548results about "Optical computing devices" patented technology

The invention relates to the technical field of edge computing, and discloses an intelligent edge computing co-processing system based on an integrated circuit, which comprises a heterogeneous computing cluster module, a hardware computing unit set, a multi-core control processor based on RISC-V, a programmable pulse tensor computing array and a reconfigurable engine oriented to streaming processing, according to the intelligent edge computing cooperative processing system based on the integrated circuit, zero-delay data exchange is realized through silicon intermediate layer integration of the heterogeneous computing cluster module and a snakelike data channel, and traditional bus arbitration delay is eliminated through real-time operation code analysis and optimal optical communication path mapping of the hardware task routing matrix (TRF) module; the priority path distribution of the task scheduling subsystem is synchronously coordinated with the time-sensitive task, so that the collaborative efficiency of the computing unit is improved in multiple dimensions, the non-blocking transmission of the high-priority task is ensured, and the effect of enhancing the overall processing capability and response speed of the intelligent edge computing is achieved.

The invention discloses an intelligent control method and system based on pole-mounted circuit breaker equipment, and relates to the technical field of power grid control, and the method comprises the steps: collecting environmental data of a pole-mounted circuit breaker, employing a Kalman filtering fusion algorithm, outputting a fusion state vector, constructing time series data, employing a photon to calculate an accelerated time series neural network, and obtaining a time series neural network model; and performing complex field mapping and optical phase shift modulation on the extracted features, and predicting a future current value. According to the method, complex field mapping is carried out on features extracted by a time convolution layer, the expression ability of nonlinear features is enhanced, optical phase shift modulation is introduced, phase and amplitude information is further adjusted, the nonlinear modeling ability of time sequence features is improved, and multi-modal data fusion and multi-scale consistency verification of fractal dimensions are combined, so that the time sequence features of the fractal dimension are optimized. Time scale deviation of different data sources is eliminated, and effectiveness and consistency of multi-dimensional feature fusion are improved.

The invention discloses a multi-core-particle optical matrix calculation framework, which is characterized in that a block matrix is adopted to decompose a large-scale optical matrix calculation chip into a plurality of small-scale optical matrix calculation core particles, and active and passive separation is adopted to decompose the optical matrix calculation chip into modulator array core particles, detector array core particles and optical matrix calculation core particles. Decomposing the M * N matrix A into m * n p * q matrixes Aij; an input N-dimensional vector X is decomposed into n-channel q-dimensional vectors Xj, and an output M-dimensional vector Y is decomposed into m p-dimensional vectors Yi. Input light passes through the n modulator array core particles to form n channel q-dimensional vectors, m * n q-dimensional vectors are formed after m beam splitting copying, the m * n q-dimensional vectors are input into the m * n optical matrix calculation core particles respectively and multiplied by Aij to obtain m * n p-dimensional vectors, m p-dimensional vectors are obtained after the light of the n channels passes through n channel multiplexing (wavelength division multiplexing, polarization multiplexing, mode multiplexing and the like and multi-dimensional multiplexing), and m * n p-dimensional vectors are obtained. And then detection is carried out, and large-scale matrix-vector multiplication calculation Y = AX is realized.

Embodiments of the present disclosure are directed to a photonic implementation of a processor for keys update and hash generation for digital currency (e.g., bitcoin) transactions. The processor includes a first photonic circuit and a second photonic circuit coupled to the first photonic circuit via a set of optical connections. The first photonic circuit is configured to generate a plurality of new messages based at least in part on a plurality of input messages. During a plurality of operational cycles, the second photonic circuit is configured to receive, from the first photonic circuit via the set of optical connections, the plurality of new messages, and update a plurality of keys based at least in part on the received plurality of new messages. The second photonic circuit is further configured to generate at least one hash value based on the plurality of keys generated after the plurality of operational cycles.

A photonic parallel network can be used to sample combinatorially hard distributions of Ising problems. The photonic parallel network, also called a photonic processor, finds the ground state of a general Ising problem and can probe critical behaviors of universality classes and their critical exponents. In addition to the attractive features of photonic networks—passivity, parallelization, high-speed and low-power—the photonic processor exploits dynamic noise that occurs during the detection process to find ground states more efficiently.

