The invention discloses a rapid biological cell classification imaging method and system based on a quantum correlation diffractionoptical neural network, and the method comprises the steps: regulating and controlling a signalphoton to an orbital angular momentum state optimized by a neural network based on a time-energy correlation two-photon pair generated in a spontaneous parametric down-conversion process, and irradiating a biological cell sample; a diffractive optical neural network is utilized to construct a quantum state illumination diffractive optical processor, photons carrying cellcomplex amplitude information are mapped to different detection areas of a predefined image plane, and rapid and high-precision cell classification and recognition are realized through correlation imaging results of an enhanced charge coupled camera. The method has the signal-to-noise ratio and anti-interference capability exceeding the classic limit, can keep high-precision cell classification capability under high background noise, and is suitable for long-time monitoring of living cells under the condition of extremely low light intensity. The method has the characteristics of low energy consumption and high efficiency, and meets the requirements of green calculation and sustainable development. And the method can be used for rapidly classifying and identifying the living biological cells without marks and phototoxicity.
An optical processor and a method for optically processing data are described herein. The optical processor may comprise an optical pulse generator, an optical memory, and optical logic. The optical pulse generator may be configured to generate an optical interrogation pulse. The optical memory may comprise one or more memory cells. Each memory cell may comprise a phase-change material. The optical memory may be configured to direct the optical interrogation pulse at memory cells thereby generating optical readout pulses. Each optical readout pulse may correspond to a state of the phase-change material in the memory cells thereby encoding data stored in the memory cells. Each optical readout pulse may be directed to the optical logic. The optical logic may be configured to perform at least one logical operation on the data based on the readout pulses.
The present disclosure discloses an optical signal amplification apparatus, method, and optical communicationsystem, the optical signal amplification apparatus including a first optical processor, a second optical processor, a third optical processor, a fourth optical processor, and a transmission optical fiber, wherein the fourth optical processor receives second pump light and third pump light and multiplexes the second pump light and the third pump light to form a first mixed pump light, the third optical processor receives the first pump light, the second optical processor receives the first pump light and the first mixed pump light and multiplexes the first pump light and the first mixed pump light to form a second mixed pump light, the first optical processor receives the second mixed pump light and fourth pump light and multiplexes the second mixed pump light and the fourth pump light to form a third mixed pump light, and the transmission optical fiber receives a full-band service optical signal and the third mixed pump light and amplifies an optical signal of at least one wavelength band of the service optical signal based on the third mixed pump light.
The present disclosure relates to central units and remote units. One example central unit includes at least one digital-to-analog converter (DAC), at least one first electro-optical converter configured to convert an analog electrical signal output by the DAC into an analog optical signal, at least one first optical processor configured to process the analog optical signal output by the first electro-optical converter, where the first optical processor includes at least one of at least one first optical filter, at least one first optical phase shifter, and at least one first optical poweramplifier, a first multiplexer configured to combine analog optical signals output by the first optical processor into one analog optical signal, and a first demultiplexer configured to decompose the one analog optical signal into multiple analog optical signals at different wavelengths.
A photonic image rejection radio frequency (RF) mixer and a receiver implementing the same may suppress undesired mirror image signals having frequencies at a spectral location that is mirror-symmetric, with respect to a local oscillator (LO), to that of a signal of interest. An upconverted optical beam corresponding to a captured RF beam is extracted by an optical processor. The upconverted optical beam is mixed with the LO to obtain a desired composite optical signal and an undesired composite optical signal, each providing a corresponding beat frequency optical signal at the same frequency. The desired and undesired composite optical signals are captured by multiple optical pickups with relative phase shifts in their beat frequency optical signals which are converted into corresponding electrical signals and combined to suppress the undesired signal.
