370 results about "Quantum entanglement" patented technology

The invention relates to the technical field of power distribution, in particular to a construction method and system for a digital twinborn model of a power distribution network. Establishing a digital element of the multi-physical field coupling characteristic of the power distribution network equipment based on quantum state space mapping, and simulating a collaborative degradation process of insulation aging and electromagnetic interference of the equipment; constructing a dynamic energy flow entanglement relationship among the nodes of the power distribution network according to the equipment degradation characteristic tensor; based on the quantum entanglement relationship between the device degradation feature tensor and the topology connection hypergraph, establishing a time-space coupling eigenmode of the device multi-physical field state and network energy flow distribution, and generating a quantum topology covariant tensor of a twin model; and carrying out dynamic fusion on real-time characteristic data and the quantum topology covariant tensor to form the digital twin model of the power distribution network. According to the method, the digital twin model capable of accurately reflecting the power distribution network equipment aging and energy transmission spatio-temporal evolution law is constructed, and a high-fidelity simulation platform is provided for power distribution network state evaluation, fault early warning and optimization regulation and control.

The invention discloses a carbon emission intelligent prediction method and system based on big data, and relates to the technical field of carbon emission monitoring, and the method comprises the steps: collecting carbon emission associated data, and generating a carbon emission feature tensor through quantum time-space coding and time-space grid alignment; constructing a dynamic causal graph network through causal entropy on the basis of the carbon emission feature tensor, and generating a causal weight matrix by combining anti-fact intervention and a Bayesian false-rejecting causal relationship; constructing a federated learning framework based on the causal weight matrix, deploying a federated aggregator at a cloud end to aggregate the encryption gradient of each edge node, and embedding a causal regular term in a federated loss function to perform joint training to generate a global carbon emission prediction model; according to the method, efficient fusion of industrial sensor data, satellite remote sensing data and other multi-source heterogeneous data is realized by utilizing quantum bit superposition state mapping and quantum entanglement state association technologies.

The invention relates to the technical field of autonomous navigation and robot environment perception, and discloses a multi-source sensor fused adaptive navigation system, which comprises a multi-source sensor space-time synchronization module, a quantum particle filtering positioning estimation module, a space-time element learning controller module, a cross-modal quantum fusion module and an adaptive navigation control module. Multi-source data space-time alignment is realized through Lie group SE (3) calibration and dynamic time warping; the positioning robustness of particle filtering is improved based on quantum state coding and annealing optimization; dynamically distributing a fusion weight and injecting a physical constraint by utilizing a meta-learning network; feature level fusion of laser radar, vision and inertial data is realized by means of a quantum entanglement mechanism; and constructing closed-loop adaptive navigation by combining model predictive control and quantum purity trigger feedback. According to the method, the navigation reliability problem caused by misalignment of multi-modal sensor data fusion, divergence of state estimation and insufficient cross-modal relevance in a dynamic environment is solved.

The invention provides a power grid dispatching strategy optimization method and system, and the method comprises the steps: deploying a device based on a quantum entanglement technology between transformer substations, and collecting the state information of a power grid, and encrypting and transmitting the state information to a control center through a quantum network; a pulse neural network processor is used in a control center to extract spatial-temporal characteristics, and a quantum game theory model is used to generate an optimized scheduling strategy. Multi-modal verification data is collected, including visual deformation, abnormal sound monitoring, and operational resistance data. A genetic algorithm and deep reinforcement learning are utilized to optimize a decision model, and a dynamic weight distribution mechanism is included. And through a photon-quantum hybrid computing architecture execution model, a scheduling strategy is collaboratively optimized, and a result is fed back to a physical power grid. According to the method, the quantum technology and the spiking neural network are combined, new energy fluctuation is captured in real time, the multi-target weight is dynamically adjusted through the quantum game theory model, and the scheduling strategy robustness is improved. And a photon-quantum hybrid computing architecture is adopted, so that the feature extraction speed and the optimization efficiency are improved.

