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

Pavel Sidorenko, Ofer Kfir, Yoav Shechtman, Avner Fleischer, Yonina C. Eldar, Mordechai Segev, Oren Cohen

Research output: Contribution to journalArticlepeer-review

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.

Original languageEnglish
Article number8209
JournalNature Communications
Volume6
DOIs
StatePublished - 8 Sep 2015
Externally publishedYes

Fingerprint

Dive into the research topics of 'Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects'. Together they form a unique fingerprint.

Cite this