Based on transformation optics, we introduce another set of generalized laws of reflection and refraction (differs from that of [Science 334, 333 (2011)]), through which a transformation media slab is derived as a meta-surface, producing anomalous reflection and refraction for all polarizations of incident light.

Generalized laws of reflection and refraction from transformation optics

The pace of innovations in the field of optical trapping has ramped up in the past couple of years. The implementation of structured light, leading to groundbreaking inventions such as high-resolution microscopy or optical communication, has unveiled the unexplored potential for optical trapping. Advancing from a single Gaussian light field as trapping potential, optical tweezers have gotten more and more structure; innovative trapping landscapes have been developed, starting from multiple traps realized by holographic optical tweezers, via complex scalar light fields sculpted in amplitude and phase, up to polarization-structured and highly confined vectorial beams. In this article, we provide a timely overview on recent advances in advanced optical trapping and discuss future perspectives given by the combination of optical manipulation with the emerging field of structured light.

Optical trapping gets structure: Structured light for advanced optical manipulation

Photonic solutions are today a mature industrial reality concerning high speed, high throughput data communication and switching infrastructures. It is still a matter of investigation to what extent photonics will play a role in next-generation computing architectures. In particular, due to the recent outstanding achievements of artificial neural networks, there is a big interest in trying to improve their speed and energy efficiency by exploiting photonic-based hardware instead of electronic-based hardware. In this work we review the state-of-the-art of photonic artificial neural networks. We propose a taxonomy of the existing solutions (categorized into multilayer perceptrons, convolutional neural networks, spiking neural networks, and reservoir computing) with emphasis on proof-of-concept implementations. We also survey the specific approaches developed for training photonic neural networks. Finally we discuss the open challenges and highlight the most promising future research directions in this field.

Photonic Neural Networks: A Survey

Fourier ptychography (FP) is a recently developed computational framework for high-resolution multimodal imaging. In a coherent imaging setting, FP illuminates the sample with angle-varied plane waves and captures the corresponding intensity images. The captured intensity data are then iteratively synthesized in the Fourier space to recover a widefield, high-resolution complex sample image that bypasses the frequency limit of the employed objective lens. The recovery process of FP can also be extended to incoherent imaging settings where non-uniform intensity patterns are projected on the sample and the captured data are used for image reconstruction. In this paper, we will review the progress of the FP technique and discuss different implementations including LED-array illumination, liquid-crystal-display modulation, aperture-scanning approach, lensless synthetic aperture implementation, and incoherent-imaging implementation. We will also review different imaging modalities using FP and report the new developments of darkfield and epi-illuminated imaging modalities.

Fourier Ptychography for Brightfield, Phase, Darkfield, Reflective, Multi-Slice, and Fluorescence Imaging

It is widely believed that grape seed proanthocyanidin extract (GSPE) exerts antioxidant and anti-inflammatory effects. Dietary supplementation with GSPE has been reported to alleviate colitis signs in mice, but the mechanisms involved require further exploration. The present study investigated how the oral administration of GSPE ameliorates colitis signs and reduces colitis-associated inflammation. C57BL/6 mice were treated with GSPE for 21 days. During the final 7 days of treatment, the mice were administered dextran sulfate sodium (DSS) dissolved in drinking water to induce experimental colitis. We found that GSPE treatment improved DSS-induced colitis, which was evidenced by decreases in disease activity index (DAI) scores, pathological scores, and oxidative stress and increases in zonula occludens-1 (ZO-1), occludin, and claudin-1 mRNA levels of colon tissue. Notably, the proinflammatory cytokines TNF-α and IL-1β were significantly downregulated as a result of GSPE treatment in colon tissues. GSPE treatment also reduced NLR family pyrin domain-containing 3 (NLRP3) inflammasome mRNA levels of colon tissue. Furthermore, an analysis of 16S rRNA sequences showed that GSPE rebalanced the DSS-damaged gut microbiota, including reducing Bacteroidetes, Dubosiella, and Veillonella, increasing Verrucomicrobia and Akkermansia, and elevating the Firmicutes to Bacteroidetes ratio. In conclusion, GSPE supplementation alleviates DSS-induced colitis by modulating inflammatory cytokines and oxidation stress, maintaining the intestinal barrier, and improving the microbial community. These results indicate that GSPE might be a new dietary strategy for the treatment of ulcerative colitis.