The invention discloses an image data annotation method and system, and relates to the technical field of computer vision, and the method comprises the steps: collecting image and text data, carrying out the updating through kernel density estimation and a kinetic equation, carrying out the optimization through employing Euler discretization in combination with CLP propagation and EA, carrying out the conversion through amplitude coding, and carrying out the construction through a quantum state circuit. The method comprises the following steps: carrying out calculation by using partial traces, generating topological weighted entanglement entropy through weighted fusion, carrying out updating based on an attention mechanism, generating potential conflict pairs, calculating priorities, generating final conflict pairs through a CNN model, outputting region features through a NeRF model, carrying out extraction by using a CLIP model, and carrying out updating through a loss function. According to the method, VAE is combined with GLP propagation and EA for optimization, the precision and consistency of labeling are improved, and through joint verification of quantum entanglement entropy calculation and the NeBF model, the efficiency and accuracy of labeling are improved.

The invention discloses a computer network security situation awareness system and method, and relates to the technical field of computer network security, and the method comprises the steps: generating a dynamic gene pool through an antigen-antibody matching algorithm based on an initial quantum trust vector, and building a mapping relation table of an antigen feature vector and an antibody defense strategy; triggering a quantum alarm according to an entanglement entropy mutation event in the real-time quantum state flow data, matching a biological antibody strategy corresponding to a current network attack feature based on a mapping relation table, and fusing the quantum alarm and the biological alarm to generate an attack path topological graph; the network security situation is perceived by analyzing the quantum state change of the abnormal node ID and combining an attack path topological graph and a dynamic gene pool. Quantum entanglement pairs are distributed to network nodes through the quantum key distribution center, and initial quantum trust vectors are generated, so that the unknown attack resisting capability of the network is remarkably improved, and efficient and accurate network security situation awareness is realized.

The invention discloses a data processing method of an intelligent cold stamping production line integrated with an MES system, and the method comprises the steps: S1, installing at least one fisheye lens for detecting a stamping workpiece, collecting data, preprocessing the data, and building a three-dimensional scene, S2, carrying out the further processing of the preprocessed data in S1 through a flexible sensor network, the method comprises the following steps: S1, carrying out cross-modal fusion and feature extraction on data, S3, transmitting the data extracted in S2 to a digital twinborn body for dynamic updating and prediction, S4, carrying out deformation with the assistance of quantum entanglement and carrying out over-distance early warning, and S5, carrying out data storage and knowledge management. According to the data processing method of the intelligent cold stamping production line integrated with the MES system, a digital twinborn dynamic updating and predicting technology is utilized, quantum-classical hybrid simulation modeling and reinforcement learning algorithms are combined, precise prediction and optimization adjustment can be conducted on mold abrasion, process parameters and the like, the production efficiency and the product quality are improved, and the production cost is reduced. The production cost and the energy consumption are reduced.

The invention relates to the technical field of geological disaster monitoring, in particular to a geological disaster monitoring method and system based on a quantum coupling effect. The method comprises the following steps: acquiring geological environment parameters of a target monitoring area; laying a quantum sensor network; initializing a quantum bit; the tunneling effect of quantum bits is excited by using microwave signals; obtaining quantum state data by using a quantum measurement technology; analyzing a coupling relationship among the geological environment parameters to realize geological disaster risk early warning; the causes and development tracks of geological disasters are traced, and monitoring and early warning strategies are optimized. Through a quantum sensor network and a multi-field coupling analysis model, ultrahigh-precision monitoring of stress, displacement, temperature and water level parameters is realized by using a quantum entanglement state, topology protection and time reversal technology, a disaster chain reaction path is revealed, cause and risk evolution are dynamically traced, the early warning reliability is remarkably improved, and the early warning effect is improved. And the monitoring mode is promoted to transition from passive response to active intervention.

