457 results about "Optical computing" patented technology

A computing network for space-ground collaborative detection comprises an on-satellite optical computing network and a ground electric computing network, and can directly detect and identify simple targets on a satellite, preprocess complex targets, compress the scale of mass remote sensing data and reduce on-satellite energy consumption and downloading difficulty. And for a simple target identification result and a complex target compression preprocessing result, a compression vector downloaded by an optical network is reconstructed and classified in a ground electric computing network, so that the overall accuracy of the system is improved.

The invention discloses an optical memristor, and relates to the field of photon integrated circuits and optical computing, and the optical memristor comprises a waveguide layer, a ferroelectric film layer, an electrode structure and a substrate. The ferroelectric film layer is located on the upper surface of the substrate; the waveguide layer and the electrode structure are located on the upper surface of the ferroelectric film layer; the waveguide layer is used for propagating an incident light signal and performing amplitude modulation on the incident light signal; the electrode structure is used for applying an electric field to the ferroelectric film layer; and the ferroelectric film layer is used for carrying out phase modulation on optical signals transmitted in the waveguide layer under the action of the electric field. The ferroelectric material is used as the optical switch of the optical memristor, efficient modulation of the optical phase is achieved through the non-volatility and the high electro-optical effect of the ferroelectric material, and meanwhile the optical memristor has the advantages of being low in energy consumption and rapid in response.

The invention provides an optical computing system, a computing compensation method and a photonic integrated circuit chip. The optical computing system includes: a beam splitter which divides an optical wave input to the optical computing system into a first branch and a second branch according to a preset proportion; the calculation module is configured to receive the light wave of the second branch, load an electric signal to the light wave of the second branch to form a light signal, and calculate information represented by the light signal; the monitoring module is configured to receive a first branch of the light wave and monitor the light wave of the first branch in real time; and the post-processing module is configured to perform compensation operation on the calculation result output by the calculation module according to the monitoring result obtained by the monitoring module through monitoring. According to the invention, the extra monitoring module is arranged to monitor the change of the incident light power of the chip in real time, and the calculation precision is compensated in real time based on the change.

The invention belongs to the technical field of micro-nano photoelectrons, and particularly relates to a multi-channel switchable holographic metasurface encryption device and method. The holographic metasurface encryption device is an array formed by nanoscale structure units through two-dimensional periodic continuation, and is called as a phase change dynamic holographic metasurface. Wherein the structural unit is formed by sequentially overlapping a phase change material layer and a metal material layer on a substrate; rectangular holes are formed in the central parts of the phase change material layer and the metal material layer; holographic encryption is realized by utilizing the adjusting capability of the phase change material unit, a plurality of independent holographic image channels are expanded by utilizing the independence of left and right polarization of circularly polarized light, and the switching function of the metasurface holographic display channel is realized through the phase change degree of the phase change material. The phase-change material is introduced into metasurface holographic display, switching of different responses to incident light is achieved through thermal modulation or electric pulse modulation, and therefore different encryption degrees are achieved. The device has a wide application prospect in the fields of optical display, optical calculation and the like.

The invention provides a spatial light modulator, a self-checking device thereof and a light computing device, and relates to the technical field of optical modulation.The spatial light modulator comprises an incident waveguide structure, a covering plate, a liquid crystal layer, a substrate and an emergent waveguide structure; the incident waveguide structure is optically coupled with the cover plate and is used for guiding externally incident laser into the cover plate at a preset angle; the covering plate is used for enabling laser to be propagated in the covering plate in a total reflection form; the substrate bears the liquid crystal layer, integrates the driving circuit and is used for applying regulation and control voltage to the liquid crystal layer; the liquid crystal layer is arranged on the lower side of the covering plate and used for conducting phase modulation on the laser transmitted to the liquid crystal layer in a total reflection mode in response to the regulation voltage. And the emergent waveguide structure is optically coupled with the covering plate and is used for guiding the laser modulated by the liquid crystal layer out of the covering plate to a free space. According to the spatial light modulator, efficient spatial modulation and accurate control of the light field are realized, so that the integration and function accuracy of the spatial light modulator in self-inspection and light calculation are improved.

