All-in-one silicon photonic polarization processor

Abstract

With the great developments in optical communication technology and large-scale optical integration technology, it is imperative to realize the traditional functions of polarization processing on an integration platform. Most of the existing polarization devices, such as polarization multiplexers/demultiplexers, polarization controllers, polarization analyzers, etc., perform only a single function. Definitely, integrating all these polarization functions on a chip will increase function flexibility and integration density and also cut the cost. In this article, we demonstrate an all-in-one chip-scale polarization processor based on a linear optical network. The polarization functions can be configured by tuning the array of phase shifters on the chip. We demonstrate multiple polarization processing functions, including those of a multiple-input-multiple-output polarization descrambler, polarization controller, and polarization analyzer, which are the basic building blocks of polarization processing. More functions can be realized by using an additional two-dimensional output grating. A numerical gradient descent algorithm is employed to self-configure and self-optimize these functions. Our demonstration suggests great potential for chip-scale, reconfigurable, and fully programmable photonic polarization processors with the artificial intelligence algorithm.

Adaptive opto-electromechanical silicon-on-insulator increased bandwidth accelerometer

“…For industrial production integrating the lasing source with the sensor has the advantages of cutting on the cost and eliminating the intensity fluctuation of the input light due to vibrations in the coupling fiber. The integration of a programmable polarization controller [47,48] on the sensor chip to couple the desired fundamental mode is also advantageous to avoid the cost of expensive external polarization controllers. The different photonic components on the integration template of the sensor are connected by waveguides.…”

Recent progress of integrated circuits and optoelectronic chips

“…The spike temporal encoding, excitatory and inhibitory response, refractory period, and spike-timing dependent plasticity (STDP) have been demonstrated numerically and experimentally. From the architectures and algorithm perspective, different architectures, such as optical matrix computation [184,185], photonic inmemory computing [186], photonic convolutional neural network [187,188], photonic reservoir computing [189,190], and photonic SNN [191,192], have been explored in recent years.…”

Photonic Matrix Computing: From Fundamentals to Applications

“…The following year, Hughes et al thoroughly discussed the training of ONNs by backpropagation and gradient measurement [ 52 ], and this work provided a path toward effectively implementing on-chip training and optimizing reconfigurable integrated optical platforms. By applying on-chip training on the integrated optical platform, Zhou et al proposed and experimentally demonstrated an all-in-one silicon photonic polarization processor [ 53 , 54 ], a universal matrix computing chip [ 55 ], and a self-configuring programmable signal processor [ 56 ], etc. Beyond the applications in machine learning, these works may also broaden the access to intelligent optical information processing.…”