The invention discloses a power monitoring system host security micro-isolation method and system, particularly relates to the technical field of power terminal security isolation, and aims to monitor electromagnetic interference and quantum state changes in real time and improve the stability and security of a quantum key distribution process in combination with quantum error correction and dynamic prediction technologies. A high-confidentiality encryption key is generated through the randomness of a quantum key generator, the interference level is monitored in real time in a high electromagnetic interference environment, a security protocol is automatically triggered, and parameters of a quantum system are adjusted through an active feedback mechanism; a dynamic Bayesian network is utilized to predict entanglement attenuation of a quantum state, an information exchange behavior of a quantum system is analyzed through quantum entanglement entropy, the attenuation degree and interaction intensity of the quantum state are comprehensively analyzed, and a dynamic micro-isolation strategy is implemented according to an analysis result; the reliability of quantum key distribution is improved, and the anti-interference capability of a power monitoring system in a complex electromagnetic environment is enhanced.

The invention discloses a quadruped inspection robot space positioning method and system based on gravity center sensing, and aims to construct a gravity center potential energy field through foot end contact force and body attitude information, form a gravity center disturbance mode in combination with fluctuation spectrum analysis, and reveal a disturbance propagation mechanism. A reverse compensation technology is adopted to generate an anti-disturbance sequence, a foot end force distribution topology is reconstructed, and active disturbance suppression is achieved; a multi-frequency detection wave beam and coherent superposition technology is introduced, an environment hologram is generated, geometric topology is reconstructed, and a high-precision environment sensing system is established; high and low impedance regions are identified through energy density analysis, and an energy optimal path is constructed in combination with double strategies of potential field bypassing and streamline tracking; establishing an oscillation analysis space for path projection simulation, identifying resonance risk points and determining stabilization parameters; finally, a coordinate reference is generated by adopting a quantum entanglement type multi-anchor-point synchronization mechanism, accurate positioning is realized by fusing environmental geometric information, and a technical closed loop from gravity center dynamics analysis to environmental perception navigation is realized.

The invention discloses an automatic alignment and integrated control system and method for an optical crystal array. The automatic alignment and integrated control system comprises a quantum entanglement enhanced ultra-precise sensing array, a multi-factor coupling error prediction module, a full-link adaptive compensation execution module, a central control module and a federal learning collaborative optimization module. The sensing array is used for acquiring multi-dimensional error data such as sub-nano displacement, Raman spectrum deformation, infrared temperature rise and friction stress in real time; the prediction module is used for mining coupling characteristics between error sources based on an attention mechanism and predicting an instant alignment error and a hysteresis deformation error; the compensation execution module realizes full-link compensation through quantum traceability calibration, mechanical arm dynamic composite compensation and process parameter cooperative adjustment according to the prediction error; the central control module performs synchronous scheduling and conflict coordination; and the federated learning module realizes collaborative optimization and privacy protection of models among multiple devices. According to the invention, ultrahigh-precision and adaptive intelligent integration of the optical crystal array is realized.

The invention relates to the technical field of knowledge graph and content management, in particular to an intelligent education content management method and system based on a knowledge graph, and the method comprises the steps: obtaining multi-modal education content data which comprises text data and audio data; based on the multi-modal education content data, executing multi-modal tensor decomposition to obtain unified feature representation; according to the unified feature representation, topological continuous coherence feature extraction is executed to obtain topological features; based on the topological features, quantum entanglement feature enhancement is executed, and enhanced features are obtained; executing non-exchangeable geometric feature fusion according to the enhanced features to obtain fusion features; based on the fusion features, chaotic dynamics knowledge extraction is executed, and extracted knowledge is obtained; according to the method, the extracted knowledge is constructed into the knowledge graph, different forms of education contents such as texts and audios are integrated through a multi-modal tensor decomposition technology, complementary information among different modals can be captured, and comprehensiveness and accuracy of knowledge representation are improved.

