The AIRY-LN software package for the LINC-NIRVANA interferometer of the Large Binocular Telescope (LBT): image reconstruction methods and simulations

The Large Binocular Telescope (LBT) currently nearing completion on Mount Graham in Arizona, will be the world’s largest optical and infrared telescope. The raw images obtained with LINC-NIRVANA (LN), the optical/NIR beam combiner of LBT, will have an anisotropic angular resolution: typical of an 8 meter class telescope in one axis, approximately 3 times better in the orthogonal one. If exposures are taken at different hour angles in order to obtain a better {u, v}-coverage, an aperture synthesis image reconstruction procedure can provide reconstructed images with the full angular resolution of a 22.8 m single-dish telescope in all directions. The goal of this thesis is to provide the official software needed by LN to perform image reconstruction by means of a collection of iterative methods. A first release of the software, namely ”AIRY-LN Software Package” (Astronomical Image Reconstruction in interferometrY for Linc Nirvana), has been developed and fully tested during the last three years. AIRY-LN (based on IDL, Interactive Data Language) has been conceived to be used in two different ways. The first is a ”light version” of the software, to be used through the IDL Virtual Machine (IDL-license is not required); this version provides some ”pre-edited” projects for pre-processing and deconvolution in which the astronomer has only to modify some parameters. The second is a ”full version” (IDL-license is needed), in which the astronomer can build his own project using a collection of modules, each one performing a specific task. Another basic topic of the thesis is the study of new deconvolution algorithms for the reconstruction of the LN images. Various kinds of ”regularizations” applied to the basic reconstruction algorithm (the so-called Ordered Subset Expectation Maximization OSEM) will be able to optimize the reconstructions for different kinds of astronomical targets. The proposed methods are first-order optimization methods based on a suitable decomposition of the gradient of the functional to be minimized. In particular efficient algorithms of the class of the scaled gradient projection (SGP) methods are investigated. Moreover, due to the large dimensions of the LN images (2048×2048 pixels) and the heavy computational costs of the regularized algorithm, it is clear that computational efficiency is an important issue. Therefore we also extend, to the proposed iterative algorithms, the acceleration methods introduced by Biggs & Andrews. In addition a method of blind deconvolution, able to improve PSF reconstruction (and hence the whole blind deconvolution process in order to obtain better reconstructed objects) has been studied and implemented using a priori information about the physical features of the PSF, such as the band in the domain used for the acquisition and/or the Strehl ratio (used in optical astronomy to characterize the image quality that is obtained after AO correction of the images ). Finally, the software has been used in a Simulation Project (funded by INAF), to verify the performance of the instrument LINC-NIRVANA for the observation of specific astronomical targets.