The exponential growth in deep learning models is challenging existing computing hardware. Optical neural networks (ONNs) accelerate machine learning tasks with potentially ultrahigh bandwidth and nearly no loss in data movement. Scaling up ONNs involves improving scalability, energy efficiency, compute density, and inline nonlinearity. However, realizing all these criteria remains an unsolved challenge. Here, we demonstrate a three-dimensional spatial time-multiplexed ONN architecture based on dense arrays of microscale vertical cavity surface emitting lasers (VCSELs). The VCSELs, coherently injection-locked to a leader laser, operate at gigahertz data rates with a 7T-phase-shift voltage on the 10-millivolt level. Optical nonlinearity is incorporated into the ONN with no added energy cost using coherent detection of optical interference between VCSELs.

The invention provides an optical interconnection structure based on an optical chip, and relates to the technical field of microwave photonics. The optical interconnection structure comprises an input optical fiber array used for inputting optical signals; the front-end optical chip is provided with a plurality of input ports and a plurality of output ports and is used for processing optical signals, and the input ports of the front-end optical chip are correspondingly connected with the input optical fiber array; one end of the interconnected optical fiber array is correspondingly connected with a plurality of output ports of the front-end optical chip, and the interconnected optical fiber array is used for transmitting the processed optical signals; the rear-end optical chip is provided with a plurality of input ports and a plurality of output ports and is used for carrying out secondary processing on the processed optical signals, and the input ports of the rear-end optical chip are correspondingly connected with one end, far away from the front-end optical chip, of the interconnected optical fiber array; and the output optical fiber array is correspondingly connected with a plurality of output ports of the rear-end optical chip and is used for outputting the secondarily processed optical signals.

The invention provides a photon parallel matrix convolution operation chip which can be applied to the technical field of integrated photonics and optical calculation. The chip is integrated by a 1 * N array waveguide grating, a 1 * 2 beam splitter array, an input matrix modulator array, two N * 1 array waveguide gratings, two 1 * N beam splitters, a weight matrix modulator array, an M * M array waveguide grating detector array and a detector array. Main functional devices are integrated in a monolithic mode, the system is compact, the complexity and power consumption of the system can be effectively reduced, and the calculation efficiency is improved.

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 relates to an energy-calculation integrated optical calculation chip element based on a photovoltaic effect and a preparation method and application thereof, and relates to the technical field of optical calculation and photovoltaics. The component comprises a substrate layer, a conductive electrode, a conductive contact piece, a flexural photovoltaic layer and a photoinduced strain layer, light energy entering the flexural photovoltaic layer is converted into electric energy due to the photovoltaic effect, and the photoinduced strain layer in physical contact with the flexural photovoltaic layer is irradiated by a special light beam to generate strain. The strain of the photoinduced strain layer enables the flexural photovoltaic layer in contact with the photoinduced strain layer to generate local strain regulated and controlled by a light beam, and photocurrent generated by the flexural photovoltaic layer due to a photovoltaic effect is subjected to strain regulation and control due to local strain gradient of a material. Compared with the prior art, the element integrates a photovoltaic effect and an optical calculation function, can simultaneously realize conversion from optical energy to electric energy and electric signal output of an optical calculation result through a single element, is a new generation of energy-calculation integrated optical calculation element, and can be used as a core calculation element of a green low-carbon chip.

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.

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 relates to the field of optical chips, photoelectric fusion calculation and image recognition, and discloses an image processing acceleration method, system, chip and device based on photoelectric fusion, and the method comprises the following steps: receiving input image data, and transmitting the input image data to an FPGA chip; the invention also discloses a system which comprises the components of an upper computer which is used for receiving input image data and transmitting the input image data to the FPGA chip; the FPGA chip is used for converting a received digital signal into an analog signal and carrying out feature extraction and high-dimensional mapping through the optical chip; the invention also discloses a chip which comprises an optical calculation module configured to perform image feature extraction and high-dimensional mapping. According to the invention, the photoelectric fusion technology is combined with optical calculation and electronic calculation, so that the image processing speed, accuracy and energy efficiency are improved; feature extraction is accelerated by adopting an echo state network, and the calculation complexity is reduced; and meanwhile, through cooperative work of the FPGA and the GPU, data processing is optimized.