The invention relates to the technical field of quantum communication and network security, in particular to a dynamic encryption method based on quantum key distribution, which comprises the following steps of: generating a multi-layer quantum entanglement state and adaptively setting a measurement basis in combination with a chaos scheduler; if the identity verification is qualified, quantum bits are measured at different levels, results are combined, and a shared quantum key is formed after Hash processing; the system end fragments plaintext data and encrypts the plaintext data by using the subkey segments; when abnormity is detected, entanglement purification or key updating is carried out immediately, and when communication is finished, high-fidelity entanglement resources are recycled and chaotic scheduler parameters are deleted. Multiple times of actual measurement and comparison show that the method can still maintain excellent safety and throughput performance in noise and attack environments.

The invention discloses a multi-mode image information fusion method based on deep learning, and relates to the technical field of image processing, and the method comprises the steps: obtaining image data of an optical microscopic mode and an electronic microscopic mode, and carrying out the spatial resolution alignment; a quantum entangled state light field coding method is adopted for the optical microscopic image data to generate quantum enhancement features, and topological persistent coherence analysis is performed on the electronic microscopic image data to extract multi-scale structural features; the features are mapped to a tensor space, cross-modal feature fusion is carried out through a tensor ring decomposition method of dynamic rank adjustment, a joint representation tensor is generated, physical constraint reconstruction is carried out on the joint representation tensor, and a super-resolution fusion image is generated. Through fusion of quantum enhancement features and multi-scale topological features, tensor ring decomposition of dynamic rank adjustment and Tucker decomposition dimension reduction compression, efficient fusion of high-resolution images is achieved, calculation redundancy is reduced, and processing efficiency is remarkably improved.

The invention discloses a traffic signal global collaborative prediction method based on a quantum entanglement state, and the method comprises the steps: building a quantization model of a dynamic evolution path of a target traffic network in a time window in the future, and constructing a space-time diagram model; mapping the signal phase state of the intersection into a time-space integrated quantum state by adopting a layered quantum coding scheme; on the basis of a preset traffic optimization target, constructing Hamiltonian including spatial coupling, time evolution and a cost item, solving a ground state of the Hamiltonian through a mixed quantum-classical calculation method, and determining an optimal dynamic evolution path; coding the actual state of the current traffic network into an initial state, carrying out sequential measurement through an optimal evolution operator, decoding a cooperative signal control strategy of each time point in the future, and executing the cooperative signal control strategy through a rolling time domain control framework; according to the invention, global optimization is carried out by using quantum parallelism, the optimal cooperation strategy in the whole space-time range can be obtained at one time, and the overall operation efficiency, predictability and robustness of the traffic network are improved.

A control system for a network of quantum systems operates the network to perform quantum informatics processing. The control system includes an entanglement scheduler configured to identify operations for which entanglement of two or more of the quantum systems is desired, identify plural potential entanglement attempts for generating the entanglement; and schedule at least some of the potential entanglement attempts to be performed to generate the entanglement for at least one of the operations. The entanglement scheduler may use direct entanglement, entanglement swapping and / or quantum teleportation approaches to generate the entanglement. The entanglement scheduler may schedule probabilistic entanglement attempts based at least in part on the probability of success of the entanglement attempts. The entanglement scheduler may generate entanglement to support plural branches of a quantum informatics process and / or to respond to events occurring while the quantum informatics process is executing.

The invention discloses an image classification method, system and device based on a quantum convolutional neural network, a medium and a product, and relates to the field of image classification, and the method comprises the steps: obtaining a to-be-classified image; preprocessing the to-be-classified image to obtain a processed to-be-classified image; converting the processed to-be-classified image into quantum image information by using a quantum coding technology; determining the category of the to-be-classified image by using an image classification model according to the quantum image information; wherein the image classification model is obtained by training a quantum convolutional neural network by using a training data set; the quantum convolutional neural network comprises a quantum entanglement layer, a quantum convolutional layer, a quantum pooling layer and a quantum full-connection layer which are connected in sequence. According to the method, the quantum convolutional neural network is adopted to classify the images, quantum entanglement and superposition characteristics are fully utilized, and the classification performance and the overall precision of the network are effectively improved.

