequency Interferencies) outliers removal and accurate background baseline subtraction. SDI generates SAOImage DS9 ( ) output FITS images suited to further analysis by standard astronomy tools. Our scientific data products rely on calibrated brightness images of the Sun atmosphere in K-band typically taken up to 0.7 degrees from the solar centroid ephemeris.ĭata analysis is performed using the SRT Single-Dish Imager (SDI), which is a tool designed to perform continuum and spectro-polarimetric imaging, optimized for On-the-fly (OTF) scan mapping, and suitable for most receivers/backends available for INAF radio-telescopes (see details e.g. ![]()
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