184results about "Digital data" patented technology

An optical computation system includes a light source configured to produce a pump beam, an optical modulator configured to modulate the pump beam based on the modulation mask to generate a modulated beam, a non-linear medium configured to convert a portion of the modulated beam to a second harmonic (SH) beam and to produce an output including the SH beam and an unconverted portion of the pump beam, and a dichroic mirror configured to receive the output of the non-linear medium and to decouple the SH beam and the unconverted portion of the pump beam, a detector configured to detect a first optical power of the unconverted portion of the pump beam and to detect a second optical power of the SH beam, and a controller configured to generate an updated modulation mask based on the first and second optical powers for transmission to the optical modulator.

The invention relates to the field of photoelectric hybrid computing, and discloses an inter-chip data transmission processing method based on a photoelectric hybrid architecture, which comprises the following steps of: converting an electric signal into an optical signal through a high-speed SerDes interface by virtue of cooperative work of an electric chip and an optical chip, and performing high-speed data processing and computing by utilizing an optical device in the optical chip, the processed optical signal is converted into an electric signal through a photoelectric converter, and the electric signal is returned to an electric chip for subsequent calculation; through the photoelectric hybrid architecture, the electric chip focuses on complex calculation tasks, and the optical chip is responsible for high-speed data transmission and primary processing, so that the data transmission efficiency and the calculation performance are remarkably improved, and the power consumption of the system is reduced. The method can effectively improve the performance in a large-scale parallel computing task, has lower energy consumption and higher transmission efficiency, and is particularly suitable for the fields of high-performance computing, deep learning and the like.

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.

A method for topological design optimization in which a number of objective scattering(S) parameters are initially decomposed into a product of smaller devices (primitives). Each of the primitives are optimized in parallel using inverse design; and the topologies of the smaller devices are then composited into a final device design region, in which the final device design region is an initialization of a final optimization, advantageously saving computation time. According to at least one embodiment, the herein described optimization procedure can be utilized in order to design a composite power combiner that is essentially phase-insensitive.

A method for assembling a photonic computing system includes attaching a photonic source to a support structure, and attaching a photonic integrated circuit to the support structure. The photonic source includes a first laser die on a substrate configured to provide a first optical beam, and a second laser die on the substrate configured to provide a second optical beam. The photonic integrated circuit includes a first waveguide and a first coupler coupled to the first waveguide, and a second waveguide and a second coupler coupled to the second waveguide. The method includes attaching a plurality of beam-shaping optical elements to the support structure, the substrate, or the photonic integrated circuit, in which the attaching includes aligning a first beam-shaping optical element during attachment so that the first optical beam is coupled to the first coupler, and aligning a second beam-shaping optical element during attachment so that the second optical beam is coupled to the second coupler.

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 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.

An entangled quantum system can be generated using entanglement-generating circuits that operate non-deterministically. Multiple instances of the entanglement generating circuit can be operated and outputs of successful instances can be propagated. The circuit can be implemented such that a photon that is part of the final output state passes through as few as one or two active switches from generation to the final output state.

The invention is directed to solving an optimization problem. The method operates a photonic crossbar array structure including N input lines and M output lines, which are interconnected at junctions via N×M photonic memory devices, where N≥2 and M≥2. The photonic memory devices are programmed to store respective weights in accordance with the optimization problem. The photonic crossbar array structure is operated as follows. First, the method determines values of L input vectors of N components each, where L≥2. Second, based on the determined values, N electromagnetic signals are generated, where each of the generated signals multiplexes L input signals encoded at respective wavelengths, so as for the N electromagnetic signals to map the L input vectors of N components each. Third, the N electromagnetic signals generated are applied to the N input lines of the photonic crossbar array structure.

A computing system may be provided. The computing system may include an optical memory cavity configured to store signal pulses representing a current combination for a combinatorial optimization computation. The computing system may further include an optical processing cavity. The optical processing cavity may be configured to receive the signal pulses from the optical memory cavity, perform an all-optical 1-bit delay computation on the signal pulses to generate a feedback pulse for at least one signal pulse, and provide the feedback pulse to be coupled back to the optical memory cavity.

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.

A method and system for data processing. The method comprises the following steps: converting input data into optical signals (S1); performing a matrix-vector multiplication on the input data carried by the optical signals and a weight matrix using a plurality of photonic multipliers, wherein the weight matrix determines the problem to be solved by the data processing (S2); and converting the optical signals resulting from the multiplication into output data (S3). The method can be applied to systems and algorithms for solving the problems of data clustering, labeling, classification, and semantic segmentation. Using photonic multipliers for the most time-and energy-consuming matrix-vector multiplications can greatly reduce both computation time and energy consumption, resulting in faster processing speeds and improved energy efficiency.

