65 results about "Optical diffraction" patented technology

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 invention belongs to the field of molecular sieve material characterization, and particularly relates to a method for analyzing aluminum atom pairs in a ZSM-5 molecular sieve based on super-resolution fluorescence microscopic imaging, which comprises the following steps: activating a ZSM-5 molecular sieve sample; contacting the obtained sample with probe molecules; washing the ZSM-5 molecular sieve sample, and removing unbound or nonspecifically bound probe molecules; imaging the marked sample by using a super-resolution fluorescence microscope to obtain an image sequence containing a single fluorescent molecule emission event; processing the image sequence, determining a space coordinate of each fluorescence event, and reconstructing a super-resolution fluorescence image exceeding an optical diffraction limit; and based on the space coordinates of the fluorescent dots in the super-resolution fluorescence image, carrying out statistics to obtain the position, surface density or distribution information of the aluminum atom pairs in the ZSM-5 molecular sieve. According to the method disclosed by the invention, nanoscale spatial resolution, direct imaging and quantitative analysis of Al-pair in ZSM-5 (Zeolite Socony Mobil-5) can be realized.

The invention discloses a space customization three-dimensional column vector light beam array generation method based on a metasurface, and belongs to the field of micro-nano optics, diffraction optics and structured light field regulation and control. The implementation method comprises the following steps of: independently regulating and controlling left-hand circular polarization and right-hand circular polarization components of incident light based on geometric and propagation phase joint modulation of the metasurface; a metasurface, a phase distribution coding lens factor of a polarization channel, a Dammann vortex grating with opposite basic topological charges and a spiral Dammann zone plate are independently optimized, and left-handed and right-handed circular polarization components generate a three-dimensional vortex beam array with opposite spatial topological charges in a near-field Fresnel domain; the left-handed circular polarization vortex array and the right-handed circular polarization vortex array with opposite topological charges are coherently superposed to form a spatially customized three-dimensional column vector light beam array, and the vector characteristic of each light beam in the array depends on the amplitude ratio, the phase difference and the topological charges of the left-handed circular polarization component and the right-handed circular polarization component on each diffraction order. According to the invention, the regulation dimension of the column vector light beam can be expanded.

The invention relates to the technical field of microscopic imaging, and discloses a multi-level physical model and double-domain deep learning structured light illumination imaging reconstruction method, which comprises the following steps: firstly, constructing a multi-level physical degradation model based on illumination light field modulation, optical diffraction sensor discrete sampling and photoelectric noise, and generating a simulation data set containing random errors; then constructing a deep neural network containing spatial domain and frequency domain branches, and performing iterative training on the network by using a joint loss function; and finally, acquiring an original structured light stripe image of a real sample, inputting the original structured light stripe image into the trained model to execute end-to-end reasoning, and outputting a super-resolution fluorescent microscopic image. According to the method, the problem of obtaining real pairing training data is solved through physical simulation, high-frequency detail recovery is enhanced by utilizing frequency domain constraint, reconstruction artifacts are effectively removed, the imaging resolution is improved, and the spatial resolution and edge sharpness of a reconstructed image are improved while the ringing effect and background noise are effectively suppressed.

Microscopy imaging that allows for multiple mRNAs, proteins and metabolites to be spatially resolved at a subcellular level provides valuable molecular information which is a crucial factor for understanding tissue heterogeneity as for example within the tumor micro environment. The current invention describes a method (High Density-SUMI-Seq) which combines the use of Spatial Unique Molecular Identifier in situ localization and identification (by in situ sequencing or sequential fluorescence hybridization) of rolonies derived from rolling circle amplification of circular oligonucleotides and in vitro sequencing of target amplified RNA or DNA in combination with SUMI identification at a subcellular level with no optical diffraction limitation in the amount of amplified target information that can be analyzed per cell. Apart from amplified RNA or DNA, the High Density-SUMI-Seq method can also be applied using linear oligonucleotides to spatially resolve proteins and metabolites to provide multiomics results.

