Silicon is evolving as a versatile photonic platform with multiple functionalities that can be seamlessly integrated. The tool box is rich starting from the ability to guide and amplify multiple wavelength sources at GHz bandwidths, to optomechanical MEMS. The strong confinement of light in ultra small structures also enables the generation of strong optical forces. We have recently shown that nonlinear optical forces can enable controllable manipulation of photonic structures. These advances should enable future micro-optomechanical systems (MOMS) with novel and distinct functionalities. A research area that recently has emerged is nonlinear optics using silicon photonics. Since the birth of nonlinear optics, researchers have continually focused on developing efficient nonlinear optical devices that require low optical powers. The strong light confinement in silicon waveguides results in a high effective nonlinearity ad enables fine tuning of waveguide dispersion which is essential for phase matching of parametric nonlinear optical processes such as four-wave-mixing (FWM) We demonstrated FWM-based frequency conversion in waveguides using as little as 1 mW of pump power in a ring-resonator geometry, and ∼100 mW of pump power over bandwidths exceeding 800 nm in a straight-waveguide device. In addition, by using the concept of time-space duality we have shown the temporally stretching and compressing of optical waveforms which allows for seamless transformation between the GHz and THz regimes.

Nonlinear silicon photonics

Photonic signal processing is essential in the optical communication and optical computing. Numerous photonic signal processors have been proposed, but most of them exhibit limited reconfigurabilit...

Self-Configuring and Reconfigurable Silicon Photonic Signal Processor

All-optical devices, which are utilized to process optical signals without electro-optical conversion, play an essential role in the next generation ultrafast, ultralow power-consumption optical information processing systems To satisfy the performance requirement, nonlinear optical materials that are associated with fast response, high nonlinearity, broad wavelength operation, low optical loss, low fabrication cost, and integration compatibility with optical components are required Graphene is a promising candidate, particularly considering its electrically or optically tunable optical properties, ultrafast large nonlinearity, and high integration compatibility with various nanostructures Thus far, three all-optical modulation systems utilize graphene, namely free-space modulators, fiber-based modulators, and on-chip modulators This paper aims to provide a broad view of state-of-the-art researches on the graphene-based all-optical modulation systems The performances of different devices are reviewed and compared to present a comprehensive analysis and perspective of graphene-based all-optical modulation devices

Graphene-based all-optical modulators

Replacing electrons with photons is a compelling route towards light-speed, highly parallel, and low-power artificial intelligence computing. Recently, all-optical diffractive neural deep neural networks have been demonstrated. However, the existing architectures often comprise bulky components and, most critically, they cannot mimic the human brain for multitasking. Here, we demonstrate a multi-skilled diffractive neural network based on a metasurface device, which can perform on-chip multi-channel sensing and multitasking at the speed of light in the visible. The metasurface is integrated with a complementary metal oxide semiconductor imaging sensor. Polarization multiplexing scheme of the subwavelength nanostructures are applied to construct a multi-channel classifier framework for simultaneous recognition of digital and fashionable items. The areal density of the artificial neurons can reach up to 6.25x106/mm2 multiplied by the number of channels. Our platform provides an integrated solution with all-optical on-chip sensing and computing for applications in machine vision, autonomous driving, and precision medicine.

Metasurface-Enabled On-Chip Multiplexed Diffractive Neural Networks in the Visible

Abstract Ultracompact chip-integrated all-optical half- and full-adders are realized based on signal-light induced plasmonic-nanocavity-modes shift in a planar plasmonic microstructure covered with a nonlinear nanocomposite layer, which can be directly integrated into plasmonic circuits. Tremendous nonlinear enhancement is obtained for the nanocomposite cover layer, attributed to resonant excitation, slow light effect, as well as field enhancement effect provided by the plasmonic nanocavity. The feature size of the device is <15 μm, which is reduced by three orders of magnitude compared with previous reports. The operating threshold power is determined to be 300 μW (corresponding to a threshold intensity of 7.8 MW/cm2), which is reduced by two orders of magnitude compared with previous reports. The intensity contrast ratio between two output logic states, “1” and “0,” is larger than 27 dB, which is among the highest values reported to date. Our work is the first to experimentally realize on-chip half- and full-adders based on nonlinear plasmonic nanocavities having an ultrasmall feature size, ultralow threshold power, and high intensity contrast ratio simultaneously. This work not only provides a platform for the study of nonlinear optics, but also paves a way to realize ultrahigh-speed signal computing chips.

