268 results about "Quantum entanglement" patented technology

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 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 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 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 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 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.

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 discloses a multi-parameter cooperative control method for non-excavation repair of a drainage pipe network in urban updating, and relates to the technical field of municipal engineering, and the method comprises the steps: firstly constructing a quantum entanglement sensing pipe network digital twinborn model, fusing multi-source data, monitoring micro-strain in real time through a nano sensor, deploying a self-organizing intelligent node and terahertz imaging equipment, and constructing a quantum entanglement sensing pipe network digital twinborn model; multi-dimensional features are extracted, repair parameters are dynamically regulated and controlled through technologies such as magnetofluid plugging and multi-robot cooperation based on digital twinning virtual simulation, finally, the repair effect is evaluated and the scheme is optimized in combination with cognitive calculation and microbial self-healing technologies, and full-process intelligent control is achieved. The intelligent level of non-excavation repair of the drainage pipe network is improved, the problem that traditional monitoring is one-sided is solved through high-precision data fusion, precise construction control is achieved through cooperation of magnetofluid leaking stoppage and the robot, durability is enhanced through the microorganism self-healing technology, repair quality and efficiency are improved, and urban updating and sustainable development are promoted.

The invention discloses a temperature and humidity sensor data high-dimensional feature compression method based on quantum approximate optimization, and the method comprises the steps: inputting a temperature and humidity sensor time sequence data matrix, carrying out the quantum entanglement coding, and generating a quantum state; constructing a variable component sub-circuit of a quantum approximate optimization algorithm based on the quantum state, and dynamically updating circuit parameters through a genetic algorithm to obtain an output quantum state; performing projection measurement on the output quantum state to generate a candidate feature subset, updating a genetic algorithm population through quantum interference, and executing a dynamic crossover operation to generate a new feature subset; calculating a mutation probability by using a quantum gradient, executing an adaptive mutation operation, and optimizing a feature subset; the nonlinear relation between temperature and humidity data features is captured through quantum entanglement coding and quantum interference, dynamic parameter optimization and quantum gradient variation are combined, robust feature selection in a high-noise environment is achieved, feature compression efficiency and precision are improved, and the method is suitable for high-dimensional data processing in an Internet of Things scene.

The invention belongs to the technical field of irony detection, and discloses an inconsistency perception quantum fuzzy irony detection system and method, and the system comprises a multi-mode feature coding module which is responsible for coding originally inputted text and image data, and converting the data into a high-dimensional feature matrix; the cross-modal inconsistency embedding module is responsible for respectively extracting inconsistency features of a fact level and inconsistency features of an emotion level from the encoded text and image features; the inconsistency fuzzification module is responsible for utilizing fuzzy logic processing and representing inherent uncertainty in fact and emotion information to prepare for subsequent quantum calculation; and the quantum modal fusion and detection module is responsible for performing deep fusion and interaction on the fuzzified features in a quantum calculation space, and capturing a complex cross-modal relationship by using the characteristics such as quantum entanglement and the like. The invention designs a multi-mode irony detection framework of a hybrid quantum fuzzy neural network based on inconsistency perception.

The invention provides an auxiliary language training system based on artificial intelligence, belongs to the technical field of artificial intelligence, and realizes paradigm innovation of language learning through deep fusion of a quantum-classical hybrid architecture and a multi-modal neuroscience technology. A quantum semantic analysis engine and a cross-language parallel corpus generation module break through culture barriers, and a dynamic knowledge graph is fused with anthropology features and a taboo word weight quantification model, so that the cross-culture semantic accuracy is improved by 78%; a multi-modal synchronous compensation algorithm is combined with brain oxygen metabolism real-time monitoring, cross-modal delay of a VR / AR scene is compressed to be within 70 ms, a neural morphological pronunciation correction module and a 4D bionic tongue model construct a pronunciation-auditory feedback closed loop, the TTS phoneme fidelity of a small language reaches 97.9%, and 39% of language interference is reduced compared with a traditional model. A logic traceability network driven by a quantum entanglement dialogue module can analyze 12 layers of grammar nesting errors, and a dynamic correction path is generated in cooperation with a pulse neural dictionary.

The invention relates to the technical field of quantum, and particularly discloses a physical structure and function exploration method of a light quantum chip based on an e-p-n quantum entangled state basic particle model. Related quantum characteristics are brand-new interpreted based on the e-p-n quantum entangled state basic particle model, and the physical structure and function exploration method of the light quantum chip based on the e-p-n quantum entangled state basic particle model is established based on the e-p-n quantum entangled state basic particle model. The method comprises the following steps: researching basic modules of a light quantum chip, including generation of light quantum, formation of light quantum bits, a light quantum storage and reading scheme, linear optical quantum calculation, a light quantum chip control module, a substrate material of the light quantum chip and the like, and carrying out deep analysis on a light quantum chip technology; and the color, the luminous intensity, the spatial relative position and the like of an object can be judged due to the capability, and the method can be applied to the fields of visual automatic driving and the like.

The invention provides an optimization method, device and equipment for a quantum key distribution handshake protocol, and the method comprises the steps: preparing a standard quantum state and building a spinning peak shifting time sequence, and achieving the time division multiplexing and parallel processing of a plurality of quantum channels; constructing a handshake mode with successful pre-matched codebook storage history, and supporting rapid mode matching; the authentication sub-process and the negotiation sub-process are decoupled through a parallel verification architecture and are executed in parallel on different time phases; the quantum signature token and the key negotiation parameters are fused to generate a handshake state matrix, and global representation of the handshake process is achieved; performing success probability pre-judgment based on quantum entanglement association strength analysis, and triggering a pre-generation mechanism of a candidate key pool; performing quantum state weaving and fusion on the key by using local, non-local and mixed entanglement distribution adjustment to generate an enhanced key; and finally, optimal distribution is completed in combination with a spinning peak shifting time sequence, so that parallelization of authentication and negotiation, intellectualization of resource distribution and real-time state monitoring are realized.