The invention discloses a multi-wavelength channel diffraction neural network system based on threshold screening and a processing method, and belongs to the technical field of artificial intelligence and optical computing. Comprising an encoding module used for encoding task information corresponding to different to-be-processed tasks to multiple light beams with different working wavelengths output by a light source module to form multiple task channel light fields; the optical diffraction module comprises a plurality of modulation layers; the optical diffraction module is used for receiving the task channel light fields and realizing diffraction modulation and threshold screening of the task channel light fields by changing the metasurface structures on different modulation layers; each task channel light field shares the same set of diffraction modulation parameters, namely parameters such as phase, mask generation and threshold; threshold screening: comparing the mask generation parameter with a threshold parameter, performing binarization selection on the phase parameter according to a comparison result, and screening out a target phase parameter; the output detection module detects the output light intensity. Task channels are expanded, and the system integration degree is improved.

The invention provides a multi-site adaptive optical correction method and device applied to a mesoscopic two-photon scanning microscope, and the method comprises the steps: employing a resonance mirror and two galvanometers as a scanning module of a system, dividing a whole imaging view into a plurality of sub-regions, and carrying out the sequential scanning of the sub-regions one by one; a reflective deformable mirror is used as an aberration compensator, and an aberration compensation value is updated in real time; the whole visual field is filled with a regular hexagon, the center and vertex positions of the regular hexagon are set as aberration compensation points, and a reflective deformable mirror is used for carrying out aberration correction on the compensation points in advance; and automatically loading an optical aberration compensation value closest to the center of the sub-region according to the central coordinate position of the sub-region so as to ensure that the image resolution near the optical diffraction limit is kept in the whole view region.

This invention discloses a laser projection display method and system. The method involves configuring the micromirrors of a phase-modulated light device into a high-low periodic structure. Then, based on optical diffraction characteristics, the actual height of the phase-modulated light device under each stage of driving signals is measured. Next, an ideal height set for the micromirrors is defined, which changes linearly with the progressively increasing driving signals. The actual heights that are within a defined error range from the actual heights are identified. These actual heights are matched with the phase level to establish an approximately linear relationship between the driving signal and the changeable phase level. This allows the driving signal to be sent according to the desired linearized height distribution in subsequent designs, achieving an approximately linear adjustment relationship between the change in the actual micromirror position and the change in the ideal micromirror position, thereby improving the dynamic contrast adjustment effect.

A machine vision task, machine learning task, and / or classification of objects is performed using a diffractive optical neural network device. Light from objects passes through or reflects off the diffractive optical neural network device formed by multiple substrate layers. The diffractive optical neural network device defines a trained function between an input optical signal from the object light illuminated at a plurality or a continuum of wavelengths and an output optical signal corresponding to one or more unique wavelengths or sets of wavelengths assigned to represent distinct data classes or object types / classes created by optical diffraction and / or reflection through / off the substrate layers. Output light is captured with detector(s) that generate a signal or data that comprise the one or more unique wavelengths or sets of wavelengths assigned to represent distinct data classes or object types or object classes which are used to perform the task or classification.

The application provides a video image fast clipping and dimension reduction method and system based on a hierarchical bounding box, applied to the technical field of image processing, wherein the method collects multi-view dynamic scene point cloud data, and then divides the space by using a hierarchical bounding box to establish a bounding box structure with density characteristics; subsequently, optical diffraction array pre-filtering is used, and point clouds are separated based on wavelength selectivity and density distribution to generate a first subset and a background subset; then, adaptive pulse code modulation is used on nodes in the first subset to obtain high-precision data, and nodes in the second subset are compressed into low-code-rate data by using run-length encoding; subsequently, the two types of data are input into an improved k-d tree based on the spatial relationship of the bounding box to generate a two-dimensional point set representing key features, and a spatial index is constructed to realize real-time scene retrieval. The application can realize image dimension reduction while retaining key geometric features of the image, thereby improving efficient real-time spatial retrieval in a dynamic scene.

The application is suitable for the technical field of optical devices, and provides an optical assembly, a laser and a laser processing device. The optical assembly comprises, in sequence along an outgoing light direction, a resonant cavity, an optical diffraction element, a frequency doubling crystal and a Q switch. The resonant cavity is used for emitting a light beam. The optical diffraction element is used for homogenizing the light beam. The frequency doubling crystal is used for modulating the frequency of the light beam. The Q switch is used for adjusting the direction of the light beam to control whether the light beam is emitted. The resonant cavity, the optical diffraction element, the frequency doubling crystal and the Q switch in the embodiment of the application are arranged in sequence along the outgoing light direction, so that the stability of the light beam emitted from the Q switch can be improved.