The invention discloses a multi-modal data search method and system based on an AI large model, and relates to the technical field of multi-modal data processing, and the method comprises the steps: inputting multi-modal data into a quantum state propagation engine, mapping the multi-modal data to a quantum entanglement state through a quantum neural radiation field model, and generating a quantum entanglement state coding feature tensor; dynamically planning a quantum state propagation path of the quantum entangled state coding feature tensor based on a nonlinear soliton equation, and constructing a quantum topological index network and a knowledge graph; compiling a user search instruction into a quantum measurement operator, executing quantum state propagation path navigation in the quantum topological index network, and generating a candidate result set of cross-modal matching through a path interference effect; performing quantum de-coherence driven probability reordering on the candidate result set, and screening high-confidence results; through the amplitude damping channel and the fluctuation ratio weight calculation, the problem of high response delay caused by the calculation efficiency bottleneck is solved.

The invention relates to the technical field of wireless communication, and discloses a wireless communication adaptive method and system based on a data transmission state, and the method comprises the steps: obtaining multi-source data, carrying out the preprocessing of the multi-source data, obtaining a CSI compression matrix, predicting the channel coherence time, dynamically adjusting the CSI sampling interval, and defining a load-channel coupling factor; obtaining cross-layer data based on the CSI compression matrix, performing fusion through a rotation matrix to obtain a fusion matrix, and extracting a physical layer fusion feature and an application layer fusion feature to calculate a multi-target state score; establishing a 5G power compensation mechanism based on cross-layer data, calculating a four-dimensional influence tensor, performing tensor decomposition and optimal action selection, and decomposing T into a core tensor and a factor matrix; selecting an optimal parameter combination through modular product calculation; based on cross-layer data, a quantum entanglement feedback mechanism is introduced, data is fed back, entanglement state association cross-layer indexes are designed, a quantum gate is adjusted through entanglement state design, and a model is updated in real time in combination with incremental learning.

The invention discloses an intelligent equipment management and monitoring method based on the Internet of Things. The method comprises the following steps: S1, collecting and preprocessing equipment state data through a quantum sensor; s2, constructing a quantum sensing network, and dynamically optimizing a network topology structure by using a quantum entanglement technology; s3, mapping the equipment state data into a quantum state, and optimizing time delay and spatial distribution in a data transmission process through quantum superposition and quantum interference technologies; s4, correcting error data in the transmission process by adopting a quantum error correction algorithm, and encrypting the corrected data through a quantum key distribution technology; s5, predicting the state of the equipment, and fusing a prediction result with the encrypted data to form a management instruction; s6, executing the management instruction and adjusting the equipment management strategy; and S7, monitoring the running state of the equipment in real time and updating the management instruction. The method has the advantages of high efficiency, accuracy, safety and high adaptability, and the equipment operation and maintenance efficiency is improved.

The invention relates to the field of power equipment management, and discloses a power equipment traceability data management method based on a block chain, and the method comprises the following steps: collecting power equipment data through a block chain technology, the power equipment data including production, transportation, use and maintenance data; the consistency of the power equipment data is optimized based on the maximum entropy principle, and information sharing and data synchronization are carried out by using the entropy value of each node; the data state of each node is dynamically updated through Bayesian inference, and the real-time consistency of the traceability data is guaranteed; a quantum game mechanism is adopted to optimize a consensus algorithm, and a quantum superposition state and quantum entanglement are utilized to improve information sharing and data synchronization. By adopting the block chain technology, the maximum entropy principle, the Bayesian inference and the quantum game mechanism, the efficient, real-time synchronization and consistency of the power equipment data are realized, the security and integrity of the data are ensured, and the node fault recovery efficiency is improved.

