Abstract: Embodiments of the present disclosure provide a network logical layering method based on Routing In Fat Tree (RIFT) protocol, a network logical layering device, a network device and a storage medium. By exchanging Link Information Element (LIE) packets and Topology Information Element (TIE) packets with other devices, a network device can enable the other devices in the network to know a topology supported by the present device and to know neighbor information and Metric information of the present device in the supported topology, and the network device can also know the topologies supported by the other devices in the network and the neighbor information and the Metric information of the other devices in the corresponding topologies. Thus, the device can calculate a topology route corresponding to the topology supported thereby.

Abstract: A high-speed and low-voltage electro-optical modulator based on a lithium niobate-silicon wafer. A silicon wafer is located above a lithium niobate wafer; a lithium niobate-silicon hybrid waveguide is formed by etching a silicon waveguide; and the power of light waves is differently distributed in the lithium niobate-silicon hybrid waveguide by changing the structure of the silicon waveguide. When higher power is distributed in the silicon waveguide, the high-speed and low-voltage electro-optical modulator is suitable for realizing a compact wave splitting function, a wave combining function and a thermo-optical modulation function; and when higher power is distributed in the lithium niobate waveguide, the high-speed and low-voltage electro-optical modulator is suitable for realizing a high-speed and low-voltage electro-optical modulation function.

Abstract: A monolithically integrated optical analog-to-digital conversion system based on a lithium niobate-silicon wafer, and a method for manufacturing the same, wherein a novel wafer (lithium niobate-silicon wafer) is used to implement the monolithically integrated optical analog-to-digital conversion system having multiple photonic devices, including an electro-optical modulator array, a tunable delay line array, an electronic circuit, and the like. As a result, multiple devices are manufactured on one chip, and the performance advantages and the stability of the system are guaranteed. Moreover, the present invention provides a CMOS-compatible method for manufacturing the system, so that the monolithically integrated optical analog-to-digital conversion system based on the lithium niobate-silicon wafer can be implemented on platforms of most chip manufacturers.

Abstract: Method and system for intelligent decision-making photonic signal processing, where the system comprises a multi-functional input unit, an electro-optical conversion module, a signal processing module, a photoelectric conversion module, a multi-functional output unit, and an artificial intelligence chip. The invention combines the advantages of photonic high-speed, wide-band, and electronic flexibility, combined with heterogeneous photoelectron hybrid integration, packaging and other processes, along with deep learning algorithm, is an intelligent electronic information system that may simultaneously realize digital and analog signal processing.

Abstract: A high-speed and low-voltage electro-optical modulator based on a lithium niobate-silicon wafer. A silicon wafer is located above a lithium niobate wafer; a lithium niobate-silicon hybrid waveguide is formed by etching a silicon waveguide; and the power of light waves is differently distributed in the lithium niobate-silicon hybrid waveguide by changing the structure of the silicon waveguide. When higher power is distributed in the silicon waveguide, the high-speed and low-voltage electro-optical modulator is suitable for realizing a compact wave splitting function, a wave combining function and a thermo-optical modulation function; and when higher power is distributed in the lithium niobate waveguide, the high-speed and low-voltage electro-optical modulator is suitable for realizing a high-speed and low-voltage electro-optical modulation function.

Abstract: Integration method of a large-scale silicon-based lithium niobate film electro-optic modulator array. By using the method, the difficulty of a fabrication process of a lithium niobate crystal layer is reduced, requirements on precision of bonding lithium niobate and silicon is reduced, and fabrication and bonding of the large-scale array lithium niobate crystal layer can be completed at one time, so that production efficiency of the silicon-based lithium niobate film electro-optic modulator array is greatly improved; through design and optimization of the structure of the silicon crystal layers, light can be naturally alternated and mutually transmitted in silicon waveguides and lithium niobate waveguides, and a high-performance electro-optic modulation effect of the lithium niobate film is achieved.