The application provides an image recognition simulation model and system, the image recognition simulation model comprising: an optical diffraction neural network for a handwritten digit recognition task, the optical diffraction neural network comprising: an input layer, a diffraction layer and an output layer; the input layer modulates incident light into a wavefront array carrying image information; the diffraction layer performs multiple diffractions on the light output by the input layer to simulate a convolution weight matrix, and adjusts a phase distribution in a manner of error back propagation; and the output layer generates a focused light spot corresponding to the number of categories, the focused light spot focusing on a number corresponding to a plurality of detection points, and a detection surface light spot intensity distribution of the focused light spot is used to represent a classification probability. Through nano structure design, high degree of freedom regulation of light field amplitude, phase and polarization is realized in a two-dimensional plane; meanwhile, through multi-layer cascading extension network depth, feature abstraction capability is improved, nonlinear mapping is realized through multi-layer cascading diffraction, and a classification light intensity distribution is directly output, and the light intensity distribution represents a classification result.

The application relates to a parallel three-dimensional gray-scale laser direct writing lithography method based on a rotating mirror, wherein the method comprises the following steps: generating a writing laser through a writing laser; generating a multi-channel writing light beam according to an optical diffraction device and the writing laser; generating three-dimensional gray-scale writing data according to a two-dimensional gray-scale image of a structure to be written; splitting and writing the three-dimensional gray-scale writing data into different output channels of a waveform generator based on a rotating mirror parallel writing algorithm and the number of the multi-channel writing light beams; when a displacement table moves to a target position, controlling the switching or amplitude modulation of each corresponding channel of a multi-channel acousto-optic modulator by using the three-dimensional gray-scale writing data of the different output channels of the waveform generator, and completing parallel writing of the structure to be written. Through the application, the problem that obvious step phenomena easily occur during three-dimensional laser writing in the related art is solved, the three-dimensional laser writing speed is improved, and the obvious step phenomena during three-dimensional laser writing are eliminated.

The application discloses a kind of spatial diffraction deep neural network asymmetric multifunctional imaging method and system, it is suitable for optical signal processing field.The system is composed of signal input module, all-optical diffraction neural network module and signal acquisition module.Signal input module is responsible for providing light source and modulation element, for generating and modulating optical field signal.All-optical diffraction neural network module uses double loss function optimization strategy to carry out asymmetric training.Specifically, it introduces different loss functions in different transmission directions to train different functions simultaneously, thereby realizing the diversification of signal processing.Signal acquisition module is responsible for collecting and storing the final calculation result.The application can realize different imaging functions according to the different signal input directions, thereby adapting to the diversification needs of optical signal processing, not only filling the gap in the related field, but also providing a new way of thinking for further research and application in the field of optical imaging.

The invention provides a lensless amplitude phase imaging method and system suitable for axial scanning of polychromatic light. The method comprises the following steps: respectively acquiring diffraction data of an optical diffraction element and sample diffraction data at different positions through a lensless imaging device; randomly selecting a sample plane, transmitting a probe function of the optical diffraction element plane to the sample plane, transmitting a transmission function of the sample plane to a detector plane, and updating the transmission function through sample diffraction data; reversely transmitting the updated transmission function back to the sample plane, respectively updating the probe function and the object function of the sample, and transmitting the probe function back to the optical diffraction element plane; transmitting the probe function to a detector plane, performing amplitude constraint on the probe function by using diffraction data of the optical diffraction element, and then transmitting the probe function back to the plane of the optical diffraction element; and repeating the above steps to complete iteration, and finally obtaining a structure diagram through reconstruction. According to the invention, data volume is reduced and imaging quality is improved.

This invention relates to a polarization-customized holographic device based on a spin-decoupled plasmonic metasurface, belonging to the fields of micro-nano optics, diffraction optics, and holographic imaging. The device employs a three-layer metal-dielectric-metal reflective structure, consisting of a bottom metal reflective surface, an intermediate dielectric spacer layer, and a top anisotropic metaatomic layer. The top metaatomic layer is composed of various periodically arranged metaatoms. By superimposing the propagation phase and geometric phase, phase decoupling between left-handed circular polarization (LCP) and right-handed circular polarization (RCP) is achieved, allowing independent control of their phase delays. Precise customization of the output linear polarization direction is achieved by adjusting the phase difference between the two. This invention breaks the lock-in relationship between geometric phase and spin state in existing metasurface holographic devices, achieving highly integrated, high-quality polarization-customized holographic imaging. It exhibits stable performance over a wide spectral range and large incident angles, and can be widely applied in optical encryption, secure displays, and optical communications.

