Image Processing Based on Compound Flat Optics

Image processing has become a critical technology in a variety of science and engineering disciplines. While most image processing is performed digitally, optical analog processing has the advantages of being low-power and high-speed though it requires a large volume. Here, we demonstrate optical analog imaging processing using a flat optic for direct image differentiation allowing one to significantly shrink the required optical system size. We first demonstrate how the image differentiator can be combined with traditional imaging systems such as a commercial optical microscope and camera sensor for edge detection. Second, we demonstrate how the entire analog processing system can be realized as a monolithic compound flat optic by integrating the differentiator with a metalens. The compound nanophotonic system manifests the advantage of thin form factor optics as well as the ability to implement complex transfer functions and could open new opportunities in applications such as biological imaging and machine vision

Simulation study of district heating control based on load forecasting

At present, the development of district heating system (DHS) in China is mainly reflected in the scale and structure, there are still great disadvantages in system management and control. The problem of imbalance between the heat supply and the user’s demand is serious. In this paper, a DHS in Kaifeng of China was taken as the research object, and the control model of secondary return temperature of a typical thermal power station which based on the step response is established. Based on the high-precision heating load prediction model of thermal power station, the primary side flow as the control variable, secondary return temperature as the controlled variable, and the generalized predictive control (GPC) algorithm as the control method, the secondary return temperature of the target system is accurately controlled; at the same time, particle swarm optimization (PSO) is used to determine parameters adaptively for parameter tuning in GPC; and the control strategy is simulated. Compared with the traditional Proportion integral differential (PID) control algorithm, The root-mean-square error and mean absolute percentage error of the simulation results of the control strategy and the set value are reduced by 22.24% and 22.33%, respectively, has the advantages of smaller overshoot and faster response, which can achieve the effective control of secondary return temperature and on-demand heating better.</p

All-Dielectric Meta-optics for High-Efficiency Independent Amplitude and Phase Manipulation

Metasurfaces, composed of subwavelength scattering elements, have demonstrated remarkable control over the transmitted amplitude, phase, and polarization of light. However, manipulating the amplitude upon transmission has required loss if a single metasurface is used. Here, we describe high-efficiency independent manipulation of the amplitude and phase of a beam using two lossless phase-only metasurfaces separated by a distance. With this configuration, we experimentally demonstrate optical components such as combined beam-forming and splitting devices, as well as those for forming complex-valued, three-dimensional holograms. The compound meta-optic platform provides a promising approach for achieving high performance optical holographic displays and compact optical components, while exhibiting a high overall efficiency

Meta-optic Accelerators for Object Classifiers

Rapid advances in deep learning have led to paradigm shifts in a number of fields, from medical image analysis to autonomous systems. These advances, however, have resulted in digital neural networks with large computational requirements, resulting in high energy consumption and limitations in real-time decision making when computation resources are limited. Here, we demonstrate a meta-optic based neural network accelerator that can off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both spatial multiplexing and additional information channels, such as polarization, in object classification. End-to-end design is used to co-optimize the optical and digital systems resulting in a robust classifier that achieves 95% accurate classification of handwriting digits and 94% accuracy in classifying both the digit and its polarization state. This approach could enable compact, high-speed, and low-power image and information processing systems for a wide range of applications in machine-vision and artificial intelligence

Intelligent Multi-channel Meta-imagers for Accelerating Machine Vision

Rapid developments in machine vision have led to advances in a variety of industries, from medical image analysis to autonomous systems. These achievements, however, typically necessitate digital neural networks with heavy computational requirements, which are limited by high energy consumption and further hinder real-time decision-making when computation resources are not accessible. Here, we demonstrate an intelligent meta-imager that is designed to work in concert with a digital back-end to off-load computationally expensive convolution operations into high-speed and low-power optics. In this architecture, metasurfaces enable both angle and polarization multiplexing to create multiple information channels that perform positive and negatively valued convolution operations in a single shot. The meta-imager is employed for object classification, experimentally achieving 98.6% accurate classification of handwritten digits and 88.8% accuracy in classifying fashion images. With compactness, high speed, and low power consumption, this approach could find a wide range of applications in artificial intelligence and machine vision applications

Reconfigurable Metasurface for Image Processing

Optical Fourier transform-based processing is an attractive technique due to the fast processing times and large-data rates. Furthermore, it has recently been demonstrated that certain Fourier-based processors can be realized in compact form factors using flat optics. The flat optics, however, have been demonstrated as static filters where the operator is fixed, limiting the applicability of the approach. Here, we demonstrate a reconfigurable metasurface that can be dynamically tuned to provide a range of processing modalities including bright-field imaging, low-pass and high-pass filtering, and second-order differentiation. The dynamically tunable metasurface can be directly combined with standard coherent imaging systems and operates with a numerical aperture up to 0.25 and over a 60 nm bandwidth. The ability to dynamically control light in the wave vector domain, while doing so in a compact form factor, may open new doors to applications in microscopy, machine vision, and sensing

Ultra-thin, High-efficiency Mid-Infrared Transmissive Huygens Meta-Optics

The mid-infrared (mid-IR) is a strategically important band for numerous applications ranging from night vision to biochemical sensing. Unlike visible or near-infrared optical parts which are commonplace and economically available off-the-shelf, mid-IR optics often requires exotic materials or complicated processing, which accounts for their high cost and inferior quality compared to their visible or near-infrared counterparts. Here we theoretically analyzed and experimentally realized a Huygens metasurface platform capable of fulfilling a diverse cross-section of optical functions in the mid-IR. The meta-optical elements were constructed using high-index chalcogenide films deposited on fluoride substrates:the choices of wide-band transparent materials allow the design to be scaled across a broad infrared spectrum. Capitalizing on a novel two-component Huygens' meta-atom design, the meta-optical devices feature an ultra-thin profile ($\lambda_0/8$ in thickness, where $\lambda_0$ is the free-space wavelength) and measured optical efficiencies up to 75% in transmissive mode, both of which represent major improvements over state-of-the-art. We have also demonstrated, for the first time, mid-IR transmissive meta-lenses with diffraction-limited focusing and imaging performance. The projected size, weight and power advantages, coupled with the manufacturing scalability leveraging standard microfabrication technologies, make the Huygens meta-optical devices promising for next-generation mid-IR system applications

Chalcogenide Glass-on-Graphene Photonics

Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated devices via a transfer process. In this paper, we present a new route for 2-D material integration with planar photonics. Central to this approach is the use of chalcogenide glass, a multifunctional material which can be directly deposited and patterned on a wide variety of 2-D materials and can simultaneously function as the light guiding medium, a gate dielectric, and a passivation layer for 2-D materials. Besides claiming improved fabrication yield and throughput compared to the traditional transfer process, our technique also enables unconventional multilayer device geometries optimally designed for enhancing light-matter interactions in the 2-D layers. Capitalizing on this facile integration method, we demonstrate a series of high-performance glass-on-graphene devices including ultra-broadband on-chip polarizers, energy-efficient thermo-optic switches, as well as graphene-based mid-infrared (mid-IR) waveguide-integrated photodetectors and modulators