The invention discloses an end-to-end optical computing chip based on multi-mode analog signal fusion processing, and belongs to the optical computing technology. Comprising a multi-mode input fusion front-end module, an optical fiber input interface and an end-to-end reasoning module. The multi-mode input fusion front-end module can convert different types of original analog signals such as images, spectrums and radio frequencies into unified broadband spectrum input signals. The end-to-end reasoning module constructs a deep optical neural network, and the deep optical neural network comprises a sensing-convolution integrated unit realized by an arrayed waveguide grating (AWG). The end-to-end reasoning module further comprises a photoelectric non-linear-pooling integrated unit, the average pooling function and the non-linear activation function are achieved at the same time, and light path loss is effectively compensated through injection of the supply light source. And finally, integrating the signals subjected to multi-layer processing by a full connection layer, and outputting a classification result by an output layer. According to the chip architecture, direct and efficient processing of multi-mode analog signals is realized.

The invention discloses a three-dimensional heterogeneous integrated optical computing chip, and belongs to the field of optical computing. The computing chip consists of three parts: a spatial diffraction optical neural network core particle, a plane matrix reconfigurable optical neural network component and a plane switchable optical switch module, the single or multiple spatial diffraction optical neural network core particles, the plane matrix reconfigurable optical neural network assembly and the plane switchable optical switch module are combined together in a three-dimensional heterogeneous integration mode, and efficient multi-task optical calculation processing is achieved. The spatial diffraction optical neural network and the plane matrix reconfigurable optical neural network are combined with each other, a traditional optical calculation framework is broken through, the method has wide application prospects in the optical calculation field, and the blank of related technical fields is filled.

Apparatuses, systems and methods for all-optical computing are disclosed. An optical computing apparatus includes a nonlinear optical crystal, at least one light source, and a detector. The at least one light source is configured to spatially modulate vectors of operand values onto coherent optical radiation and to direct the spatially modulated coherent optical radiation into the nonlinear optical crystal, thereby exciting propagating modes in the nonlinear optical crystal corresponding to a computational result of linear and nonlinear operations performed over the vectors. The detector is coupled to receive and sense the coherent optical radiation that has propagated through the nonlinear optical crystal so as to decode the computational result.

The invention discloses an optical computing array based on micro-ring resonators without a free spectral range, which comprises an on-chip wavelength division multiplexing beam splitting array, an on-chip intensity modulation array, two groups of on-chip wavelength division multiplexing beam combining arrays and an on-chip balance detector, the on-chip wavelength division multiplexing beam splitting array and the on-chip wavelength division multiplexing beam combining array are respectively composed of a group of multiple FSR-free MRRs which share the same bus optical waveguide, each resonator corresponds to an independent wavelength channel, and the on-chip intensity modulator array is composed of a plurality of groups of on-chip MZI modulator arrays. According to the optical calculation array implementation method, independent control and coding calculation of different wavelength channels in a broadband wavelength range are realized by utilizing the single harmonic peak characteristic of the FSR-free MRR array and the wide-spectrum intensity modulation function of the MZI unit, the limitation of a free spectrum range on the optical calculation wavelength channel is eliminated, the higher wavelength parallelism is achieved, and the optical calculation array implementation method has the advantages of being simple in structure and convenient to implement. And therefore, the calculation scale is remarkably improved.

The invention discloses an all-optical vortex beam orbital angular momentum mode identification method and system, and relates to the field of optical information processing and optical computing, and the method comprises the steps: S1, constructing a multi-layer architecture all-optical diffraction network; s2, dividing the output detection surface after the diffraction network into a plurality of preset space regions; s3, the vortex light beams carrying orbital angular momentum OAM information sequentially penetrate through the all-optical diffraction network, spatial evolution of a light field in the propagation process is completed, and vortex light classified according to intensity distribution is output; s4, mapping the topological charges of the vortex light to different sub-regions of the detection surface in an intensity distribution form; and S5, performing intensity acquisition on each area on the detection surface through a detector, and determining an OAM mode type of the input light field based on the mode number corresponding to the area with the maximum light intensity. The method is used for performing high-robustness identification on the orbital angular momentum vortex light mode of the vortex light in the presence of a random phase scattering medium.