The invention discloses an all-optical diffraction neural network gesture recognition method for a three-dimensional space, belongs to the technical field of crossing of optical calculation and artificial intelligence, and aims to solve the problems of insufficient generalization ability and recognition failure caused by the fact that an existing all-optical diffraction neural network cannot adapt to imaging scale zooming and defocusing effects caused by target movement in the three-dimensional space. The method comprises the following steps: step 1, constructing a physical model and setting parameters of the physical model; 2, establishing a three-dimensional space imaging geometric mapping relation; step 3, dynamic modeling of an input layer light field; 4, calculating light field propagation from the dynamic imaging surface to a first diffraction layer of the D2NN diffraction layer; 5, carrying out network structure constraint and forward propagation; step 6, detector layer signal extraction and category determination; and step seven, D2NN diffraction layer training and parameter optimization are carried out. According to the invention, the problem of identification failure is effectively solved; and the generalization ability and robustness of the all-optical diffraction neural network to a three-dimensional space dynamic target are significantly improved.

The invention discloses a binary mask plate design method of a three-dimensional structure, a binary mask plate and a manufacturing method, and relates to the field of mask plate production and manufacturing. The method comprises the following steps: S1, designing a graphic unit of which the resolution is smaller than that of an exposure machine in the flat panel display industry on a binary mask; s2, according to the parameters of the target three-dimensional structure, the light transmission amount required by the corresponding plane pattern on the binary mask is inversely calculated; s3, calculating the pattern unit arrangement density of each array small unit according to the light transmittance requirement; and S4, generating coordinates corresponding to each pattern unit according to the pattern unit arrangement density, and generating a gds pattern file required by photoetching. According to the invention, a micro three-dimensional structure is formed on the large-size panel display glass by using an optical diffraction principle. The method is simple, does not need to add special equipment, is compatible with an existing panel display exposure process, solves the problems that a traditional three-dimensional graph is low in manufacturing efficiency, high in cost and limited in size, enriches the optical design selection of the panel display industry, and has remarkable practical value and popularization prospects.

The invention discloses a multi-channel optical diffraction neural network image classification method based on inter-class similarity decomposition, and the method comprises the steps: calculating a class center vector through a pre-training network, constructing an inter-class similarity matrix, and decomposing a multi-class task into a plurality of sub-tasks; configuring an independent optical channel for each subtask, and generating a multi-channel coded word table; constructing a multi-channel optical diffraction neural network, and synchronously training each channel by adopting a joint loss function; during reasoning, a test image is propagated through a network, and a final classification result is obtained through coding word decoding. According to the method, decoupling and parallel optical calculation of multi-class tasks are realized, and the accuracy and expandability of the shallow optical diffraction neural network in multi-class classification are effectively improved.

The invention discloses a space in-orbit diffraction imaging no-reference global defocus measurement method and device, and belongs to the technical field of image quality assessment, and the method comprises the steps: determining the focusing step length of a coarse focusing stage and the focusing limit of a fine focusing stage of a camera; according to the focusing step length of the coarse focusing stage, taking a laboratory focusing result as an initial focusing position, and obtaining a coarse focusing continuous zooming image sequence before and after the initial focusing position; the obtained rough focusing continuous zooming image sequence is subjected to rapid preselection through information entropy and local variance detection, and the range of the optimal focal plane position of rough focusing is obtained; a fine focusing continuous zooming image sequence is obtained in the range of the coarse focusing optimal focal plane position; and finally determining the optimal focal plane position of fine focusing. The problem that the MTF index cannot be directly measured in the continuous focusing process is solved, and in-orbit focus fixing of the optical diffraction camera is achieved.