Grape seed proanthocyanidin extract ameliorates dextran sulfate sodium-induced colitis through intestinal barrier improvement, oxidative stress reduction, and inflammatory cytokines and gut microbiota modulation.

Gold nanoparticles are widely exploited in phototherapy. Owing to their biocompatibility and their strong visible-light surface plasmonic resonance, these particles also serve as contrast agents for cell image enhancement and super-resolved imaging. Yet, their optical signal is still insufficiently strong for many important real-life applications. Also, the differentiation between adjacent nanoparticles is usually limited by the optical resolution and the orientations of non-spherical particles are unknown. These limitations hamper the progress in cell research by direct optical microscopy and narrow the range of phototherapy applications. Here we demonstrate exploiting the optical anisotropy of non-spherical nanoparticles to achieve super-resolution in live cell imaging and to resolve the intracellular nanoparticle orientations. In particular, by modulating the light polarization and taking advantage of the polarization-dependence of gold nanorod optical properties, we realize the ‘lock-in amplification’, widely-used in electronic engineering, to achieve image enhancement in live cells and in cells that undergo apoptotic changes.

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Imaging of nanoparticle dynamics in live and apoptotic cells using temporally-modulated polarization.

The rapid growth of applications that rely on artificial neural network (ANN) concepts gives rise to a staggering increase in the demand for hardware implementations of neural networks. New types of hardware that can support the requirements of high-speed associative computing while maintaining low power consumption are sought, and optical artificial neural networks fit the task well. Inherently, optical artificial neural networks can be faster, support larger bandwidth, and produce less heat than their electronic counterparts. Here we propose the design of an optical ANN-based imaging system that has the ability to self-study image signals from an incoherent light source in different colors. Our design consists of a combination of a multimode fiber and a multi-core optical fiber realizing a neural network. We show that the signals, transmitted through the multimode fiber, can be used for image identification purposes and can also be reconstructed using ANNs with a low number of nodes. An all-optical solution can then be achieved by realizing these networks with the multi-core optical neural network fiber.

Color image identification and reconstruction using artificial neural networks on multimode fiber images: towards an all-optical design.

We propose a method for resolution enhancement of a diffraction limited optical system based on the capture of a set of low resolution images. These images are obtained after projection of an ensemble of unknown speckle patterns on top of the high resolution object that is to be imaged. Each speckle pattern is generated by the same thin (and unknown) diffuser, but illuminated with a slightly different wavelength. From the ensemble of low resolution images, we obtain a system of equations that can be solved in an iterative manner that enables reconstruction of the high resolution object. As a result, we also achieve the projected high resolution speckle patterns used for the encoding.

Superresolved imaging based on wavelength multiplexing of projected unknown speckle patterns

We present here a new method for shaping a pulsed IR (λ = 1550nm) laser beam in silicon. The shaping is based on the plasma dispersion effect (PDE). The shaping is done by a second pulsed pump laser beam at 532nm (in either a Gaussian mode or a donut mode) which simultaneously and collinearly illuminates the silicon's surface with the IR beam. Following the PDE, and in proportion to its spatial intensity distribution, the 532nm laser beam shapes the point spread function (PSF) by controlling the lateral transmission of the IR probe beam. The use of this probe in a laser scanning microscope allows imaging and a wide range of contactless electrical measurements in silicon integrated circuits (IC) being under operation. We propose this shaping method to overcome the diffraction resolution limit in silicon microscopy on and deep under the silicon surface.

Plasma dispersion effect based super-resolved imaging in silicon.

Previous works reported that linear optics could be used to observe sub-wavelength features with a conventional optical microscope. Yet, the ability to reach a sub-200 nm resolution with a visible light remains limited. We present a novel widely-applicable method, where particle trapping is employed to overcome this limit. The combination of the light scattered by the sample and by the trapped particles encodes super-resolution information, which we decode by post image processing, with the trapped particle locations predetermined. As the first proof of concept our method successfully resolved sample characteristic features down to 100 nm. Improved performance is achieved with the fluorescence of the trapped particles employed. Further improvement may be attained with trapped particles of a smaller size.

Omer Wagner

Papers

Imaging of nanoparticle dynamics in live and apoptotic cells using temporally-modulated polarization.

Color image identification and reconstruction using artificial neural networks on multimode fiber images: towards an all-optical design.

Superresolved imaging based on wavelength multiplexing of projected unknown speckle patterns

Plasma dispersion effect based super-resolved imaging in silicon.

Optical-tweezing-based linear-optics nanoscopy.