Large Binocular Telescope

Abstract

Some of the new giant ground-bases telescopes will be equipped with interferometric systems, so that multiple images of the same target, corresponding to different orientations of the baseline, will be available. These interferometric images will need specific processing to provide a unique high resolution image of the target.In this thesis we consider the case of the Large Binocular Telescope (LBT) which is currently under construction on the top of Mount Graham in Arizona and will be equipped with a Fizeau interferometer with a baseline of 22.8m. From the point of view of image reconstruction, the interesting feature is that LINC/NIRVANA (the Fizeau interferometer for LBT) will require routinely the use of multiple image deconvolution methods to produce a unique image with the resolution of a 22.8m telescope.The aim of the thesis is to investigate the extension of existing reconstruction methods to the problem of multiple image deconvolution, to optimize their use and to propose and develop new methods in order to face problems not yet solved.In this sense we find out that two classes of deconvolution methods with different characteristics may be needed:-quick-look methods, computationally efficient even if not always very accurate, to be routinely used for a preliminary view of the target just after data acquisition; -ad hoc methods, designed for specific classes of astronomical objects, which can be computationally expensive but must be accurate as far as possible for all the objects in a given class.Therefore the processing of LINC/NIRVANA images will in general require two steps: the first, based on a quick-look method, is intended to identify the specific features of the particular object the astronomer is observing; the second consists in the use of the ad hoc method which has been designed for the objects with those specific features.In the case of quick-look methods we develop acceleration techniques of the OS-EM (Ordered Subsets Expectation Maximization) algorithm, allowing a reduction of the number of iterations without a significant increase of the computational cost per iteration. Moreover we investigate and implement the combination of the multi-images provided by LN into a single one to use single image deconvolution methods.For the second class of methods we propose and develop a method which is able to superresolve compact stellar objects such as a binary system with an angular separation smaller than the angular resolution of the telescope. Moreover we extend to the multiple image case a general approach, denoted as SGM (Split Gradient Method), and we use it for introducing a new method for the reconstruction of objects with a high dynamic range.All these methods are validated by means of extensive numerical simulations.Two general problems of image reconstruction are also investigated and solved. Indeed we propose a method for the reduction of the boundary effects (ripples) in the deconvolution of astronomical images. Moreover we develop a blind deconvolution method to be used when po...