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Over the last 20 years, thin and lightweight optical elements have become very desirable, especially for the terahertz (THz) range. Reduction of the volume of optical elements alongside an increase in their effective efficiency has begun a new direction of research leading to many practical applications. On top of that, diffractive optical elements can not only focus the incident beam, but also can shape the incoming wavefront into a desirable distribution or can redirect the energy. Starting from theoretical calculations of Fourier optics, diffractive elements have been transformed and nowadays form complicated structures that do not resemble a typical Fresnel lens. The precise control over a phase shift introduced by the designed element creates an opportunity to almost freely transform an incident wavefront. Moreover, the vast diversity of computer-generated holograms (also called synthetic) contributes substantially to this topic. Diffractive elements have a great impact on THz optical systems because their manufacturing is very simple in comparison with any other range of radiation (infrared, visible, ultraviolet, etc.). This review paper underlines developments in evolution of diffractive optics and highlights main principles and technological approaches for fabrication of diffraction optics within the terahertz range, thus serving as a guide to design and production considerations.

Zone plates are diffractive optics commonly used in X-ray microscopes. Here, we present a wet-chemical approach for fabricating high aspect ratio Pd/Si zone plate optics aimed at the hard X-ray regime. A Si zone plate mold is fabricated via metal-assisted chemical etching (MACE) and further metalized with Pd via electroless deposition (ELD). MACE results in vertical Si zones with high aspect ratios. The observed MACE rate with our zone plate design is 700 nm/min. The ELD metallization yields a Pd density of 10.7 g/cm 3 , a value slightly lower than the theoretical density of 12 g/cm 3 . Fabricated zone plates have a grid design, 1:1 line-to-space-ratio, 30 nm outermost zone width, and an aspect ratio of 30:1. At 9 keV X-ray energy, the zone plate device shows a first order diffraction efficiency of 1.9%, measured at the MAX IV NanoMAX beamline. With this work, the possibility is opened to fabricate X-ray zone plates with low-cost etching and metallization methods.

We experimentally demonstrate imaging in the long-wave infrared (LWIR) spectral band (8 μm to 12 μm) using a single polymer flat lens based upon multilevel diffractive optics. The device thickness is only 10 am, and chromatic aberrations are corrected over the entire LWIR band with one surface. Due to the drastic reduction in device thickness, we are able to utilize polymers with absorption in the LWIR, allowing for inexpensive manufacturing via imprint lithography. The weight of our lens is less than 100 times those of comparable refractive lenses. We fabricated and characterized 2 different flat lenses. Even with about 25% absorption losses, experiments show that our flat polymer lenses obtain good imaging with field of view of 35° and angular resolution less than 0.013°. The flat lenses were characterized with 2 different commercial LWIR image sensors. Finally, we show that, by using lossless, higher-refractive-index materials like silicon, focusing efficiencies in excess of 70% can be achieved over the entire LWIR band. Our results firmly establish the potential for lightweight, ultrathin, broadband lenses for high-quality imaging in the LWIR band.

One order of magnitude detection enhancement of bow-tie-shaped InGaAs-based terahertz detectors by on-chip incorporation of the secondary diffractive optics is reported. Zone plates were produced directly on the bottom surface of 500 µm-thick InP substrate using the direct laser write technique after an array of InGaAs detectors was formed on the front surface of the wafer. Measurements of detected signal dependence on the angle of the incident wave were performed at 0.76 THz and compared with finite-difference time-domain simulation results. Good correlation of the results shows that the observed enhancement is indeed caused by the focusing performance of the zone plate rather than by the exceptional sensitivity of the single detector.

Machine learning technologies have been extensively applied in high-performance information-processing fields. However, the computation rate of existing hardware is severely circumscribed by conventional Von Neumann architecture. Photonic approaches have demonstrated extraordinary potential for executing deep learning processes that involve complex calculations. In this work, an on-chip diffractive optical neural network (DONN) based on a silicon-on-insulator platform is proposed to perform machine learning tasks with high integration and low power consumption characteristics. To validate the proposed DONN, we fabricated 1-hidden-layer and 3-hidden-layer on-chip DONNs with footprints of 0.15 mm 2 and 0.3 mm 2 and experimentally verified their performance on the classification task of the Iris plants dataset, yielding accuracies of 86.7% and 90%, respectively. Furthermore, a 3-hidden-layer on-chip DONN is fabricated to classify the Modified National Institute of Standards and Technology handwritten digit images. The proposed passive on-chip DONN provides a potential solution for accelerating future artificial intelligence hardware with enhanced performance. Integrating diffractive optical neural networks (DONN) would reduce errors due to bulky components and calibration. Here, the authors exploit integrated 1D dielectric metasurfaces to realise an on-chip DONN device with 90% classification accuracy, computing at 10^16 flops/mm^2 and consuming 10E-17 J/Flop.

