Slitless Solar Spectroscopy

Abstract:

Spectrometers provide our most detailed diagnostics of the solar coronal plasma, and spectral data is routinely used to measure the temperature, density, and flow velocity of coronal features. However, spectrographs suffer from a limited instantaneous field-of-view (FOV). Imaging instruments can provide a large FOV but offer only very limited spectral resolution. In this work, we present an instrument concept that combines the strengths of these two instrument classes, i.e., a large FOV and high spectral resolution.

Our approach is based on computational imaging, which involves distributing the spectral imaging task between a physical and a computational system, and then digitally forming images of interest from multiplexed measurements by means of solving an inverse problem. In particular, a nonscanning spectral imaging technique is developed to enable performing spectroscopy over a two-dimensional instantaneous field-of-view. This technique combines a parametric estimation approach with a slitless spectrometer configuration. The associated inverse problem, which can be viewed as a multiframe image deblurring problem, is formulated in a Bayesian estimation framework and computationally efficient algorithms are designed to solve the resulting nonlinear optimization problems. Furthermore, statistical bounds are obtained to characterize the estimation uncertainties and performance limits, and to explore the optimized system design for specific observing requirements. We illustrate that such an instrument concept will facilitate the investigation of highly dynamic solar phenomena such as flares, CMEs, and transient brightening, with a significant reduction in hardware cost and complexity, but at an accuracy comparable with conventional designs.