Described herein are embodiments of a photonic computing system comprising one or more processors in communication with disaggregated memory through one or more optical channels. The disaggregated memory comprises multiple memory units placed on a photonic substrate that includes a photonic network that can be programmed to configure which of the memory units can be accessed by each of the processor(s). The disaggregated memory includes a memory controller for reading and writing data to / from the memory units. The memory controller may be configured to perform processing in concert with the processor(s).

The embodiment of the invention discloses a photovoltaic power characteristic difference prediction method and system under different weather conditions and a medium. The method comprises the following steps: determining thermodynamic diagram data carrying dust type distribution information according to particle size analysis data; determining airflow turbulence characteristic parameters based on the three-dimensional velocity field data and the pressure distribution data; constructing a dust removal effect model according to the thermodynamic diagram data and the airflow turbulence characteristic parameters, and establishing a mapping relation between turbulence intensity and a dust removal effect; a power recovery speed prediction model is constructed according to the power output data of the photovoltaic panel under different dust removal effects, and a mapping relation between the dust removal effects and the power recovery speed is established; constructing a quantitative relation model under the severe convection weather condition based on the mapping relation; and according to the quantitative relation model and a preset photovoltaic power prediction model under a non-severe convection weather condition, constructing a photovoltaic power characteristic difference prediction model to perform photovoltaic power prediction under different weather conditions, thereby realizing accurate prediction of power recovery of the photovoltaic power station under severe convection weather.

A calculation device of the present disclosure is characterized by implementing an item, which expresses a magnetic field, at each site by adding, to the conventional coherent Ising machine, a function for simulating the magnetic field item. Specifically, light having the amplitude of a predetermined sign is input in the conventional coherent Ising machine by dislocating an operation point of the push-pull-type optical modulator. When the operation point is dislocated to a + direction, DOPO (Degenerate Optical Parametric Oscillator) having the same wavelength as that of DOPO of an optical resonator and having a fixed initial phase difference from pump light into which the light is injected considerably tends to oscillate at 0 phase, and becomes reversed when the operation point is dislocated to a minus direction.

The invention relates to the field of computer vision and artificial intelligence, and discloses an image classification method and system based on a photoelectric hybrid computing architecture, and the method comprises the following steps: receiving and preprocessing an input image, and carrying out the optical transformation of the image through optical diffraction calculation to extract optical features, the extracted optical features are converted into electric signals through a photoelectric conversion module; the electronic neural network module receives the data after photoelectric conversion, and performs feature extraction and classification prediction by using a convolutional neural network; and finally, classification loss is calculated through a loss calculation and optimization module, and neural network parameters are adjusted by using an optimization algorithm so as to improve classification precision. According to the method, optical calculation and electronic calculation are combined, the electronic calculation burden is reduced, the calculation efficiency is improved, the power consumption is reduced, and meanwhile, the method is compatible with an existing deep learning framework and is suitable for multiple application scenes such as large-scale data classification and real-time target recognition.

The invention discloses an optical calculation error adjustment method and system, a medium and a program product, and relates to the technical field of optical calculation, and the method comprises the steps: determining a unified correction deviation value corresponding to the phase noise of an interferometer array; a target function based on a correction deviation direction variable is generated with the minimum difference sum of squares between a measured light intensity value of the photoelectric detector array and an ideal light intensity value as a target; solving the objective function to obtain the optimal value of the correction deviation direction variable of each phase shifter; and sending the correction deviation direction variable optimal value and the unified correction deviation value of each phase shifter to control equipment, so that the control equipment adjusts each phase shifter at the same time. In this way, collective adjustment of all the phase shifters can be realized through the determined unified correction deviation value and in combination with the correction deviation direction variable optimal value of each phase shifter, extra overhead caused by independent calibration is avoided, complexity of light calculation noise mitigation is reduced, a noise mitigation process is accelerated, and output precision of light calculation equipment is improved.

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.

