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The detection of mJy/sub-mJy point sources is a significant challenge for single-dish radio telescopes. Detection or upper limits on the faint afterglow from GRBs or other sources at cosmological distances are important means of constraining the source modeling. Using the Sardinia Radio Telescope (SRT), we compare the sensitivity and robustness of three methods applied to the detection of faint radio sources from raster maps around a known source position: the smart quick-look method, the source extraction method (typical of high-energy astronomy), and the fit with a 2-D Gaussian. We developed a Python code specific for the analysis of point-like radio sources applied to the SRT C-band (6.9 GHz) observations of both undetected sources (GRB afterglows of 181201A and 190114C) and the detected Galactic X-ray binary GRS 1915+105. Our comparative analysis of the different detection methods made extensive use of simulations as a useful complement to actual radio observations. The best method for the SRT data analysis is the fit with a 2-D Gaussian, as it pushes down the sensitivity limits of single-dish observations -- with respect to more traditional techniques -- to ~ 1.8 mJy, improving by ~ 40 % compared with the initial value. This analysis shows that -- especially for faint sources -- good maps of the scanned region pre- or post-outburst are essential.
The Virtual Observatory (VO) is becoming the de-facto standard for astronomical data publication. However, the number of radio astronomical archives is still low in general, and even lower is the number of radio astronomical data available through th
The study of the linear and circular polarization in AGN allows one to gain detailed information about the properties of the magnetic fields in these objects. However, especially the observation of circular polarization (CP) with single-dish radio-te
All the effort that the astrophysical community has put into the development of the Virtual Observatory (VO) has surpassed the non-return point: the VO is a reality today, and an initiative that will self-sustain, and to which all archival projects m
For submillimeter spectroscopy with ground-based single-dish telescopes, removing noise contribution from the Earths atmosphere and the instrument is essential. For this purpose, here we propose a new method based on a data-scientific approach. The k
We present a single-dish mapping algorithm with a number of advantages over traditional techniques. (1) Our algorithm makes use of weighted modeling, instead of weighted averaging, to interpolate between signal measurements. This smooths the data, bu