This invention discloses a training refractive modulation device and method that can adapt to visual axis deviation. Its structure includes a protective shell, a protective cover, a charging port, training glasses, and a charging base. The protective cover and protective shell slide together. The training glasses include a nose pad, an adjustable lens, a speaker, a charging head, a control terminal, temples, an adjustment rod, and a power switch. The nose pad is connected to the control terminal housing via the adjustment rod. The top of the adjustable lens is installed inside the control terminal. The speaker, charging head, and control terminal housing are integrated into a single structure, providing precise refractive modulation adaptation capabilities. A wireless connection is established between the mobile phone and the control terminal's control system. Users can precisely set target refractive power parameters according to their training needs. Stable optical coupling is formed by the annular optical diffraction microgrooves on the inner and outer lenses' relatively inner surfaces. After precise adjustment to the set refractive power, the device remains fixed, creating a deviation-free optical modulation environment for the trainee and ensuring the accuracy and effectiveness of visual function training.

The embodiment of the invention provides a method for determining the layout position of a spatial filter, an optical system and detection equipment, the method is applied to semiconductor detection equipment, the semiconductor detection equipment is used for detecting a to-be-detected sample, the semiconductor detection equipment comprises the optical system, and the optical system comprises a detection light source and an objective lens. The method comprises the steps that the structure period of a to-be-detected sample and key parameters of an optical system are obtained, and the key parameters at least comprise the wavelength of a detection light beam emitted by a detection light source, the angle of the detection light beam entering the to-be-detected sample and the focal length of an objective lens; based on the structure period and the key parameters of the optical system, calculating the space coordinates of each diffraction light on the Fourier surface of the objective lens through the optical diffraction theory; and determining the layout position of the spatial filter based on the spatial coordinates corresponding to the at least one diffracted light. The method is used for efficiently determining the position of the spatial filter, so that the working efficiency of semiconductor detection equipment is improved.

The invention provides a skin fungus microscopic examination image identification method and system, and the method comprises the steps: determining a high-frequency component and a low-frequency component of a fungus microscopic examination image, and reconstructing the fungus microscopic examination image into a denoised clear image; synchronously extracting optical features of spore edges during optical diffraction and texture features of spore surface textures for multi-channel feature fusion to obtain an enhanced texture feature map during fungal microscopic examination; according to a spatial topological relation of different feature units in the enhanced textural feature map in a preset neighborhood, generating discrimination features of a spore configuration, and further determining a confidence level of a spore target in the different feature units in the enhanced textural feature map through the discrimination features; and performing adaptive threshold segmentation on the enhanced texture feature map based on all confidence levels, and generating a confidence detection report of the fungal spores on the skin of the patient through a segmentation result. By adopting the scheme of the invention, the key identification features of the spores can be completely reserved while the image noise is inhibited.

The invention provides an amplitude hologram generation method based on deep learning and camera closed loop. The method comprises the following steps: firstly, acquiring light field intensity information of a to-be-reconstructed target, and generating an initial amplitude type hologram according to modulation characteristics of a spatial light modulator; the amplitude hologram is loaded to a modulator, reconstruction is achieved through optical diffraction, and a reconstructed image is collected in real time through a camera; constructing a loss function based on the deviation between the reconstructed image and the target image, performing camera closed-loop optimization on the hologram through an end-to-end gradient backhaul mechanism, and realizing the derivability of the binarization process by adopting a micro-approximation function under the condition that the binary modulation is not derivable; and training a deep learning network by using a propagation model obtained by closed-loop optimization, so that the network can quickly predict a high-quality amplitude hologram. The method compensates non-ideal deviation of an optical system while suppressing speckle noise and conjugate image interference, is suitable for holographic display of monochromatic and colorful and two-dimensional and three-dimensional scenes, and has the advantages of high reconstruction quality, efficient optimization, strong adaptability and the like.

The application discloses an optical modulation neuron and a full-optical diffraction neural network method for signal processing, establishes an optical modulation neuron, constructs a full-optical diffraction neural network based on the optical modulation neuron and applies the full-optical diffraction neural network to signal processing; an input layer of the full-optical diffraction neural network comprises a laser source array and an encoding circuit; after application data is encoded and converted, light waves emitted by the laser source array are used as signals, that is, optical input signals are generated by the input layer of the full-optical diffraction neural network; diffraction propagation of the light waves between layers of the full-optical diffraction neural network is represented as linear transformation in a complex domain; after receiving the signals, the optical modulation neuron passes through a nonlinear activation unit, modulates the signals by using a linear modulation unit and then transmits the signals to a next layer; output is obtained through forward propagation, parameters to be trained of the network are optimized according to the output by using a back propagation algorithm, and a trained full-optical diffraction neural network is obtained. The technical scheme provided by the application has low power consumption and high performance.

