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Shechtman Y, Small E, Lahini Y, et al. Sparsity-based super-resolution and phase-retrieval in waveguide arrays. Opt Express. 2013;21(20):24015-24doi: 10.1364/OE.21.024015.
Shechtman, Y., Small, E., Lahini, Y., Verbin, M., Eldar, Y. C., Silberberg, Y., & Segev, M. (2013). Sparsity-based super-resolution and phase-retrieval in waveguide arrays. Optics express, 21(20), 24015-24. https://doi.org/10.1364/OE.21.024015
Shechtman, Yoav, et al. "Sparsity-based super-resolution and phase-retrieval in waveguide arrays." Optics express vol. 21,20 (2013): 24015-24. doi: https://doi.org/10.1364/OE.21.024015
Shechtman Y, Small E, Lahini Y, Verbin M, Eldar YC, Silberberg Y, Segev M. Sparsity-based super-resolution and phase-retrieval in waveguide arrays. Opt Express. 2013 Oct 07;21(20):24015-24. doi: 10.1364/OE.21.024015. PMID: 24104311.
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Opt Express. 2013 Oct 07;21(20):24015-24. doi: 10.1364/OE.21.024015.

Sparsity-based super-resolution and phase-retrieval in waveguide arrays.

Optics express

Yoav Shechtman, Eran Small, Yoav Lahini, Mor Verbin, Yonina C Eldar, Yaron Silberberg, Mordechai Segev

PMID: 24104311 DOI: 10.1364/OE.21.024015

Abstract

We present a scheme for recovering the complex input field launched into a waveguide array, from partial measurements of its output intensity, given advance knowledge that the input is sparse. In spite of the fact that in general the inversion problem is ill-conditioned, we demonstrate experimentally and in simulations that the prior knowledge of sparsity helps overcome the loss of information. Our method is based on GESPAR, a recently proposed efficient phase retrieval algorithm. Possible applications include optical interconnects and quantum state tomography, and the ideas are extendable to other multiple input and multiple output (MIMO) communication schemes.

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