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Sidorenko P, Kfir O, Shechtman Y, et al. Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects. Nat Commun. 2015;6:8209doi: 10.1038/ncomms9209.
Sidorenko, P., Kfir, O., Shechtman, Y., Fleischer, A., Eldar, Y. C., Segev, M., & Cohen, O. (2015). Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects. Nature communications, 68209. https://doi.org/10.1038/ncomms9209
Sidorenko, Pavel, et al. "Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects." Nature communications vol. 6 (2015): 8209. doi: https://doi.org/10.1038/ncomms9209
Sidorenko P, Kfir O, Shechtman Y, Fleischer A, Eldar YC, Segev M, Cohen O. Sparsity-based super-resolved coherent diffraction imaging of one-dimensional objects. Nat Commun. 2015 Sep 08;6:8209. doi: 10.1038/ncomms9209. PMID: 26345495; PMCID: PMC4569841.
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Nat Commun. 2015 Sep 08;6:8209. doi: 10.1038/ncomms9209.

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

Nature communications

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

Affiliations

  1. Department of Physics and Solid State Institute, Technion, Haifa 32000, Israel.
  2. Department of Chemistry, Stanford University, Stanford, California 94305, USA.
  3. Department of Physics and Optical Engineering, Ort Braude College, Karmiel 21982, Israel.
  4. Department of Electrical Engineering, Technion, Haifa 32000, Israel.

PMID: 26345495 PMCID: PMC4569841 DOI: 10.1038/ncomms9209

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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