The method comprises starting with a known layout of a universal optical mesh (such as Reck or Clements schemes) 200 wherein: the known layout of the universal linear optical mesh comprises: a plural

The application belongs to the technical field of chip packaging, and particularly relates to an optoelectronic combined optical computing system, which comprises a substrate, a first interlayer, at least one photonic chip, at least two second interlayers and at least two electronic chips; the second interlayers and the photonic chips are staggered on the upper surface of the substrate, a first gap is formed between the second interlayers and the photonic chips, the first interlayer covers the upper surfaces of the photonic chips and the second interlayers, and the electronic chips are arranged on the upper surface of the first interlayer. The application provides a "bridging type" three-dimensional packaging structure for a chip packaging structure (especially in the case that the size of the photonic chip is limited) with more complex functions or larger data processing capacity, which can improve the heat dissipation performance, dynamically optimize signal transmission according to task requirements, and comprehensively improve the performance, reliability and flexibility of the packaging structure.

Methods, circuits, devices, systems and techniques for photonic computing are provided. In one aspect, a method includes: detecting at least one modulated optical signal using a plurality of multi-tap photodetectors that include a first multi-tap photodetector, the at least one modulated optical signal representing one or more input elements of an input matrix of a mathematical function, the plurality of multi-tap photodetectors being modulated based on weight elements of a weight matrix of the mathematical function; and generating electrical outputs based on outputs of the plurality of multi-tap photodetectors using a control circuitry, the electrical outputs representing a computation result of the mathematical function corresponding to a multiplication of the input matrix and the weight matrix.

A method for operating a Fourier transform device, comprising: receiving an input vector signal comprising N elements each comprising P bits; generating, based on the input vector, a first and a second frame, wherein each of the first and second frames comprises M elements each comprising Q bits, wherein Q < P, wherein the optical Fourier transform device comprises M input channels; obtaining, using the optical Fourier transform device, a first Fourier transform of the first frame and a second Fourier transform of the second frame; and combining, to obtain an output signal comprising a Fourier transform of the input vector, a first part and a second part, wherein the first part is based on the first Fourier transform and the second part is based on the second Fourier transform.

A device for optical matrix-vector multiplication is provided. A x → = y → , encompassing: n * m optically coupled cells (i,j) (330, 331-399) representing the elements of an (n×m) matrix A, an input vector x → , whose components x i (221,222,223) are represented by n waveguides which are coupled to the rows of matrix A, forming an output vector y → whose components y j (231,232,233) are represented by m waveguides coupled to the columns of matrix A, wherein each cell (i,j) (330, 331-399) comprises an optical amplifier (400) configured to apply a weighting factor a ij to implement ∈[1;∞[.

An optical arrangement for generating a plurality of conditioned optical signals is presented. The optical device (305) includes at least one temporally incoherent light source (310) coupled to a plurality of amplitude modulators (341, 342). Each amplitude regulator is configured to attenuate or amplify an optical signal derived from the at least one temporally incoherent light source (310) to provide a corresponding regulated optical signal. An optical computing system is also presented that includes an optical arrangement coupled to a processing device having a plurality of inputs for receiving conditioned optical signals.

In an optical computing device in which a plurality of microcells provided in a matrix form are disposed so as to be stacked on each other, reduced are variations which occur in cell size and position due to dehydration and shrinkage. An optical computing device (10) includes a plurality of light diffraction layers (L1, L2, L3) stacked on each other. In the optical computing device (10), each light diffraction layer (L1, L2, L3) includes a plurality of microcells (Cijk) which have refractive indexes set individually and which are provided in a matrix form. The plurality of light diffraction layers (L1, L2, L3) are contained in a dried gel (11).

