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The past decade has witnessed the advent of nanophotonics, where light–matter interaction is shaped, almost at will, with human-made designed nanostructures. However, the design process for these nanostructures has remained complex, often relying on the intuition and expertise of the designer, ultimately limiting the reach and penetration of this groundbreaking approach. Recently, there has been an increasing number of studies in applying machine learning techniques for the design of nanostructures. Most of these studies engage deep learning techniques, which entail training a deep neural network (DNN) to approximate the highly nonlinear function of the underlying physical process of the interaction between light and the nanostructures. At the end of the training, the DNN allows for on-demand design of nanostructures (i.e., the model can infer nanostructure geometries for desired light spectra). In this article, we review previous studies for designing nanostructures, including recent advances where a DNN is trained to generate a two-dimensional image of the designed nanostructure, which is not limited to a closed set of nanostructure shapes, and can be trained for the design of any geometry. This allows for better generalization, with higher applicability for real-world design problems.

Currently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the preclinical stage. This study assessed the pupil light reflex (PLR) for focal red and blue stimuli in central and peripheral retina in 125 cognitively normal middle age subjects (45-71 YO) at high risk for AD due to a family history of the disease, and 61 age-similar subjects with no family history of AD using Chromatic Pupilloperimetry coupled with Machine Learning (ML). All subjects had normal ophthalmic assessment, and normal retinal and optic nerve thickness by optical coherence tomography. No significant differences were observed between groups in cognitive function and volumetric brain MRI. Chromatic pupilloperimetry-based ML models were highly discriminative in differentiating subjects with and without AD family history, using transient PLR for focal red (primarily cone-mediated), and dim blue (primarily rod-mediated) light stimuli. Features associated with transient PLR latency achieved Area Under the Receiver Operating Characteristic Curve of 0.90 ± 0.051 (left-eye) and 0.87 ± 0.048 (right-eye). Parameters associated with the contraction arm of the rod and cone-mediated PLR were more discriminative compared to parameters associated with the relaxation arm and melanopsin-mediated PLR. Taken together our study suggests that subtle focal changes in pupil contraction latency may be detected decades before the onset of AD clinical symptoms. The dendrites of melanopsin containing retinal ganglion cells may be affected very early at the preclinical stages of AD.

Currently there are no reliable biomarkers for early detection of Alzheimer's disease (AD) at the preclinical stage. This study assessed the pupil light reflex (PLR) for focal red and blue light stimuli in central and peripheral retina in 125 cognitively normal middle age subjects (45–71 years old) at high risk for AD due to a family history of the disease (FH+), and 61 age-similar subjects with no family history of AD (FH−) using Chromatic Pupilloperimetry coupled with Machine Learning (ML). All subjects had normal ophthalmic assessment, and normal retinal and optic nerve thickness by optical coherence tomography. No significant differences were observed between groups in cognitive function and volumetric brain MRI. Chromatic pupilloperimetry-based ML models were highly discriminative in differentiating subjects with and without AD family history, using transient PLR for focal red (primarily cone-mediated), and dim blue (primarily rod-mediated) light stimuli. Features associated with transient pupil response latency (PRL) achieved Area Under the Curve Receiver Operating Characteristic (AUC-ROC) of 0.90 ± 0.051 (left-eye) and 0.87 ± 0.048 (right-eye). Parameters associated with the contraction arm of the rod and cone-mediated PLR were more discriminative compared to parameters associated with the relaxation arm and melanopsin-mediated PLR. Significantly shorter PRL for dim blue light was measured in the FH+ group in two test targets in the temporal visual field in right eye that had highest relative weight in the ML algorithm (mean ± standard error, SE 0.449 s ± 0.007 s vs. 0.478 s ± 0.010 s, p = 0.038). Taken together our study suggests that subtle focal changes in pupil contraction latency may be detected in subjects at high risk to develop AD, decades before the onset of AD clinical symptoms. The dendrites of melanopsin containing retinal ganglion cells may be affected very early at the preclinical stages of AD.

