Many breakthroughs in the laboratories often do not bridge the gap between research and commercialization. However, silicon photonics bucked the trend, with industry observers estimating the commercial market to close in on a billion dollars in 2020. Silicon photonics leverages the billions of dollars and decades of research poured into silicon semiconductor device processing to enable high yield, robust processing, and most of all, low cost. Silicon is also a good optical material, with transparency in the commercially important infrared wavelength bands, and is a suitable platform for large-scale photonic integrated circuits. Silicon photonics is therefore slated to address the world's ever-increasing needs for bandwidth. It is part of an emerging ecosystem which includes designers, foundries, and integrators. In this paper, we review most of the foundries that presently enable silicon photonics integrated circuits fabrication. Some of these are pilot lines of major research institutes, and others are fully commercial pure-play foundries. Since silicon photonics has been commercially active for some years, foundries have released process design kits (PDK) that contain a standard device library. These libraries represent optimized and well-tested photonic elements, whose performance reflects the stability and maturity of the integration platforms. We will document the early works in silicon photonics, as well as its commercial status. We will provide a comprehensive review of the development of silicon photonics and the foundry services which enable the productization, including various efforts to develop and release PDK devices. In this context, we will report the long-standing efforts and contributions that previously IME/A*STAR and now AMF has dedicated to accelerating this journey.

Complex-valued neural networks have many advantages over their real-valued counterparts. Conventional digital electronic computing platforms are incapable of executing truly complex-valued representations and operations. In contrast, optical computing platforms that encode information in both phase and magnitude can execute complex arithmetic by optical interference, offering significantly enhanced computational speed and energy efficiency. However, to date, most demonstrations of optical neural networks still only utilize conventional real-valued frameworks that are designed for digital computers, forfeiting many of the advantages of optical computing such as efficient complex-valued operations. In this article, we highlight an optical neural chip (ONC) that implements truly complex-valued neural networks. We benchmark the performance of our complex-valued ONC in four settings: simple Boolean tasks, species classification of an Iris dataset, classifying nonlinear datasets (Circle and Spiral), and handwriting recognition. Strong learning capabilities (i.e., high accuracy, fast convergence and the capability to construct nonlinear decision boundaries) are achieved by our complex-valued ONC compared to its real-valued counterpart.

Large-scale, highly integrated and low-power-consuming hardware is becoming progressively more important for realizing optical neural networks (ONNs) capable of advanced optical computing. Traditional experimental implementations needN²units such as Mach-Zehnder interferometers (MZIs) for an input dimensionNto realize typical computing operations (convolutions and matrix multiplication), resulting in limited scalability and consuming excessive power. Here, we propose the integrated diffractive optical network for implementing parallel Fourier transforms, convolution operations and application-specific optical computing using two ultracompact diffractive cells (Fourier transform operation) and onlyNMZIs. The footprint and energy consumption scales linearly with the input data dimension, instead of the quadratic scaling in the traditional ONN framework. A ~10-fold reduction in both footprint and energy consumption, as well as equal high accuracy with previous MZI-based ONNs was experimentally achieved for computations performed on theMNISTandFashion-MNISTdatasets. The integrated diffractive optical network (IDNN) chip demonstrates a promising avenue towards scalable and low-power-consumption optical computational chips for optical-artificial-intelligence.

Silicon photonic integrated circuits for telecommunication and data centers have been well studied in the past decade, and now most related efforts have been progressing toward commercialization. Scaling up the silicon-on-insulator (SOI)-based device dimensions in order to extend the operation wavelength to the short mid-infrared (MIR) range (2–4 μm) is attracting research interest, owing to the host of potential applications in lab-on-chip sensors, free space communications, and much more. Other material systems and technology platforms, including silicon-on-silicon nitride, germanium-on-silicon, germanium-on-SOI, germanium-on-silicon nitride, sapphire-on-silicon, SiGe alloy-on-silicon, and aluminum nitride-on-insulator are explored as well in order to realize low-loss waveguide devices for different MIR wavelengths. In this paper, we will comprehensively review silicon photonics for MIR applications, with regard to the state-of-the-art achievements from various device demonstrations in different material platforms by various groups. We will then introduce in detail of our institute’s research and development efforts on the MIR photonic platforms as one case study. Meanwhile, we will discuss the integration schemes along with remaining challenges in devices (e.g., light source) and integration. A few application-oriented examples will be examined to illustrate the issues needing a critical solution toward the final production path (e.g., gas sensors). Finally, we will provide our assessment of the outlook of potential future research topics and engineering challenges along with opportunities.

Optical phased array (OPA) technology is considered a promising solution for solid-state beam steering to supersede the traditional mechanical beam steering. As a key component of the LIDAR system for long-range detection, OPAs featuring a wide steering angle and high resolution without beam aliasing are highly desired. However, a wide steering range requires a waveguide pitch less than half of the wavelength, which is easily subjected to cross talk. Besides, high resolution requires a large aperture, and it is normally achieved by a high count number of waveguides, which complicates the control system. To solve the mentioned issues, we design two high-performance 128-channel OPAs fabricated on a multilayered SiN-on-SOI platform. Attributed to the nonuniform antenna pitch, only 128 waveguides are used to achieve a 4 mm wide aperture. Besides, by virtue of innovative dual-level silicon nitride ( Si 3 N 4 ) waveguide grating antennas, the fishbone antenna OPA achieves a 100 ° × 19.4 ° field of view (FOV) with divergence of 0.021 ° × 0.029 ° , and the chain antenna OPA realizes a 140 ° × 19.23 ° FOV with divergence of 0.021 ° × 0.1 ° . To our best knowledge, 140° is the widest lateral steering range in two-dimensional OPA, and 0.029° is the smallest longitudinal divergence. Finally, we embed the OPA into a frequency-modulated continuous-wave system to achieve 100 m distance measurement. The reflected signal from 100 m distance is well detected with 26 dBm input transmitter power, which proves that OPA serves as a promising candidate for transceiving optical signal in a LIDAR system.

In this paper, we review and provide additional details about our progress on multilayer silicon nitride (SiN)-on-silicon (Si) integrated photonic platforms. In these platforms, one or more SiN waveguide layers are monolithically integrated onto a Si photonic layer. This paper focuses on the development of three-layer platforms for the O- and SCL-bands for very large-scale photonic integrated circuits requiring hundreds or thousands of waveguide crossings. Low-loss interlayer transitions and ultralow-loss waveguide crossings have been demonstrated, along with bilevel and trilevel grating couplers for fiber-to-chip coupling. The SiN and Si passive devices have been monolithically integrated with high-efficiency optical modulators, photodetectors, and thermal tuners in a single photonic platform.