Imaging the polarization of light scattered from an object provides an additional degree of freedom for gaining information from a scene. Conventional polarimeters can be bulky and usually consist of mechanically moving parts (with a polarizer and analyzer setup rotating to reveal the degree of polarization). Rubin et al. designed a metasurface-based full-Stokes compact polarization camera without conventional polarization optics and without moving parts. The results provide a simplified route for polarization imaging. Science , this issue p. eaax1839 A metasurface array is designed that can operate as a polarization camera Recent developments have enabled the practical realization of optical elements in which the polarization of light may vary spatially. We present an extension of Fourier optics—matrix Fourier optics—for understanding these devices and apply it to the design and realization of metasurface gratings implementing arbitrary, parallel polarization analysis. We show how these gratings enable a compact, full-Stokes polarization camera without standard polarization optics. Our single-shot polarization camera requires no moving parts, specially patterned pixels, or conventional polarization optics and may enable the widespread adoption of polarization imaging in machine vision, remote sensing, and other areas.

High-end imaging lenses have tended to be based on bulk optical components. Advances in fabrication techniques have enabled the development of ultrathin, lightweight, and planar lenses (metalenses) that have unprecedented functionalities. These metalenses have the potential to replace or complement their conventional bulk counterparts. Khorasaninejad and Capasso review the evolution of metalenses, summarizing achievements and applications and identifying future challenges and opportunities. Metalenses can have numerous applications, ranging from cellphone camera modules, to wearable displays for augmented and virtual reality and machine vision, to bio-imaging and endoscopy. Science , this issue p. eaam8100 Recent progress in metasurface designs fueled by advanced-fabrication techniques has led to the realization of ultrathin, lightweight, and flat lenses (metalenses) with unprecedented functionalities. Owing to straightforward fabrication, generally requiring a single-step lithography, and the possibility of vertical integration, these planar lenses can potentially replace or complement their conventional refractive and diffractive counterparts, leading to further miniaturization of high-performance optical devices and systems. Here we provide a brief overview of the evolution of metalenses, with an emphasis on the visible and near-infrared spectrum, and summarize their important features: diffraction-limited focusing, high-quality imaging, and multifunctionalities. We discuss impending challenges, including aberration correction, and also examine current issues and solutions. We conclude by providing an outlook of this technology platform and identifying promising directions for future research.

Multimodal deep learning plays a pivotal role in supporting the processing and learning of diverse data types within the realm of artificial intelligence generated content (AIGC). However, most photonic neuromorphic processors for deep learning can only handle a single data modality (either vision or audio) due to the lack of abundant parameter training in optical domain. Here, we propose and demonstrate a trainable diffractive optical neural network (TDONN) chip based on on-chip diffractive optics with massive tunable elements to address these constraints. The TDONN chip includes one input layer, five hidden layers, and one output layer, and only one forward propagation is required to obtain the inference results without frequent optical-electrical conversion. The customized stochastic gradient descent algorithm and the drop-out mechanism are developed for photonic neurons to realize in situ training and fast convergence in the optical domain. The TDONN chip achieves a potential throughput of 217.6 tera-operations per second (TOPS) with high computing density (447.7 TOPS/mm 2 ), high system-level energy efficiency (7.28 TOPS/W), and low optical latency (30.2 ps). The TDONN chip has successfully implemented four-class classification in different modalities (vision, audio, and touch) and achieve 85.7% accuracy on multimodal test sets. Our work opens up a new avenue for multimodal deep learning with integrated photonic processors, providing a potential solution for low-power AI large models using photonic technology. Most photonic processors can only handle a single data modality due to the lack of abundant parameter training in optical domain. Here, authors propose and demonstrate a trainable diffractive optical neural network chip based on on-chip diffractive optics with tunable elements to address these constraints.

Optical elements play a crucial role in many modern systems, from cellphones to missiles. The miniaturization trend poses a challenge to optics, since classical lenses and mirrors tend to be bulky. One way of dealing with this challenge is using flat optics. For many years flat optics has been implemented using diffractive optics technology, but in the last two decades a new technology called metasurfaces has emerged. This technology does not replace diffractive optics, but rather expands on it, leveraging the new ability to manufacture subwavelength features on optical substrates. For imaging and focusing applications, diffractive lenses and metalenses are used, as a subset of diffractive optics and metasurfaces, respectively. Recently there has been debate over whether metalenses offer any real advantages over diffractive lenses. In this commentary we will try to gain some insight into this debate and present our opinion on the subject.

The angular response of thin diffractive optical elements is highly correlated. For example, the angles of incidence and diffraction of a grating are locked through the grating momentum determined by the grating period. Other diffractive devices, including conventional metasurfaces, have a similar angular behavior due to the fixed locations of the Fresnel zone boundaries and the weak angular sensitivity of the meta-atoms. To alter this fundamental property, we introduce angle-multiplexed metasurfaces, composed of reflective high-contrast dielectric U-shaped meta-atoms, whose response under illumination from different angles can be controlled independently. This enables flat optical devices that impose different and independent optical transformations when illuminated from different directions, a capability not previously available in diffractive optics.