Small-angle X-ray scattering (SAXS) techniques enable convenient nanoscopic characterization for various systems and conditions. Unlike synchrotron-based setups, lab-based SAXS systems intrinsically suffer from lower X-ray flux and limited angular resolution. Here, we develop a two-step retrieval methodology to enhance the angular resolution for given experimental conditions. Using minute hardware additions, we show that translating the X-ray detector in subpixel steps and modifying the incoming beam shape results in a set of 2D scattering images, which is sufficient for super-resolution SAXS retrieval. The technique is verified experimentally to show superior resolution. Such advantages have a direct impact on the ability to resolve finer nanoscopic structures and can be implemented in most existing SAXS apparatuses both using synchrotron- and laboratory-based sources.

We introduce spectra2pix, a deep neural network trained to generate 2D images of nanostructures based on their transmission spectra. Owing to this architecture, our model can be trained for the design of any arbitrary geometry

This work presents a data driven method to retrieve the geometry of a coupled waveguide system from the measured intensity of the electric field. It is shown that neural networks perform better than kNN regression.

We introduce a broadband mid-infrared upconversion imaging scheme based on adiabatic frequency conversion. Contrary to state-of-the-art upconversion imaging limited by phase matching, our method does not require serial acquisitions to cover a large spectrum.

We experimentally demonstrate coherent control of the nonlinear response of optical second harmonic generation in resonant nanostructures beyond the weak-field regime. Contrary to common perception, we show that maximizing the intensity of the pulse does not yield the strongest nonlinear power-law response. We show this effect emerges from the temporally asymmetric photo-induced response in a resonant mediated non-instantaneous interaction. We develop a novel theoretical approach which captures the photoinduced nonlinearities in resonant nanostructures beyond the two photon description and give an intuitive picture to the observed non-instantaneous phenomena.

Van der Waals (vdW) materials offer an exciting platform for strong light-matter interaction enabled by their polaritonic modes and the associated deep subwavelength light confinement. Semiconductor vdW materials such as WSe 2 are of particular interest for photonic and quantum integrated technologies because they sustain visible–near-infrared (VIS-NIR) exciton-polariton (EP) modes at room temperature. Here, we develop a unique spatiotemporal imaging technique at the femtosecond-nanometric scale and observe the EP dynamics in WSe 2 waveguides. Our method, based on a novel ultrafast broadband intrapulse pump-probe near-field imaging, allows direct visualization of EP formation and propagation in WSe 2 showing, at room temperature, ultraslow EP with a group velocity of v g ~ 0.017 c . Our imaging method paves the way for in situ ultrafast coherent control and extreme spatiotemporal imaging of condensed matter.

We develop a coherent hyperspectral near-field microscope using a combined nano-Fourier Transform Infra-Red (FTIR) spectroscope and a scattering Scanning Near-field Optical Microscope (s-SNOM) illuminated by an ultra-broadband few-cycle femtosecond source, spanning a spectrum from 660 to 1050 nm. Using this spatio-spectral approach, we resolve hyperspectral near-field response of a single plasmonic nano-antennas over 450 nm bandwidth with a spatial resolution of 40 nm and a spectral resolution of 50 cm−1. In particular, we identify the electric near-field spatial distribution of the dipole resonant mode of various nano-antennas and observe, in accordance with previous theoretical reports, that those are spectrally red-shifted from their far-field response. Moreover, we are able to spectrally and spatially differentiate the near-field distribution of the dipole and quadrupole modes at the single nanoparticle level. Being coherent and short-pulsed, our technique opens the path for optical ultrafast characterization and control of light-matter interaction at the nanoscale.

Recently, there has been an increasing number of studies applying machine learning techniques for the design of nanostructures. Most of these studies train a deep neural network (DNN) to approximate the highly nonlinear function of the underlying physical mapping between spectra and nanostructures. At the end of training, the DNN allows an on-demand design of nanostructures, i.e., the model can infer nanostructure geometries for desired spectra. While these approaches have presented a new paradigm, they are limited in the complexity of the structures proposed, often bound to parametric geometries. Here we introduce spectra2pix, which is a DNN trained to generate 2D images of the target nanostructures. By predicting an image, our model architecture is not limited to a closed set of nanostructure shapes, and can be trained for the design of a much wider space of geometries. We show, for the first time, to the best of our knowledge, a successful generalization ability, by designing completely unseen shapes of geometries. We attribute the successful generalization to the ability of a pixel-wise architecture to learn local properties of the meta-material, therefore mimicking faithfully the underlying physical process. Importantly, beyond synthetical data, we show our model generalization capability on real experimental data.