The invention discloses a dielectric metasurface optical edge detection device and method based on dual-polarization-state Mie resonance, the method shows a non-local dielectric metasurface which is high in robustness and easy to prepare, and the device can achieve polarization-independent edge detection with excellent efficiency and high numerical aperture (NA). By simultaneously utilizing Mie resonance in the s polarization state and the p polarization state, isotropic two-dimensional second-order differential operation under any polarization condition (including non-polarization illumination) is realized. According to the design scheme, real-time image edge extraction can be achieved, the average peak efficiency reaches 30%, the working bandwidth of 40 nm is achieved at the center wavelength of 1064 nm, and high-quality edge detection can be kept under the numerical aperture of 0.5. The work provides a new method for realizing polarization-independent edge detection, and paves a way for practical application of an optical calculation and imaging system.

The invention discloses an optical computing system, a data processing method, a product, equipment and a medium, and relates to the technical field of optical computation.The method comprises the steps that two input and output modules and an optical computing module are arranged, a parameter matrix in the optical computing module is updated according to a to-be-processed feature matrix, and in each iteration, the parameter matrix of the optical computing module is updated; the optical signal modulated by the first input and output module is positively input to the optical calculation module and calculated with the parameter matrix, and the optical signal modulated by the second input and output module is reversely input to the optical calculation module and calculated with a transpose matrix of the parameter matrix, so that an output vector of current iteration is obtained; the key feature information of the feature matrix is determined according to the output vector obtained by the last iteration at the end of iteration, so that the problems of high processing complexity and low processing efficiency caused by processing data through electric calculation are solved, efficient calculation of the parameter matrix and the transpose matrix is completed through optical calculation, the processing complexity is reduced, and the processing efficiency is improved. And the treatment efficiency is improved.

The invention belongs to the technical field of optical calculation, and discloses an error-adaptive optical diffraction neural network in-situ training method, which comprises the following steps: based on the phase of each phase modulation layer, calculating the light field complex amplitude Uk of the input sample complex amplitude on the rear surface of each phase modulation layer and the light field complex amplitude Uo of the input sample complex amplitude on an output plane after forward propagation; calculating an error light field P based on Uo, carrying out three-dimensional central symmetry on a back propagation light path of the error light field P without changing the phase distribution of each phase modulation layer, and calculating the light field complex amplitude of the complex amplitude of the symmetrical error light field on the front surface of each phase modulation layer after forward propagation; the method comprises the steps of obtaining the light field complex amplitude Un + 1-k'of P back propagation to the rear surface of each phase modulation layer, calculating the gradient related to a loss function based on Uk and Un + 1-k 'so as to carry out updating, and carrying out the next round of training until a preset training round or loss convergence is reached. The method can adapt to errors existing in an optical system.

The invention relates to the technical field of optical computing, and discloses an optical neural network and an implementation method thereof, and an optical neural network chip, and the method comprises the steps: an input layer converts and processes an input external signal, obtains an optical signal, and inputs the optical signal to a hidden layer; according to the task requirement of an external signal, the hidden layer dynamically adjusts the weight parameter of the optical neural network under the external magnetic field control condition; an optical signal output by the hidden layer is transmitted to the nonlinear activation layer; aiming at the task requirement of an external signal, the nonlinear activation layer dynamically adjusts the nonlinear characteristic of an activation function under an external magnetic field control condition; and the output layer converts the optical signal output by the nonlinear activation layer into an electric signal, carries out corresponding processing, and outputs a final result. Therefore, the optical neural network is endowed with dynamic adjustability and rapid adjustment capability among different network layers, the weight parameter and the nonlinear function of the full-optical domain dynamic adjustment optical neural network are realized, and the overall operation efficiency is improved.