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Ultracompact all-optical full-adder and half-adder based on nonlinear plasmonic nanocavities

Matrix computation, as a fundamental building block of information processing in science and technology, contributes most of the computational overheads in modern signal processing and artificial intelligence algorithms. Photonic accelerators are designed to accelerate specific categories of computing in the optical domain, especially matrix multiplication, to address the growing demand for computing resources and capacity. Photonic matrix multiplication has much potential to expand the domain of telecommunication, and artificial intelligence benefiting from its superior performance. Recent research in photonic matrix multiplication has flourished and may provide opportunities to develop applications that are unachievable at present by conventional electronic processors. In this review, we first introduce the methods of photonic matrix multiplication, mainly including the plane light conversion method, Mach-Zehnder interferometer method and wavelength division multiplexing method. We also summarize the developmental milestones of photonic matrix multiplication and the related applications. Then, we review their detailed advances in applications to optical signal processing and artificial neural networks in recent years. Finally, we comment on the challenges and perspectives of photonic matrix multiplication and photonic acceleration. 

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Photonic matrix multiplication lights up photonic accelerator and beyond

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Here we experimentally demonstrate reconfigurable logic gates via four-wave-mixing (FWM) in silicon waveguide with an operating speed of up to 40 Gb/s. After demodulated by a 40-GHz delay interferometer (DI), four non-return-to-zero differential phase shift keying (NRZ-DPSK) signals with carefully selected wavelengths are launched into the waveguide at the same time. Thanks to the effective FWM in silicon nano-waveguide, a full set of the two-input logic minterms can be generated simultaneously, and arbitrary combinational logic functions are able to be realized by properly combining these minterms.

40 Gb/s reconfigurable optical logic gates based on FWM in silicon waveguide.

We present an expanded all-optical programmable logic array (O-PLA) using multi-input and multi-output canonical logic units (CLUs) generation. Based on four-wave mixing (FWM) in highly nonlinear fiber (HNLF), two-input and three-input CLUs are simultaneously achieved in five different channels with an operation speed of 40 Gb/s. Clear temporal waveforms and wide open eye diagrams are successfully observed. The effectiveness of the scheme is validated by extinction ratio and optical signal-to-noise ratio measurements. The computing capacity, defined as the total amount of logic functions achieved by the O-PLA, is discussed in detail. For a three-input O-PLA, the computing capacity of the expanded CLUs-PLA is more than two times as large as that of the standard CLUs-PLA, and this multiple will increase to more than three and a half as the idlers are individually independent.

Expanded all-optical programmable logic array based on multi-input/output canonical logic units

The all-optical programmable logic array (PLA) is one of the most important optical complex logic devices that can implement combinational logic functions. In this Letter, we propose and experimentally demonstrate an integrated all-optical PLA at the operation speed of 40 Gb/s. The PLA mainly consists of a delay interferometer (DI) and semiconductor optical amplifiers (SOAs) of different lengths. The DI is used to pre-code the input signals and improve the reconfigurability of the scheme. The longer SOAs are nonlinear media for generating canonical logic units (CLUs) using four-wave mixing. The shorter SOAs are used to select the appropriate CLUs by changing the working states; then reconfigurable logic functions can be output directly. The results show that all the CLUs are realized successfully, and the optical signal-to-noise ratios are above 22 dB. The exclusive NOR gate and exclusive OR gate are experimentally demonstrated based on output CLUs.

Wenchan Dong

Papers

Photonic matrix multiplication lights up photonic accelerator and beyond

Photonic matrix multiplication lights up photonic accelerator and beyond

40 Gb/s reconfigurable optical logic gates based on FWM in silicon waveguide.

Expanded all-optical programmable logic array based on multi-input/output canonical logic units

Integrated all-optical programmable logic array based on semiconductor optical amplifiers.