Upconversion imaging, where mid infrared (IR) photons are converted to visible and near IR photons via a nonlinear crystal and detected on cheap and high-performance Silicon detectors, is an appealing method to address the limitations of thermal sensors which are expensive, often require cooling and suffer from both limited spectral response and limited spatial resolution as well as poor sensitivity. However, phase matching severely limits the spectral bandwidth of this technique therefore requiring serial acquisitions in order to cover a large spectrum. Here, we introduce a novel upconversion imaging scheme covering the mid IR based on adiabatic frequency conversion. We present a mid IR multicolor imaging and demonstrate simultaneous imaging on a CMOS camera of radiation spanning a spectrum from 2 to 4 \mu m. Our approach being coherent and ultrafast in essence, we further demonstrate spectrally resolved spatio-temporal imaging which allows spatially distinguishing the temporal evolution of spectral components.

We demonstrate a method to retrieve the geometry of physically inaccessible coupled waveguide systems based solely on the measured distribution of the optical intensity. Inspired by recent advancements in computer vision, and by leveraging the image-to-image translation capabilities of conditional generative adversarial neural networks (cGANs), our method successfully predicts the arbitrary geometry of waveguide systems with segments of varying widths. As a benchmark, we show that our neural network outperforms nearest neighbor regression from both a runtime and accuracy point of view.

Nanophotonics, the field that merges photonics and nanotechnology, has in recent years revolutionized the field of optics by enabling the manipulation of light–matter interactions with subwavelength structures. However, despite the many advances in this field, the design, fabrication and characterization has remained widely an iterative process in which the designer guesses a structure and solves the Maxwell’s equations for it. In contrast, the inverse problem, i.e., obtaining a geometry for a desired electromagnetic response, remains a challenging and time-consuming task within the boundaries of very specific assumptions. Here, we experimentally demonstrate that a novel Deep Neural Network trained with thousands of synthetic experiments is not only able to retrieve subwavelength dimensions from solely far-field measurements but is also capable of directly addressing the inverse problem. Our approach allows the rapid design and characterization of metasurface-based optical elements as well as optimal nanostructures for targeted chemicals and biomolecules, which are critical for sensing, imaging and integrated spectroscopy applications., Optics: Controlling light at the nanoscale Scientists have used the power of computing to design tiny structures capable of controlling light at the nanoscale, opening the door for new applications in sensing, imaging and spectroscopy. The emerging field of nano-photonics, which enables the manipulation of light-matter interactions using nanostructures, has revolutionized the field of optics. However, designing a nanostructure that produces a desired optical response is very challenging. Rising to the challenge, Haim Suchowski and colleagues from Tel Aviv University in Israel have developed an innovative technique that uses Deep Neural Networks to model the complex relationships between light-matter interactions, allowing them to characterise nanostructures based on their far-field optical responses. Their approach provides a rapid and efficient method for the designing the optical responses of nanostructures, and could be used in a range of applications, including sensing and imaging.

Our visual perception of our surroundings is ultimately limited by the diffraction-limit, which stipulates that optical information smaller than roughly half the illumination wavelength is not retrievable. Over the past decades, many breakthroughs have led to unprecedented imaging capabilities beyond the diffraction-limit, with applications in biology and nanotechnology. In this context, nano-photonics has had a profound impact on the field of optics by enabling the manipulation of light-matter interaction with subwave-length structures [1, 2, 3]. However, despite the many advances in this field, its impact and penetration in our daily life has been hindered by a convoluted and iterative process, cycling through modeling, nanofabrication and nano-characterization. The fundamental reason is the fact that not only the prediction of the optical response is very time consuming and requires solving Maxwell's equations with dedicated numerical packages [4, 5, 6]. But, more significantly, the inverse problem, i.e. designing a nanostructure with an on-demand optical response, is currently a prohibitive task even with the most advanced numerical tools due to the high non-linearity of the problem [7, 8]. Here, we harness the power of Deep Learning and show its ability to predict the geometry of nanostructures based solely on their far-field response. This approach addresses in a direct way the currently inaccessible inverse problem breaking the ground for on-demand design of optical response with applications such as sensing, imaging and also for Plasmons mediated cancer thermotherapy.