A method of operating an optical Fourier transform 'OFT' apparatus, the OFT apparatus comprising N input channels and K output channels, the method comprising: quantising the light at the input channels to form a quantised output at each output channel.

Systems and methods for increasing throughput of a photonic processor by using photonic degrees of freedom (DOF) are provided. The photonic processor includes a multiplexer configured to multiplex, using at least one photonic DOF, multiple encoded optical signals into a multiplexed optical signal. The photonic processor also includes a detector coupled to an output of an optical path including the multiplexer, the detector being configured to generate a first current based on the multiplexed optical signal or a demultiplexed portion of the multiplexed optical signal. The photonic processor further includes a modulator coupled to and output of the detector, the modulator being configured to generate a second current by modulating the first current.

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.

A large-scale distributed photoelectric intelligent computing system, including: a diffractive compression encoder, configured to collect two-dimensional light field information through a grating array, convert the two-dimensional light field information into one-dimensional information through waveguide transmission and transmit the one-dimensional information to a first diffractive region, and perform computing using a diffractive coding weight to output a one-dimensional vector through an output end of the first diffractive region; a reconfigurable interference feature embedder consisting of an interferometer array composed of a plurality of thermo-optical phase modulators, in which the interferometer array is configured to perform a multiplication operation on the one-dimensional vector, to output a computed result in a one-dimensional vector form; and a diffractive decoder, configured for diffractive decoding the computed result in the one-dimensional vector form through a second diffractive region, to compute and output final light field information through a diffractive decoding weight.

Systems and methods for optical multiplication are disclosed. In one arrangement, a first modulator comprising rows and columns of first modulator elements is configured to spatially modulate light received from a deflector. The first modulator encodes values of a first matrix. The first matrix defines a plurality of input vectors each corresponding to a respective row of the first matrix. A second modulator spatially modulates light received from the first modulator and encodes values of a second matrix in rows and columns of second modulator elements. A light-summing optical arrangement converges light output from each row of second modulator elements to encode a plurality of output vectors representing the results of vector-matrix multiplication between a respective plurality of the input vectors and the second matrix.

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 discloses a renewable energy source data clustering method and system based on an optical quantum computer, and the method comprises the steps: building a renewable energy source data clustering optimization problem based on a quadratic unconstrained binary optimization (QUBO) model based on a discrete optimization objective function, carrying out the matrix of the objective function, carrying out the clustering optimization of the objective function through a kernel method, and carrying out the clustering optimization of the objective function. The method comprises the following steps of: establishing a target function item, converting the target function item into a matrix form, constructing a matrix of a new clustering model, finally solving a new QUBO optimization problem by using CIM, and converting the new QUBO optimization problem into an optimal clustering result. According to the method, data similarity measurement is improved by constructing the QUBO model and combining a kernel method, and a renewable energy source data clustering problem is converted into a form suitable for CIM solution, so that the calculation bottleneck of a classical calculation method in high-dimensional data processing is avoided. According to the method, the nonlinear characteristic of the data can be kept, efficient clustering optimization calculation can be realized, and the calculation efficiency and the clustering precision are remarkably improved.

The present invention relates to the technical field of optical analog computing, and specifically provides a planar micro-nano optical analog computing device. A planar micro-nano optical element includes a micro-nano structure. By adjusting a physical parameter of the micro-nano structure, the planar micro-nano optical element corresponds to different transfer functions at different resonance wavelengths, and a relationship curve between the transfer function and an incident wave vector at different resonance wavelengths is rectangle bandpass filtering functions with different bandwidths. According to the present invention, based on the planar micro-nano optical element, required transfer functions at different wavelengths are designed, so that a wavelength-controlled two-dimensional multi-channel image optical analog computing device with a high numerical aperture and insensitive polarization can be implemented, and differential image processing can be performed on target objects with different structural sizes selectively.

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.

An optical computing device includes: one or more light-diffraction elements each of which includes microcells, wherein each of the microcells has an individually set thickness or refractive index; and an optical signal input section that simultaneously inputs an optical signal and a delayed optical signal obtained by delaying the optical signal to the one or more light-diffraction elements.