A method for performing a Fourier transform, comprising: receiving an input vector comprising N elements each comprising P bits; generating, based on the input vector, a first and a second frame, wher

We propose a hybrid wave-based logic model for optical computing that integrates both Total Wave Modified Schrödinger Equation (TWMSE) formulations and non-TWMSE interference field logic. This system enables deterministic collapse behavior through physical wave interactions, rather than relying on conventional transistor logic or probabilistic quantum models. In the TWMSE regime, collapse thresholds are governed by field interference between signal and control waves, allowing dynamic selection of tasks based on intensity and phase alignment. In the generalized non-TWMSE regime, similar collapse-like logic can be achieved using thresholded interference models that are classically engineered for optical domain systems. Together, these formulations enable adaptive task selection, nonlinear logic gating, and scalable parallel processing in optical chips. Our architecture supports real-time wavefield decisions and is compatible with standard photonic components such as interferometers, microring resonators, variable attenuators, and optical threshold comparators. The result is a unified logic framework for next-generation AI hardware that harnesses both quantum-inspired and classical wave interference dynamics.

The invention relates to the technical field of photoelectric data processing, provides a light wave chromatography computer coding method, system and architecture based on a toning principle, and aims to break through the performance bottleneck of traditional electronic calculation. According to the method, physical-level color processing is realized through color binary coding and light wave state discrete mapping based on an optical toning principle. The system integrates a digital input interface, a wavelength coding converter, a light wave operation core and a wavelength analysis unit, and supports efficient optical signal direct operation. On the architecture level, an extended von Neumann design is adopted, a three-level Clos-WSS optical interconnection network, a photon ALU and a PCM holographic main memory are included, and femtosecond-level delay, low power consumption and high parallelism are achieved. Advantages include physical level computational accuracy, nearly zero data handling energy consumption, and large scale wavelength level parallel processing. The method is suitable for 8K video real-time color modulation, industrial sorting and other high-requirement scenes, and a subversive solution is provided for the fields of automatic driving, digital twinning and the like.

The purpose of the present invention is to provide an optical computer having high scalability and capable of reducing noise. This optical computer is characterized by including: an input layer which accepts an input signal as a computer; a reservoir layer which responds to a signal input from the input layer, and in which using a plurality of degenerate optical parametric oscillator (DOPO) pulses of a DOPO that are generated by an optical phase-sensitive amplifier (PSA) based on pump light as nodes, a connection relation between the nodes is determined by a measurement feedback method or a method equivalent to the measurement feedback method; and an output layer which outputs an output signal based on the respective responses of the plurality of DOPO pulses to the input signal from the reservoir layer.

The disclosure provides for high bandwidth processing through the sharing of memory dies (104) over a plurality of computing dies (102) via an optical interchange (106). The optical interchange may be configured so as to operate as both an optical switch (108) and optical demultiplexer (107). The optical switch (108) configuration for the optical interchange (106) allows for data to be written from any computing die (102) to one of a plurality of memory dies (104) via an optical connection. The optical demultiplexer (107) configuration allows for data to be broadcast from a memory die (104) to a plurality of the computing dies (102).

A method for performing computations in a system having a matrix multiplication unit that converts an optical input vector to an analog output vector based on a plurality of weight control signals, the method comprising: receiving a computation request comprising at least one digital input vector and a first plurality of weights; storing the digital input vector and the first plurality of weights in a storage unit; generating a first plurality of modulator control signals based on the digital input vector, generating a first plurality of weight control signals based on the first plurality of weights; generating an optical input vector based on the first plurality of modulator control signals; obtaining a first plurality of digital outputs corresponding to the analog output vector, the first plurality of digital outputs forming a first digital output vector; performing, by the controller, a non-linear conversion on the first digital output vector to produce a first converted digital output vector; storing the first converted digital output vector in a storage unit; an output generated based on the first converted digital output vector is output by the controller.

A hybrid quantum-classical system for solving a binary optimisation problems with trainable probability values and parameters. The hybrid quantum-classical system comprises a boson sampler and a class

Systems and methods relate to selectively arranging a plurality of qubits into a spatial structure to encode a quantum computing problem. Exemplary arrangement techniques can be applied to encode various quantum computing problems. The plurality of qubits can be driven according to various driving techniques into a final state. The final state can be measured to identify an exact or approximate solution to the quantum computing problem.

In order to provide a spatial light phase modulator that can be miniaturized and that is operable at high speed, each microcell (C) of this spatial light phase modulator (13) is composed of a magnetization free layer (C11) and a control unit (electrode C12) that controls the magnetization direction (arrow M11) of the magnetization free layer (C11). The magnetization free layer (C11) and the control unit (electrode C12) are configured to control the magnetization direction (arrow M11) so as to be parallel or substantially parallel the direction (arrows kf, kr) of a normal to the first optical effective surface and the second optical effective surface (bottom surfaces C111, C112).