In the past two decades, ultrashort pulse lasers oscillators and amplifiers became common equipment in the fundamental scientific exploration as well as in handful of industrial applications. Those sources, which by their nature are broadband and coherent, allow exploring processes and dynamics in nature at ultrafast time scale. Due to the extremely high peak power, nonlinear optics in the ultrashort regime results in efficient frequency conversion generation processes. Among the various nonlinear conversion processes, three wave mixing and especially second harmonic generation (SHG) became widely used. Yet, frequency conversion in the ultrashort regime usually exhibits a tradeoff between the conversion bandwidth and the conversion efficiency due to the phase mismatch between the interacting waves. In the last decade, adiabatic frequency conversion method has overcome the tradeoff between conversion efficiency and bandwidth for sum frequency generation, difference frequency generation, Optical parametric amplification and recently in SHG processes. Here, we experimentally demonstrate that an adiabatic design is capable of extremely robust and efficient SHG at power levels characteristic of high-rep-rate femtosecond oscillators. We show that with pulse peak energies of nJ, one can achieve above 50% of energy conversion efficiency for 70fs Ti-Sapphire pulses. Furthermore, the flat conversion response of the presented design allows performing broadband pulse shaping manipulations before the nonlinear optical conversion. More specifically, using a spatial light modulator in a 4-f configuration, we present a tunable pump-probe based on a varying spectral phase profile in the frequency domain. Additionally, we show that by applying a π-step spectral phase, coherent control of the SHG spectrum can be achieved.

We observe the propagation of an exciton-polariton wave in a WSe2 nanometric slab. We directly visualize with unprecedented spatio-temporal resolution (50 nm

We introduce a novel excitation and detection scheme in near-field optical microscopy based on a multifrequency method. Using this method, we experimentally demonstrate enhanced sensitivity, implying improved spatial resolution in optical measurements.

We observe the propagation of an exciton-polariton wave in a WSe2 nanometric slab. We directly visualize with unprecedented spatio-temporal resolution (50 nm

Photoelectrochemical etching of silicon can be used to form lateral refractive index gradients for transformation optical devices. This technique allows the fabrication of macroscale devices with large refractive index gradients. Patterned porous layers can also be lifted from the substrate and transferred to other materials, creating more possibilities for novel devices.

We experimentally measure the ultrafast spatio-temporal near-field response of a single plasmonic nanostructure over a broad spectral range, using a pump-probe setup combined with a nano-FTIR SNOM illuminated by ultra-broadband few-cycle femtosecond source.

The Fourier transform-infrared (FT-IR) spectrometer is a widely used high-resolution spectral characterization method in materials, chemicals, and more. However, the inverse relation between the spectral resolution and the interferometer's arm length yields a tradeoff between spectral resolution and spectrometer footprint. Here, we introduce a novel method to overcome this traditional FT-IR resolution limit. The enhanced high-resolution multi-scan compact FT-IR spectrometer we present achieves an effectively long interferogram by combining multiple short FT-IR scans. Simulation and experimental results demonstrate a significant increase in the spectral resolution of a FT-IR spectrometer by employing our interferogram stitching algorithm.

An ultrathin conformai skin cloak that can hide three-dimensional objects of arbitrary shape in the visible wavelength range is demonstrated experimentally. Using the concept of reflection phase manipulation with metasurface nanoantennas, we restored not only the wavefront, but also the phase of the reflected light.