The embodiment of the invention provides a photoelectric Transform accelerator cooperation method and device, and aims to efficiently process Transform model calculation. Firstly, according to the size M of an optical chip static random access memory on an optical computing chip and feature dimensions d of a query matrix Q, a key matrix K and a value matrix V, Q is divided into Tr sub-blocks, and K and V are respectively divided into Tc sub-blocks. Then, the universal computing chip and the optical computing chip are in interactive communication, the jth sub-block of K and V is transmitted to the optical computing chip firstly, and then the ith sub-block of Q is transmitted circularly for the sub-block. The optical computing chip computes a local attention score matrix Sij and then transmits the matrix back, the general computing chip carries out nonlinear processing on the matrix to obtain a local attention weight matrix Pij, the maximum value mij of each row of the Sij and the sum lij of each row of the Pij are computed, and m, l and O are updated until all sub-blocks K and V are processed. According to the method, through photoelectric collaboration and block calculation, resource utilization is optimized, and calculation efficiency is improved.

The present disclosure relates to the technical field of optical computing, and particularly relates to an intelligent optical computing chip cluster architecture and system. The architecture comprises: a plurality of optical computing chips, and optical path channels are established between the plurality of optical computing chips by using spatial phase adjustment to modulate light beams; and high-speed optical communication and optical diffraction network computing are performed between the plurality of optical computing chips by performing time-domain intensity modulation on the optical path channels. The present disclosure adopting the above scheme can realize the interconnection computing of optical computing chips in the spatial dimension, and does not rely on electricity for information transmission.

The present invention provides a method for optimizing a neural network model in optical computing. The method comprises: acquiring an initial quantization scaling coefficient and an optical computing system noise suppression coefficient; adjusting the initial quantization coefficient on the basis of the noise suppression coefficient; and then using the adjusted coefficient to quantize a neural network model. The present invention improves the stability and reliability of a model in an optical computing system, thereby reducing the impact of noise of the optical computing system on a neural network model.

The invention provides an optical signal synchronous calibration device and method of an optical computing system. The device comprises an optical probe array, an AI coprocessor, an optical path tuning engine and a low-speed electric feedback line, wherein the optical probe array is arranged on a chip; the optical probe array detects optical signals of wavelength channels corresponding to the plurality of optical calculation units and converts the optical signals into electric signals; the AI coprocessor drives a corresponding optical calculation unit to emit a detection pulse according to a pre-distributed time slot index variable, extracts a phase error from the electric signal and calculates a final calibration amount based on the phase error; the optical path tuning engine performs an optical path tuning operation based on the final calibration amount to calibrate an error of the corresponding optical calculation unit; and the low-speed electric feedback line transmits the electric signal to the AI coprocessor and transmits the detection pulse to the chip. According to the invention, through cooperation of spatial distributed detection and board-level centralized processing, real-time calibration in a dynamic environment is realized.

The present invention discloses a reconfigurable integrated optical computing core model, comprising: M×N matrix calculation units; each matrix calculation unit includes two dual-waveguide microring resonators, a straight waveguide, and a phase change material heater, and the straight waveguide is made by covering a phase change material on a silicon waveguide; the phase change material heater is used to heat the phase change material to generate a phase change, thereby changing the light absorption of the straight waveguide; the integrated optical computing core model realizes the multiplication operation of an M×N matrix and an N×1 vector through integrated optical methods, where M and N are natural numbers. The present invention uses a phase change material in the computing core, changes the phase state of the phase change material by heating, changes the light absorption of the straight waveguide, and further changes the matrix elements in the computing core, realizing the reconfigurable characteristics of the computing core model. The present invention can be widely applied to the field of integrated optics.

The present invention belongs to the technical field of semiconductor optoelectronic devices, and specifically relates to an optical computing array based on a germanium modulator, comprising a cross matrix, wherein the cross matrix is ​​formed by crossing multiple rows of mutually parallel input optical waveguides and multiple columns of mutually parallel output optical waveguides; and a photodetector is provided at the output end of each column of the output optical waveguide; multiple optical splitters; multiple germanium modulators, each of the germanium modulators corresponds to one of the cross waveguides, and the first input end of the germanium modulator is connected to the output end of the optical splitter through a transmission optical waveguide; and multiple optical combiners, each of the optical combiners is respectively connected to the output end of the germanium modulator and the output optical waveguide. Through the above structure, the present application comprehensively provides a computing array with a high responsiveness having a thermal compensation mechanism and capable of reducing light reflection, so as to realize a solution for a low-power large-scale integrated computing array under the condition of frequent switching.

