摘要：Understanding the complex dynamics and structure of the upper solar atmosphere strongly benefits from the use of a combination of several diagnostics. Frequently, such diverse diagnostics can only be obtained from telescopes and/or instrumentation operating at widely different spatial resolution. To optimize the utilization of such data, we propose a new method for the global inversion of data acquired at different spatial resolution. The method has its roots in the Levenberg-Marquardt algorithm but involves the use of linear operators to transform and degrade the synthetic spectra of a highly resolved guess model to account for the effects of spatial resolution, data sampling, alignment, and image rotation of each of the datasets. We have carried out a list of numerical experiments to show that our method allows for the extraction of spatial information from two simulated datasets that have gone through two different telescope apertures and that are sampled in different spatial grids. Our results show that each dataset contributes in the inversion by constraining information at the spatial scales that are present in each of the datasets, and no negative effects are derived from the combination of multiple resolution data. This method is especially relevant for chromospheric studies that attempt to combine datasets acquired with different telescopes and/or datasets acquired at different wavelengths. The techniques described in the present study will also help to address the ever increasing resolution gap between space-borne missions and forthcoming ground-based facilities.
关键词：entechniques: high angular resolutionradiative transferpolarizationSun: magnetic fieldsSun: chromosphere
