Beam-divergence deconvolution for diffractive imaging

This Rapid Communication presents a method of beam-divergence deconvolution for diffractive imaging. First, the detected diffraction intensity is formulated as a convolution between the diffraction intensity of parallel incident beams and the divergence of an incident beam. It is shown numerically that the convolution causes the reconstructed image to shrink and become blurred. Next, the algorithm of deconvolution used in the iterative Fourier phase retrieval method is applied to the convoluted diffraction intensity deteriorated by quantum noise. Numerical simulations show that the proposed algorithm recovers the deconvoluted diffraction intensity and improves the reconstructed image. Finally, the algorithm is applied to an electron-beam experiment to reconstruct a multiwall carbon nanotube. The results verified that the algorithm reduces the influence of beam divergence.