We introduce and theoretically demonstrate a quantum metamaterial made of dense ultracold neutral atoms loaded into an inherently defect-free artificial crystal of light, immune to well-known critical challenges inevitable in conventional solid-state platforms. We demonstrate an all-optical control, on ultrafast time scales, over the photonic topological transition of the isofrequency contour from an open to closed topology at the same frequency. This atomic lattice quantum metamaterial enables a dynamic manipulation of the decay rate branching ratio of a probe quantum emitter by more than an order of magnitude. Our proposal may lead to practically lossless, tunable, and topologically reconfigurable quantum metamaterials, for single or few-photon-level applications as varied as quantum sensing, quantum information processing, and quantum simulations using metamaterials.

We experimentally observe hyperspectral near-field response of a single plasmonic nanostructure, using a combined nano-FTIR SNOM illuminated by ultra-broadband few-cycle femtosecond source. Control of the spectral response across the nanpoostructure is achieved.

We propose a novel architecture for topologically reconfigurable quantum metamaterial by engineering the response of dense ultracold atoms loaded in an artificial crystal of light. Our atomic lattice quantum metamaterial opens the door for applications at single-photon level with metamaterials.

On-chip optical data processing and photonic quantum integrated circuits require the integration of densely packed directional couplers at the nanoscale. However, the inherent evanescent coupling at this length scale severely limits the compactness of such on-chip photonic circuits. Here, inspired by the adiabatic elimination in a N-level atomic system, we report an experimental realization of a pair of directional couplers that are effectively isolated from each other despite their subwavelength packing. This approach opens the way to ultradense arrays of waveguide couplers for integrated optical and quantum logic gates.

Wrap-around invisibility cloak An invisibility cloak can be used to conceal an object from view by guiding light around it. Most cloaks developed so far have bulky structures that are difficult to scale up for hiding large objects. To design a thin invisibility cloak that can be wrapped around an object such as a sheet or skin, Ni et al. designed a two-dimensional metamaterial surface. Such flexible, highly reflective materials could be manufactured at large scale to hide large objects. Science , this issue p. 1310

The ability to control light propagation in photonic integrated circuits is at the foundation of modern light-based communication. However, the inherent crosstalk in densely packed waveguides and the lack of robust control of the coupling are a major roadblock toward ultra-high density photonic integrated circuits. As a result, the diffraction limit is often considered as the lower bound for ultra-dense silicon photonics circuits. Here we experimentally demonstrate an active control of the coupling between two closely packed waveguides via the interaction with a decoupled waveguide. This control scheme is analogous to the adiabatic elimination, a well-known procedure in atomic physics. This approach offers an attractive solution for ultra-dense integrated nanophotonics for light-based communications and integrated quantum computing., Optical communications and quantum operations require active coupling control in closely packed integrated photonic circuits. Here, Mrejen et al. exploit adiabatic elimination to demonstrate active coupling control between two closely packed waveguides by tuning the mode index of an in-between decoupled waveguide.

We experimentally demonstrate an ultrathin conformal skin cloak that can hide three-dimensional objects of arbitrary shape in the visible wavelength range by exploiting the phase control capability of metasurface.

We theoretically and experimentally demonstrate a multifrequency excitation and detection scheme in apertureless near field optical microscopy, that exceeds current state of the art sensitivity and background suppression. By exciting the AFM tip at its two first flexural modes, and demodulating the detected signal at the harmonics of their sum, we extract a near field signal with a twofold improved sensitivity and deep sub-wavelength resolution, reaching $\lambda/230$. Furthermore, the method offers rich control over experimental degrees of freedom, expanding the parameter space for achieving complete optical background suppression. This approach breaks the ground for non-interferometric complete phase and amplitude retrieval of the near field signal, and is suitable for any multimodal excitation and higher harmonic demodulation., Comment: 5 pages, 4 figures

High-speed Silicon Photonics calls for solutions providing a small footprint, high density, and minimum crosstalk, as exemplified by the recent development of integrated optical modulators. Yet, the performances of such modulators are hindered by intrinsic material losses, which results in low energy efficiency. Using the concept of Adiabatic Elimination, here, we introduce a scheme allowing for the low-loss modulation in densely packed waveguides. Our system is composed of two waveguides, whose coupling is mediated by an intermediate third waveguide. The signal is carried by the two outer modes, while the active control of their coupling is achieved via the intermediate dark mode. The modulation is performed by the manipulation of the central-waveguide mode index, leaving the signal-carrying waveguides unaffected by the loss. We discuss how Adiabatic Elimination provides a solution for mitigating signal losses and designing relatively compact, broadband, and energy-efficient integrated optical modulators.

