Created by sebastien.popoff on 27/10/2020


Inverse design of planar optical components using deep learning

[N.J. Dinsdale et al., arxiv, 2009.11810, (2020)]

Photonic integrable circuits are basically waveguide structures that allow performing useful operations, such as mode or wavelength multiplexing/demultiplexing in the case of telecommunication applications. For many operations, we can find quite easy solutions, where the shape of the structure imposes certain boundary conditions that force light to behave the way we want. However, for an arbitrary operation, it is not always possible to find a trivial solution. Non-trivial solutions, where the link between the geometry of the structure and its function is not direct, should then be considered. In the present paper, the authors use deep learning to find geometrical configurations for planar photonic circuits that look like disordered waveguides but actually perform a previously chosen linear operation. These configurations lead experimentally to robust, high throughput, and accurate behaviors.

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Created by sebastien.popoff on 06/10/2020


Model-based wavefront shaping microscopy

[A. Thendiyammal et al.,  Opt. Lett., 45 (2020)]

Wavefront shaping offers the possibility to increasing microscopic imaging depth. By learning how to focus deep inside a (not too) scattering medium, we also learn how to compensate for scattering effects around this area, allowing us to retrieve an image of this area. Typically, finding the wavefront that focuses light at a given target is done using a feedback optimization procedure, or by measuring the response of the system. In this paper, the authors propose another approach. They first create a model of the system thanks to some calibration measurements. The model is then used for finding the optical input wavefront that would be utilized for imaging at different depths. They experimentally demonstrate the advantage of this technique for two-photon fluorescent imaging through a low scattering medium.

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Created by sebastien.popoff on 29/09/2020

Highlights Tutorials Spatial Light Modulators

Easy characterization of SLMs' phase deformation

[D. Marco et al., Opt. Lett., 45 (2020)]

Technical papers are important for the scientific community, it helps in particular to reproduce experimental setups. They are unfortunately not valued enough by scientific journals. I want today to highlight such a paper. Liquid crystals phase modulators - and indeed any kind of spatial light modulator (SLM) - are not free of imperfections. One effect that appears is a phase distortion of the reflected field due to spatial non-uniformities that occur during the fabrications. In practice, if you illuminate an SLM with a plane wave and you display a uniform mask, one does not end up with a plane wave, but an aberrated wavefront. In the present paper, the authors use a quite easy to implement technique to retrieve the phase distortion introduced by the SLM.

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Created by admin on 15/09/2020


Real-time shaping of entangled photons by classical control and feedback

[O. Lib, G. Hasson and Y. Bromberg, Sci. Adv. 6 (2020)]

Wavefront shaping offers the possibility to compensate for the effect of propagation through heterogeneous media. However, when using a single or a few photons, the feedback signal is typically too weak to allow real-time wavefront shaping applications, which limits applications for quantum communications using entangled photons. In this paper from the team of Yaron Bromberg at the Hebrew University of Jerusalem, the authors overcome this challenge by using as feedback the classical signal of the pump that follows the same path as the entangled photon. It allows adapting in real-time the pump wavefront to compensate for the aberrations/scattering introduced by a heterogeneous dynamic sample.

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