The invention relates to an optical processor (2), in particular to an optical interferometer, comprising: a plurality of processor input ports (5.1 to 5.4) for receiving input optical signals (4.1 to 4.4), a plurality of processor output ports (6.1 to 6.4) for emitting output optical signals (7.1 to 7.4), and an optical network (9) that connects the processor input ports (5.1 to 5.4) to the processor output ports (6.1 to 6.4) and comprises at least one layer (11) with a plurality of optical devices (10a-c) configured to process the input optical signals (4.1 to 4.4) from the processor input ports (5.1 to 5.4). The at least one layer (11) has a plurality of input ports (14.1 to 14.4) and a plurality of output ports (15.1 to 15.4) that are connected to the plurality of input ports (14.1 to 14.4) via optical delay lines (16.1 to 16.4). The invention also relates to an apparatus (1), comprising: an optical processor (2) as indicated above, a plurality of light sources (3.1 to 3.4) for generating the plurality of input optical signals (4.1 to 4.4) for the optical processor (2), and a plurality of optical detectors (8.1 to 8.4) for detecting the output optical signals (7.1 to 7.4) from the optical processor (2).
Amplitude-only Fourier optical processors is capable of processing large-scale matrices in a single time-step and microsecond-short latency. The processors may have a 4f optical system architecture and may employ reprogrammable high-resolution amplitude-only spatial modulators, such as Digital Micromirror Devices (DMD). In addition, methods are provided for obtaining amplitude-only electro-optical convolutions between large matrices displayed by the DMDs. The large matrices on which convolution is performed may be feature maps corresponding to images and kernel matrices used in neural networks classification systems. Analog optical convolutional neural networks are also provided that perform accurate classification tasks on large matrices. In addition, methods are provided for off-chip training the analog optical convolutional neural networks. The training includes building an accurate physical model for the analog optical processor and performing computer simulations of the optical processor according to the physical model. The methods do not need to employ any interferometric scheme.
A semiconductor photonic integrated circuits (PICs) may perform RF signalprocessing, including beamspace processing or spatial Fourier Transforms in a semiconductor PIC. An RF imaging system including the semiconductorprocessing PIC may include an antenna array that upconverts RF signals to optical signals using electro-optic modulators, such as lithium niobate modulators. Simultaneous processing (beamforming) of multiple RF signals utilizing the semiconductor processing PIC may be performed.
A parallel optical computingsystem is described, the system comprising: at least one first module (10) comprising at least one polarizing filter (12) and at least one liquid crystalcell (13), the first module (10) configured as an optical modulator (100) for receiving light from a light source (70) and encoding the light output from the liquid crystalcell (13) as optical data to be processed; at least one second module (20) comprising at least one polarizing filter (22) and at least one liquid crystalcell (23), the second module (20) configurable as an optical processor (200) for receiving the optical data to be processed and outputting processed optical results; at least one optical detector (40) designed to receive the processed optical results and convert the optical results into corresponding electrical results.
In-network Optical Inference (IOI) provides low-latency machine learning inference by leveraging programmable switches and optical matrix multiplication. IOI uses a transceiver module, called a Neuro Transceiver, with an optical processor to perform linear operations, such as matrix multiplication, in the optical domain. IOI's transceiver modules can be plugged into programmable packet switches, which are programmed to perform non-linear activations in the electronic domain and to respond to inference queries. Processinginference queries at the programmable packet switches inside the network, without sending them to cloud or edge inference servers, significantly reduces end-to-end inference latency experienced by users.
A parallel optical computingsystem is described, said system comprising:at least one first module (10) comprising at least one polarization filter (12) and at least one liquid crystalcell (13), the first module (10) being configured as an optical modulator (100) for receiving light from a light source (70) and for encoding the light output from the liquid crystalcell (13) into optical data to be processed;at least one second module (20) comprising at least one polarization filter (22) and at least one liquid crystalcell (23), the second module (20) being able to be configured as an optical processor (200) for receiving the optical data to be processed and for outputting an optical result of the processing;at least one optical detector (40), designed to receive the optical result of the processing and convert the optical result into a corresponding electrical result.
Example optical signalprocessing apparatuses and methods are provided. One example apparatus includes: N light sources, a wavelengthmultiplexer, an optical processor, a dither application circuit, a first detection circuit, a second detection circuit, and a feedback control circuit. The light source generates a single-wavelengthsignal. The dither application circuit applies a dithersignal to the light source. The wavelengthmultiplexer generates a multi-wavelength signal based on the single-wavelength signal. The first detection circuit is configured to obtain a first power signal of a signal input to the optical processor. The second detection circuit is configured to obtain a second power signal of a signal output from the optical processor. The feedback control circuit adjusts a working parameter of the optical processor based on the dither signal corresponding to the single-wavelength signal, the first power signal, and the second power signal.