Degenerate optical parametric amplification in CMOS silicon

Silicon is a common material for photonics due to its favorable optical properties in the telecom and mid-wave IR bands, as well as compatibility with a wide range of complementary metal-oxide semiconductor (CMOS) foundry processes. Crystalline inversion symmetry precludes silicon from natively exhibiting second-order nonlinear optical processes. In this work, we build on recent work in silicon photonics that break this material symmetry using large bias fields, thereby enabling $\chi^{(2)}$ interactions. Using this approach, we demonstrate both second-harmonic generation (with a normalized efficiency of $0.2\,\%\,\mathrm{W^{-1} cm^{-2}}$) and, to our knowledge, the first degenerate $\chi^{(2)}$ optical parametric amplifier (with relative gain of $0.02\,\mathrm{dB}$ using $3\,\mathrm{mW}$ of pump power on-chip at a pump wavelength of $1196\,\mathrm{nm}$) using silicon-on-insulator waveguides fabricated in a CMOS-compatible commercial foundry. We expect this technology to enable the integration of novel nonlinear optical devices such as optical parametric amplifiers, oscillators, and frequency converters into large-scale, hybrid photonic-electronic systems by leveraging the extensive ecosystem of CMOS fabrication.Comment: The first three authors contributed equally to this work; 9 pages, 5 figure

On-chip lateral Si:Te PIN photodiodes for room-temperature detection in the telecom optical wavelength bands

Photonic integrated circuits require photodetectors that operate at room temperature with sensitivity at telecom wavelengths and are suitable for integration with planar complementary-metal-oxide-semiconductor (CMOS) technology. Silicon hyperdoped with deep-level impurities is a promising material for silicon infrared detectors because of its strong room-temperature photoresponse in the short-wavelength infrared region caused by the creation of an impurity band within the silicon band gap. In this work, we present the first experimental demonstration of lateral Te-hyperdoped Si PIN photodetectors operating at room temperature in the optical telecom bands. We provide a detailed description of the fabrication process, working principle, and performance of the photodiodes, including their key figure of merits. Our results are promising for the integration of active and passive photonic elements on a single Si chip, leveraging the advantages of planar CMOS technology.Comment: 18 pages, 5 Figures, Supplementary informatio

Architecture and Advanced Electronics Pathways Toward Highly Adaptive Energy- Efficient Computing

With the explosion of the number of compute nodes, the bottleneck of future computing systems lies in the network architecture connecting the nodes. Addressing the bottleneck requires replacing current backplane-based network topologies. We propose to revolutionize computing electronics by realizing embedded optical waveguides for onboard networking and wireless chip-to-chip links at 200-GHz carrier frequency connecting neighboring boards in a rack. The control of novel rate-adaptive optical and mm-wave transceivers needs tight interlinking with the system software for runtime resource management

A Fault Diagnosis Design Based on Deep Learning Approach for Electric Vehicle Applications

International audienceDiagnosing faults in electric vehicles (EVs) is a great challenge. The purpose of this paper is to demonstrate the detection of faults in an electromechanical conversion chain for conventional or autonomous EVs. The information and data coming from different sensors make it possible for EVs to recover a series of information including currents, voltages, speeds, and so on. This information is processed to detect any faults in the electromechanical conversion chain. The novelty of this study is to develop an architecture for a fault diagnosis model by means of the feature extraction technique. In this regard, the long short-term memory (LSTM) approach for the fault diagnosis is proposed. This approach has been tested for an EV prototype in practice, is superior in accuracy over other fault diagnosis techniques, and is based on machine learning. An EV in an urban context is modeled, and then the fault diagnosis approach is applied based on deep learning architectures. The EV and the fault diagnosis model is simulated in Matlab software. It is also revealed how deep learning contributes to the fault diagnosis of EVs. The simulation and practical results confirm that higher accuracy in the fault diagnosis is obtained by applying the LSTM

Modulation efficiency enhancement of an optical phase modulator using one dimensional photonic crystal structures

Slow light effect based rib silicon waveguide structures are studied in this paper to enhance modulation efficiency of an optoelectronic carrier plasma dispersion effect based phase modulator. Center frequency to achieve desired slow down factor and band width limitations of the structures are investigated through finite element method simulations. Optical modulation efficiency is modeled and the effects of doping, bias voltage and slow light on its performance are studied

Fault Diagnosis of Smart Grids Based on Deep Learning Approach

International audienc