Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects

Nature Communications
P SidorenkoOren Cohen

Abstract

Phase-retrieval problems of one-dimensional (1D) signals are known to suffer from ambiguity that hampers their recovery from measurements of their Fourier magnitude, even when their support (a region that confines the signal) is known. Here we demonstrate sparsity-based coherent diffraction imaging of 1D objects using extreme-ultraviolet radiation produced from high harmonic generation. Using sparsity as prior information removes the ambiguity in many cases and enhances the resolution beyond the physical limit of the microscope. Our approach may be used in a variety of problems, such as diagnostics of defects in microelectronic chips. Importantly, this is the first demonstration of sparsity-based 1D phase retrieval from actual experiments, hence it paves the way for greatly improving the performance of Fourier-based measurement systems where 1D signals are inherent, such as diagnostics of ultrashort laser pulses, deciphering the complex time-dependent response functions (for example, time-dependent permittivity and permeability) from spectral measurements and vice versa.

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Citations

Nov 10, 2016·Optics Express·Mahendar KumbhamChristophe Silien
Aug 10, 2017·Optics Express·Pavel SidorenkoOren Cohen
Jul 17, 2020·Applied Optics·Paolo AnsuinelliH Paul Urbach
Aug 17, 2018·Optics Express·Oren SolomonYonina C Eldar
Aug 15, 2017·Nano Letters·Shahar TsiperYonina C Eldar

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BETA
chips

Software Mentioned

GESPAR

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