The application discloses a kind of ultra-high space-time resolution detection imaging method and system, it is related to optical technology field, including the following steps: to multi-wavelength short pulse laser photon space-time dynamic modulation, make single pulse local irradiation field photon number in single photon / few photon state;The patterned photon distribution microshrink after photon space-time dynamic modulation is carried out on the sample containing fluorescent molecule under few photon irradiation two / multi-photon excitation, collects two / multi-photon fluorescence;Through high space-time resolution detection means, obtain the spectral information, life information and spatial position information of two / multi-photon fluorescence, reconstruct the fluorescence information in field of view, complete the entire field of view ultra-resolution imaging and positioning.The application can realize large field of view, high frame frequency, ultra-resolution fluorescence detection imaging, for solving the major scientific problem of "optical diffraction limit", realize ultra-resolution fluorescence microscopy technology innovation provides opportunity.

The invention provides an optical body microscopic imaging device and method based on programmable LED array illumination and a quantitative phase imaging camera, and solves the problem that a traditional optical microscope is difficult to obtain a three-dimensional structure in a transparent sample such as cells; and the technical problems of high imaging noise, poor system stability and high operation and environment requirements of the existing optical diffraction tomography microscope are solved. The device comprises a programmable LED array, a microscopic imaging unit and a quantitative phase imaging camera with a built-in storage unit, the programmable LED array sequentially emits light beams to irradiate a sample on the microscopic imaging unit, the light beams become object light carrying sample information after penetrating through the sample, after amplification and interference, four-wave shear interference images are collected through the quantitative phase imaging camera, and the sample information is obtained. And finally determining the refractive index distribution of the sample according to an image processing program and an optical diffraction tomography reconstruction algorithm. The method has the advantages of low noise and high imaging quality.

The invention provides a measurement system for infinitesimal displacement, and the system comprises a laser transmitting module which is used for transmitting an original laser beam; the light beam shaping module is used for shaping the original laser beam and outputting a vortex light beam and a plane wave reference light beam; the focusing module is used for superposing the vortex light beam and the plane wave reference light beam to construct a measurement focal field, and the measurement focal field comprises a longitudinal optical singular point; the imaging acquisition module is used for acquiring a real image of a longitudinal optical singular point in a measurement focal field; and the data processing module is electrically connected with the imaging acquisition module and is used for determining the displacement of the focusing module according to the real image. The unique advantages that the spatial scale of a longitudinal optical singular point is infinitely small and the phase gradient is steep are fully utilized, optical diffraction limit restriction caused by the fact that a traditional optical metering method depends on a structured light field or an interference effect is avoided, and the precision of a displacement reference datum is improved.

The present application relates to an anapole metasurface and a low-power nanoparticle capturing method thereof, the metasurface comprising a silicon dioxide substrate and a dumbbell-shaped slot metasurface arranged on the surface of the substrate, the dumbbell-shaped slot metasurface being composed of an array of metasurface units, each metasurface unit being composed of silicon material and having a central dumbbell-shaped slot. The dumbbell-shaped slot forms an anapole mode by exciting electric dipole and ring dipole interference cancellation, and localizes the optical field in the central region of the slot to capture nanoparticles. The present application breaks through the optical diffraction limit of traditional optical tweezers by using the anapole mode excited by the dumbbell-shaped slot structure and the local light field enhancement characteristics, and realizes stable capture of nanoparticles much smaller than the wavelength of incident light; the all-dielectric system composed of silicon and silicon dioxide is adopted, there is no metal ohmic loss, the total power consumption is extremely low, and the local near-field temperature shift is negligible, so that the capture without thermal damage under low-power driving is realized.

The present application realizes an optical computing system capable of optically and in parallel performing operations for different multiple operations using a single optical diffraction element. The optical computing system (10A) is provided with an optical diffraction element (1) composed of a plurality of cells (micro-cells A) set independently in thickness or refractive index. A plurality of signal lights modulated by different signals (S1, S2,..., Sn) and different in phase are input to each cell (micro-cell A) of the optical diffraction element (1).