Abstract: A monolithically integrated optical analog-to-digital conversion system based on a lithium niobate-silicon wafer, and a method for manufacturing the same, wherein a novel wafer (lithium niobate-silicon wafer) is used to implement the monolithically integrated optical analog-to-digital conversion system having multiple photonic devices, including an electro-optical modulator array, a tunable delay line array, an electronic circuit, and the like. As a result, multiple devices are manufactured on one chip, and the performance advantages and the stability of the system are guaranteed. Moreover, the present invention provides a CMOS-compatible method for manufacturing the system, so that the monolithically integrated optical analog-to-digital conversion system based on the lithium niobate-silicon wafer can be implemented on platforms of most chip manufacturers.

Abstract: Integration method of a large-scale silicon-based lithium niobate film electro-optic modulator array. By using the method, the difficulty of a fabrication process of a lithium niobate crystal layer is reduced, requirements on precision of bonding lithium niobate and silicon is reduced, and fabrication and bonding of the large-scale array lithium niobate crystal layer can be completed at one time, so that production efficiency of the silicon-based lithium niobate film electro-optic modulator array is greatly improved; through design and optimization of the structure of the silicon crystal layers, light can be naturally alternated and mutually transmitted in silicon waveguides and lithium niobate waveguides, and a high-performance electro-optic modulation effect of the lithium niobate film is achieved.

Abstract: A device for noise suppression and distortion correction of analog-to-digital converters based on deep learning that realizes effect of correcting noise and distortion of analog to digital converters. The method is applied to electronic ADCs or photonic ADCs. It utilizes the learning ability of the deep network to perform system response learning on ADCs which need noise suppression and distortion correction, establishes a computational model in the deep network that can suppress the reconstruction of noises and distorted signals, performs noise suppression and distortion correction on the signals obtained by ADCs, and thereby improves performance of the learned ADCs. The device improves the performance of the microwave photon system with high sampling precision of microwave photon radar and optical communication system.

Abstract: A high-speed and high-precision photonic analog-to-digital conversion device capable of realizing intelligent signal processing. Learning ability of deep learning technology is utilized to learn the nonlinear response and channel mismatch effect of the system and configure optimal parameters of the deep network. Deterioration of photonic analog-to-digital conversion system performance caused by nonlinear distortion and channel mismatch distortion is eliminated in real time, and performance indicators thereof are improved. By using the induction and deduction ability of deep learning technology, intelligent signal processing of the input signal is realized, and users are provided with digital signals that meet the requirements.

Abstract: A high-speed and high-precision photonic analog-to-digital conversion device capable of realizing intelligent signal processing. Learning ability of deep learning technology is utilized to learn the nonlinear response and channel mismatch effect of the system and configure optimal parameters of the deep network. Deterioration of photonic analog-to-digital conversion system performance caused by nonlinear distortion and channel mismatch distortion is eliminated in real time, and performance indicators thereof are improved. By using the induction and deduction ability of deep learning technology, intelligent signal processing of the input signal is realized, and users are provided with digital signals that meet the requirements.

Abstract: A method for noise suppression and distortion correction of analog-to-digital converters based on deep learning that realizes effect of correcting noise and distortion of analog to digital converters. The method is applied to electronic ADCs or photonic ADCs. It utilizes the learning ability of the deep network to perform system response learning on ADCs which need noise suppression and distortion correction, establishes a computational model in the deep network that can suppress the reconstruction of noises and distorted signals, performs noise suppression and distortion correction on the signals obtained by ADCs, and thereby improves performance of the learned ADCs. The present invention has a very important role in improving the performance of the microwave photon system with high sampling precision of microwave photon radar and optical communication system.

Abstract: Method and system for intelligent decision-making photonic signal processing, where the system comprises a multi-functional input unit, an electro-optical conversion module, a signal processing module, a photoelectric conversion module, a multi-functional output unit, and an artificial intelligence chip. The invention combines the advantages of photonic high-speed, wide-band, and electronic flexibility, combined with heterogeneous photoelectron hybrid integration, packaging and other processes, along with deep learning algorithm, is an intelligent electronic information system that may simultaneously realize digital and analog signal processing.