The invention discloses an optical neural mimicry computing architecture assisted by space diffraction dimension reduction, and belongs to the field of optical computing. The spatial diffraction dimensionality reduction assisted optical neural mimicry computing architecture comprises an input module, an image copying device, a linear multiplication device, a linear accumulation device, a nonlinear activation device, an on-chip coupling device and an on-chip neural network chip, wherein the on-chip neural network chip comprises an on-chip linear multiplication device and an on-chip nonlinear activation device. According to the specific implementation method, image information needing to be recognized is coded into a multi-wavelength optical matrix through an input module, and dimension reduction operation and feature extraction of the coded matrix are achieved through a plurality of image copying devices, a linear multiplication device, a linear accumulation device and a nonlinear activation device. And the dimension reduction matrix optical information is coupled into the on-chip neural network chip through the on-chip coupling device to realize related neural network functions.

The invention discloses a neural network accelerator based on optical computing, which relates to the technical field of artificial intelligence hardware acceleration and comprises an optical convolution module and an optical full connection module which are directly connected. The optical full connection calculation part can be started after the optical convolution calculation part is completed, photoelectric conversion between convolution and full connection is avoided, photoelectric conversion links are reduced to the maximum extent, the photoelectric conversion loss rate is reduced, and the data transmission efficiency is improved. According to the method, the high parallel characteristic of photonics and the dynamic calculation requirement of a neural network are deeply fused, high-density photon integration is achieved, convolution and full-connection operation are directly completed in an optical domain through the optical calculation technology, the calculation speed and precision are improved, meanwhile, the system energy consumption overhead is reduced, and the system performance is improved. And an efficient and low-power-consumption hardware basis is provided for training and reasoning of a super-large-scale model.

The invention relates to the technical field of optical computing, in particular to a large-scale reconfigurable photon large matrix model and architecture. Wherein the model comprises a mixed light calculation sub-model; the large-scale reconfigurable photon large matrix model comprises an acquisition module, a parallel input module and an integration module, and the acquisition module is used for acquiring a first large matrix and an input vector which need to be calculated; the parallel input module is used for inputting the first large matrix and the input vector into the mixed light calculation sub-model of each parallel channel in parallel based on the determined number of the parallel channels to obtain an output vector of each parallel channel; and the integration module is used for integrating the output vectors of the parallel channels to obtain a target output vector. According to the scheme, under the condition that high calculation precision and high data flux are considered, a large-scale general optical matrix operation new normal form is achieved, and therefore a complex optical general calculation task is supported.

Provided in the present invention are an optical computing system, a computing compensation method, and a photonic integrated circuit chip. The optical computing system comprises: a beam splitter, which splits, into a first branch and a second branch and according to a preset proportion, an optical wave inputted into the optical computing system; a computing module, which is configured to receive the optical wave of the second branch and load an electrical signal onto the optical wave of the second branch, so as to form an optical signal, and perform computation on information represented by the optical signal; a monitoring module, which is configured to receive the optical wave of the first branch and perform real-time monitoring on the optical wave of the first branch; and a post-processing module, which is configured to perform, on the basis of the monitoring result obtained by the monitoring module by means of monitoring, a compensation operation on the computing result outputted by the computing module. In the present invention, by means of providing an additional monitoring module, changes in the light input power of a chip are monitored in real time, and on the basis of the changes, the computing precision is compensated for in real time.

