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Optimizing illumination for precise multi-parameter estimations in coherent diffractive imaging
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DOI：10.1364/OL.411339.png)
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Abstract
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Coherent diffractive imaging (CDI) is widely used to characterize structured samples from measurements of diffracting intensity patterns. We introduce a numerical framework to quantify the precision that can be achieved when estimating any given set of parameters characterizing the sample from measured data. The approach, based on the calculation of the Fisher information matrix, provides a clear benchmark to assess the performance of CDI methods. Moreover, by optimizing the Fisher information metric using deep learning optimization libraries, we demonstrate how to identify the optimal illumination scheme that minimizes the estimation error under specified experimental constraints. This work paves the way for an efficient characterization of structured samples at the sub-wavelength scale. (C) 2021 Optical Society of America under the terms of the OSA Open Access Publishing Agreement
Keywords:
RECONSTRUCTION
MICROSCOPY
SCATTERING
RESOLUTION
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