The invention relates to the technical field of unmanned aerial vehicle signal transmission, and discloses an unmanned aerial vehicle signal transmission rate detection method and system.The method comprises the steps that a compressed sampling matrix is constructed through quantum random projection to reduce the signal dimension, and a quantum entanglement gate is driven based on attitude parameters to generate a dynamic sparse basis matrix; a federated learning framework is adopted to be fused with multi-node data optimization base parameters, rate detection is converted into combinatorial optimization solution in combination with a quantum annealing algorithm, and finally real-time adjustment of a modulation mode and transmitting power is achieved through closed-loop control. The innovation is embodied in a quantum compression sampling-federated optimization-annealing detection cross-domain cooperation mechanism, the defects of a traditional method in dynamic adaptability, calculation efficiency and anti-interference performance are overcome, and the method has the technical advantages of sparse representation space dynamic adaptation, quantum parallel acceleration optimization, multi-target parameter balance and the like. And the communication rate detection precision and link reliability of the unmanned aerial vehicle in a complex electromagnetic environment are remarkably improved.

The invention relates to a robot track synchronization control method. According to the technical scheme, efficient collection and over-distance transmission of neural signals are achieved through the quantum entanglement technology, the brain movement intention is analyzed in combination with a high-sensitivity sensor and an intelligent algorithm, an instruction is transmitted to a robot power driving system through a low-delay communication architecture, and real-time synchronization of man-machine tracks is achieved through a two-way feedback system. Meanwhile, the movement flexibility of the robot is improved by adopting a lightweight design, the problems of high delay, low precision, poor interaction experience and the like in traditional man-machine synchronous control are solved, and the method can be widely applied to the fields of exoskeleton robots, industrial collaborative robots, rehabilitation medical robots and the like. The method has the advantages of being low in delay, high in precision, capable of improving interaction experience and wide in application range.

The invention discloses a quantum network path selection and resource allocation method and system for realizing high throughput, and the method comprises the steps: initializing global variables and network parameters at least comprising a network topology structure, a request number and the maximum capacity of edges through building a quantum network model; setting the initial capacity of each edge, adjusting the capacity according to the fidelity of the edge, and removing the edge of which the fidelity is less than 0.5; designing a path selection algorithm, and selecting an optimal path by using the characteristics of the quantum state; constructing a resource allocation strategy based on quantum entanglement and quantum parallelism, and dynamically allocating network resources; and verifying the validity of the path selection and resource allocation method through the quantum network simulator. The resource allocation sequence is optimized, redundant operation in the resource allocation process is reduced, and therefore consumption of computing resources is reduced.

The invention discloses a fusion quantum secure communication method of an NAT gateway, and relates to the technical field of communication network information security and quantum information. Comprising the steps of 1, creating a fusion quantum security communication system of an NAT gateway, 2, adopting a quantum hybrid encryption architecture through a quantum security module, and internally arranging a quantum key distribution unit and an anti-quantum computing acceleration chipset, 3, expanding a quintuple mapping structure of NAT through a dynamic address mapping and quantum encryption module, newly adding a quantum security dimension field QSV, and carrying out quantum encryption on the quantum key distribution unit and the anti-quantum computing acceleration chipset. And 4, developing a protocol non-inductive conversion engine through a hybrid protocol stack cooperation module, supporting an IPv4 / IPv6 dual-stack quantum tunnel and a quantum key inheritance protocol to realize cross-protocol family encryption parameter migration, dynamically adjusting a quantum encapsulation mode in an address conversion process, and dynamically associating an internal network address port with a quantum key parameter and a channel fingerprint feature. And 5, constructing a quantum perception type session state machine through an anti-quantum attack session management module, and performing a joint decision-making mechanism through quantum entanglement state monitoring and classical traffic feature analysis.

The invention relates to the technical field of electric power data transmission, and discloses an electric power Internet of Things equipment identity authentication method and system based on quantum cloud codes. The method comprises the following steps: acquiring quantum state information through a quantum random number generator, generating a power authentication seed and converting the power authentication seed into a quantum cloud code initial seed; collecting an electrical equipment identifier and a characteristic parameter to generate a characteristic vector; expanding the initial seed of the quantum cloud code into a sub-key sequence, and generating an authentication quantum cloud code through quantum entanglement coding and error correction; executing quantum evolution in the authentication time window to generate a dynamic authentication code; after the challenge sequence is received, quantum measurement is carried out, and authentication response data is constructed; and finally, determining an authentication state through block chain storage and an intelligent contract. According to the invention, quantum cryptography and a block chain technology are combined, so that a high-security, low-overhead and extensible device identity authentication mechanism is realized.

