Computational image formation with photon sieves for milli arcsecond solar imaging

A photon sieve is a modification of a Fresnel zone plate in which open zones are replaced by a large number of circular holes. This diffractive imaging element is specially suited to observations at UV and x-ray wavelengths where refractive lenses are not available due to strong absorption of materials, and reflective mirrors are difficult to manufacture with sufficient surface figure accuracy to achieve diffraction-limited resolution. On the other hand, photon sieves enable diffraction-limited imaging with much more relaxed tolerances than conventional imaging technology. In this presentation, we present the capabilities of an instrument concept that is based on computational image formation with photon sieves. The instrument enables high-resolution spectral imaging by distributing the imaging task between a photon sieve system and a computational method. A photon sieve coupled with a moving detector provides measurements from multiple planes. Then computational image formation, which involves deconvolution, is performed in a Bayesian estimation framework to reconstruct the multi-spectral images from these measurements. In addition to diffraction-limited high spatial resolution enabled by photon sieves, this instrument can also achieve higher spectral resolution than the conventional spectral imagers, since the technique offers the possibility of separating nearby spectral components that would not otherwise be possible using wavelength filters. Here, the promising capabilities and the imaging performance are shown for imaging the solar corona at EUV wavelengths. The effectiveness of various potential observing scenarios, the effects of interfering emission lines, and the appropriate form of the cost function for image deconvolution are examined