The invention relates to the technical field of semiconductors, in particular to a multiplexing-based optical computing chip and a design method thereof.The multiplexing-based optical computing chip comprises a computing area formed by crossing a first waveguide and a second waveguide, and the computing area comprises a branch waveguide connected with the first waveguide and the second waveguide, a beam splitting part, an intensity modulation part and a first signal conversion part are sequentially arranged on the branch waveguide, the beam splitting part is used for splitting optical signals in a specific proportion, the intensity modulation part is used for modulating the signal intensity of the optical signals into a specific value, and the first signal conversion part is used for setting or maintaining the optical signals in a specific mode; the specific mode means that the optical signal has a specific polarization direction and / or a specific order; the second waveguide is provided with a calculation unit for calculating the sum of the optical powers of the plurality of optical signals. According to the multiplexing scheme provided by the invention, the data processing amount of the optical computing chip can be improved.

The invention provides a chip package, an optical fiber assembly and optical computing equipment, and the chip package comprises a substrate; the photon integrated circuit chip is provided with a first surface and a second surface opposite to the first surface, and the second surface is used for being fixedly connected with the substrate; the optical fiber assembly comprises an optical fiber bearing plate, a cover plate and an optical fiber located between the optical fiber bearing plate and the cover plate, the optical fiber bearing plate comprises a first area and a second area, the first area is used for bearing the optical fiber, and the second area is fixed to the first surface of the photonic integrated circuit chip; an optical fiber in the optical fiber assembly is coupled to the photonic integrated circuit chip.

An optical computing device includes an optical computing section including a first transmissive optical modulation element having cells each having an independently set phase modulation amount. The first transmissive optical modulation element emits a signal light, in a signal direction, generated when transmitted light beams phase-modulated by the cells interfere with each other and a noise light, in a noise direction, transmitted through the first transmissive optical modulation element without being phase-modulated by the cells. The optical computing device includes an optical sensor that detects the signal light outputted from the optical computing section and generates an electrical signal indicating a result of the detection. The first transmissive optical modulation element is configured such that an impact that the noise light has on the electrical signal is smaller than the impact in a state where the signal direction aligns with the noise direction.

The invention relates to the field of optical computing, and provides a signal processing method and device based on an optical computing chip and a photoelectric fusion computing system.The signal processing device comprises an optical input modulation module, a first weight mapping module, a second weight mapping module and an optical output combining module, and the optical input modulation module converts an input signal into a modulated optical signal; the first weight mapping module obtains a first output optical signal based on the first weight; the second weight mapping module acquires a second output optical signal based on a second weight; the optical output combining module obtains a comprehensive output signal based on the first output optical signal and the second output optical signal; the second weight mapping module comprises a light dimension reduction unit, a low-dimensional light modulation unit and a light dimension raising unit, and the light dimension reduction unit performs low-dimensional projection on a modulated light signal; the low-dimensional optical modulation unit adjusts the second weight based on the second weight update signal and obtains an optical signal after low-dimensional processing; and the light dimension raising unit carries out high-dimensional projection on the light signal after low-dimensional processing.

The invention relates to a computing system, a computing method, a chip package and a computing board card. A computing system includes: a shared processing unit; a plurality of processing units, each of the processing units being electrically coupled to the shared processing unit, the plurality of processing units including a first processing unit and a second processing unit; and a plurality of optical computing units, each of the optical computing units being electrically coupled to the shared processing unit, where the plurality of optical computing units include a first optical computing unit and a second optical computing unit.

Quantitative phase imaging (QPI) is a label-free computational imaging technique that provides optical path length information of objects. Here, a diffractive QPI network architecture is disclosed that can synthesize the quantitative phase image of an object by converting the input phase information of a scene or object(s) into intensity variations at the output plane. A diffractive QPI network is a specialized all-optical device designed to perform a quantitative phase-to-intensity transformation through passive diffractive / reflective surfaces that are spatially engineered using deep learning and image data. Forming a compact, all-optical network that axially extends only ˜200-300λ (λ=illumination wavelength), this framework replaces traditional QPI systems and related digital computational burdens with a set of passive substrate layers. All-optical diffractive QPI networks can potentially enable power-efficient, high frame-rate and compact phase imaging systems that might be useful for various applications, including, e.g., on-chip microscopy and sensing.