A quantum computer system comprises first and second registers which are used to separate a quantum state into multiple subspaces of a 2n dimensional Hilbert space. A quantum state comprising 2n elements is defined on the first register, the first register comprising n qubits; a quantum state is defined on the second register, the second register comprising one or more qubits; and receiving a value k, where k is a binary integer such that 0 =< k =< n. The method further performing a bit-wise iteration process comprising: (i) performing a quantum entanglement between the registers to separate the quantum state on the first register into distinct subspaces of the Hilbert space which are indexed by the entangled values on the second register, and (ii) measuring an outcome on the second register to find a match with a portion of k, wherein said portion of k increases incrementally with the iteration process until the match is with all of k. The bit-wise iteration is used to separate the quantum state on the first register into subspaces of the Hilbert space, wherein elements of the subspaces have different Hamming weights, and one subspace contains only elements of Hamming weight k.

The invention discloses a watermark processing method and device, equipment, a medium and a program product. The method comprises the steps of obtaining an original document and an original watermark in response to a watermark generation instruction determined by a user; performing feature extraction on the original document to obtain structural features, semantic features and visual features corresponding to the original document; constructing an adaptive intensity mapping function based on the structural features, the semantic features and the visual features; constructing a quantum state watermark function based on the original watermark and a preset quantum parameter; and according to the adaptive intensity mapping function, the quantum state watermark function and a preset quantum entanglement enhancement function, a target watermark is generated, and the preset quantum entanglement enhancement function is used for realizing conversion between the original watermark and the quantum entanglement state. According to the embodiment of the invention, the watermark strength can be adaptively adjusted according to the document features, the watermark security is improved, and the document security is guaranteed.

A quantum entanglement purification device, comprising: a quantum entanglement purification device body (1), wherein the quantum entanglement purification device body (1) is provided with a matching vent panel (2), fixing bolts (3) are screwed onto the vent panel (2), the vent panel (2) is fixedly connected to the quantum entanglement purification device body (1) by means of the fixing bolts (3), and the vent panel (2) is provided with a plurality of sets of vent holes (4) that are distributed at intervals; a filter screen (6), wherein the filter screen (6) is arranged inside the quantum entanglement purification device body (1) on the side corresponding to the vent panel (2), and a cleaning assembly is provided between the vent panel (2) and the filter screen (6), the cleaning assembly being slidably arranged corresponding to the filter screen (6); and a cleaning discharge assembly arranged below the cleaning assembly, the cleaning discharge assembly being used for discharging dust cleaned off by the cleaning assembly. A slidably arranged sliding plate can drive an elastically arranged cleaning plate to clean dust adhering to the surface of the filter screen; during cleaning, a vertical plate is in a closed state to prevent dust from entering the inside of the quantum entanglement purification device body when cleaned off.

The invention belongs to the technical field of quantum information, and particularly relates to a quantum entanglement and classical signal common-fiber transmission device based on a hollow-core optical fiber. According to the device, the characteristics of low loss and weak non-linear effect of the hollow-core optical fiber are utilized, the quantum entanglement two-photon pair and the classical optical signal are transmitted in the hollow-core optical fiber in a co-fiber mode through the wavelength division multiplexing technology and the polarization optimization strategy, the system can tolerate the classical signal with the higher communication rate, and the lower quantum signal bit error rate is allowed. The quantum entanglement and classical signal common-fiber transmission device designed through the method can be widely applied to the fields of quantum key distribution, quantum teleportation, quantum clock synchronization, distributed quantum calculation and the like compatible with a classical optical fiber communication system.