We experimentally demonstrate a novel approach for densely packed coupled waveguides, based on adiabatic elimination scheme, allowing control of the inherent coupling between waveguides. At the nano-scale, zero coupling between the waveguides can be achieved.

We theoretically investigate interacting dark resonances in a plasmonic meta-molecule comprising a bright nano-antenna coupled to cascaded dark elements. This structure enables efficient energy transfer and exhibits sub-natural spectral response analogous to the atomic counterpart.

We investigate interacting dark resonance type physics with plasmonic metamolecule consisting of a multi-layered radiative atom coupled to cascaded subradiant atoms. In addition to sub-natural spectral response, these metamolecules also exhibits efficient intramolecular excitation transfer.

Open quantum systems consisting of coupled bound and continuum states have been studied in a variety of physical systems, particularly within the scope of nuclear, atomic, and molecular physics. In the open systems, the effects of the continuum decay channels are accounted for by indirect non-Hermitian couplings among the quasibound states. Here we explore anti-Hermitian coupling in a plasmonic system for spatially manipulating light on the nanoscale. We show that by utilizing the anti-Hermitian coupling, plasmonic antennas closely packed within only λ/15 separations can be individually excited from the far field, which are otherwise indistinguishable from each other. This opens a new venue for the nanoscale lightwave control, wavelength multiplexing, and spectrum splitting.

Extra ordinary transmission through arrays of subwavelength apertures has been investigated using near-field scanning optical microscopy. For such studies arrays were fabricated to give maximum resonance enhancement of light transmission at the wavelength of illumination that was used (532 nm). To define this enhancement a design was employed that allowed in one field of view of a near-field image the investigation of single apertures of dimension that was similar to what was incorporated into the sub-wavelength hole array. Significant asymmetry in the transmission and the propagation of the light along the aperture array was detected. This non-uniformity could be explained by polarization of the incident light, edge effects and the geometry of the array. The results support a hypothesis of both enhanced transmission due to surface plasmons and a non-diffracting beaming as a function of distance effect in the propagation of the light from the array.

Dark state physics has led to a variety of remarkable phenomena in atomic physics, quantum optics, and information theory. Here, we investigate interacting dark resonance type physics in multi-layered plasmonic meta-molecules. We theoretically demonstrate that these plasmonic meta-molecules exhibit sub-natural spectral response, analogous to conventional atomic four-level configuration, by manipulating the evanescent coupling between the bright and dark elements (plasmonic atoms). Using cascaded coupling, we show nearly 4-fold reduction in linewidth of the hybridized resonance compared to a resonantly excited single bright plasmonic atom with same absorbance. In addition, we engineered the geometry of the meta-molecules to realize efficient intramolecular excitation transfer with nearly 80%, on resonant excitation, of the total absorption being localized at the second dark plasmonic atom. An analytical description of the spectral response of the structure is presented with full electrodynamics simulations to corroborate our results. Such multilayered meta-molecules can bring a new dimension to higher quality factor plasmonic resonance, efficient excitation transfer, wavelength demultiplexing, and enhanced non-linearity at nanoscale.

We experimentally demonstrate an efficient broadband second-harmonic generation (SHG) process with a tunable mode-locked Ti:sapphire oscillator. We have achieved a robust broadband and efficient flat conversion of more than 35 nm wavelength by designing an adiabatic aperiodically poled potassium titanyl phosphate crystal. Moreover, we have shown that with such efficient flat conversion, we can shape and control broadband second-harmonic pulses. More specifically, we assign a spectral phase of absolute value and π-step, which allows wavelength tunable intense pump-probe and amplitude modulation of the broadband second-harmonic output. Such spectral phases serve as a proof of concept for other pulse-shaping applications for nonlinear spectroscopy and imaging.