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Classifying and assembling two-dimensional X-ray laser diffraction patterns of a single particle to reconstruct the three-dimensional diffraction intensity function; Resolution limit due to the quantum noise

Tokuhisa, Atsushi*; Taka, Junichiro*; Kono, Hidetoshi; Go, Nobuhiro*

A new two-step algorithm is developed for reconstructing three-dimensional diffraction intensity of a globular biological macromolecule from many experimentally measured quantum-noise limited two-dimensional (2D) X-ray laser diffraction patterns, each for unknown orientation. First step is a classification of 2D patterns into groups according to similarity of direction of incident X-ray with respect to the molecule and an averaging within each group to reduce the noise. Second is a detection of common intersecting circles between the signal-enhanced 2D patterns to identify their mutual location in the 3D wave-number space. The newly developed algorithm enables to detect signal for classification in such a noisy experimental photon-count data as low as $$sim$$0.1 photons per effective pixel. Wavenumber of such a limiting pixel determines the attainable structural resolution. From this fact, resolution attainable by this new method of analysis as well as two important experimental parameters, the number of 2D patterns to be measured (load for detector) and the number of pairs of 2D patterns to be analyzed (load for computer), are derived as a function of intensity of incident X-ray and quantities characterizing the target molecule.



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Category:Chemistry, Multidisciplinary



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