The invention relates to the technical field of computers, and discloses a semantic entanglement-based chapter task aggregation method and device, and the method comprises the steps: generating a report graph based on a target report; determining service types of nodes in the report atlas, and dividing to obtain similar to-do groups; calculating the quantum entanglement degree between any two nodes in the similar to-do groups to obtain the semantic entanglement degree of the nodes; when the semantic entanglement degree is greater than a preset threshold value, calculating a merging score of the nodes to judge whether the nodes are merged or split; conflict detection is carried out during splitting to obtain conflict types; splitting into split to-be-handled groups according to a splitting mode corresponding to the conflict type, generating sub to-be-handled tasks of the split to-be-handled groups in the total to-be-handled tasks of the similar to-be-handled groups, and aggregating the report chapters corresponding to the nodes to the sub to-be-handled tasks. According to the method, preliminary aggregation is realized through division of similar to-do groups, semantic entanglement is used for further aggregation, the to-do number is reduced, report chapters are accurately aggregated to corresponding to-do tasks, and fine aggregation is realized.

The invention relates to the technical field of key distribution, in particular to a multi-cloud architecture-oriented dynamic key fragmentation storage management method and system, which comprises the following steps of: dividing a manufacturing process of the manufacturing industry into a plurality of time sequence stages corresponding to different data access authority levels and security requirements, and constructing corresponding quantum state evolution operators; driving the key state to evolve among different time sequence stages through a quantum state evolution operator according to the progress of the manufacturing process, and adjusting the access authority of the key; quantum entanglement connection is established between supply chain nodes, the trust degree between the nodes is measured and quantized through the association of the quantum entanglement state, and the distribution weight of the key fragments is adjusted based on the change of the trust degree; collecting constraint parameters of production takt, equipment state, logistics delay and quality index in the manufacturing process, and converting the constraint parameters into quantum state constraint conditions; and when it is detected that the constraint condition changes, recalculating the key fragment distribution scheme based on the quantum state constraint condition and the credibility, and synchronously distributing the key fragment distribution scheme to each supply chain node.

The invention discloses an unmanned aerial vehicle low-altitude target radar detection and recognition system, and belongs to the technical field of radar detection and target recognition. Comprising a quantum entanglement laser emission module, a quantum multi-dimensional receiving module, a multi-source heterogeneous data fusion module, a quantum-classical hybrid calculation module, a self-adaptive anti-interference module and an environment self-adaptive correction module, the quantum entanglement laser emission module is used for generating entanglement photon pairs carrying orbital angular momentum (OAM) and emitting the entanglement photon pairs to a detection airspace; and the quantum multi-dimensional receiving module demodulates the distance, the angle, the OAM attenuation spectrum, the polarization state and the reflection spectrum of the echo signal through coincidence measurement. The quantum entanglement-OAM combined modulation technology is adopted, and the non-locality of entanglement photon pairs and the multi-dimensional information bearing capacity of a 9-path orthogonal OAM mode are improved by more than three times compared with a traditional microwave radar; single-photon-level coincidence measurement is combined with quantum Fourier transform signal processing, the signal-to-noise ratio is increased by 3dB, and stable detection of a weak target is achieved.

The invention relates to the field of radio frequency power control, and discloses a radio frequency power control method and system for a 5G mainboard, and the method comprises the steps: 1, capturing the phase fluctuation of a millimeter wave frequency band through employing a superconductive quantum bit array, building a virtual channel response based on quantum entanglement state measurement, generating a channel topological graph, calculating and predicting a channel state based on the channel topological graph, and carrying out the calculation of a predicted channel state; calculating a prediction error according to the measured actual channel state, and adjusting the radio frequency power; 2, fusing the quantum measurement matrix and the deep residual network, introducing a residual attention mechanism to reconstruct an abnormal channel, carrying out local optimization, solving asymmetric Nash equilibrium, reducing algorithm complexity and calculation complexity, dynamically controlling radio frequency power, suppressing interference and improving power amplifier performance; and step 3, analyzing the influence of environmental factors on system errors, jointly calibrating and correcting the errors, constructing a learning model and expanding a dynamic range, determining the actual maximum transmitting power and distributing radio frequency power.

The invention discloses a sliding bearing service life prediction method, and relates to the technical field of sliding bearing intelligent monitoring, and the method comprises the steps: an edge calculation node uses a quantum decryption algorithm to decrypt multi-modal time series data, and carries out the fractional order chaotic dynamics analysis, thereby achieving the prediction of the service life of a sliding bearing. Performing phase-space reconstruction on the multi-modal time sequence data, extracting fractal dimensions of phase-space attractors, and fusing chemical and crystal data to a quantum entanglement space by adopting a quantum variational auto-encoder to generate a high-dimensional data set fusing macroscopic and microscopic features; constructing a quantum enhanced life prediction model, performing parameter calibration by adopting quantum Bayesian optimization, and predicting a bearing health index according to the high-dimensional data set; according to the invention, the quantum-enhanced life prediction model is constructed through the quantum variational auto-encoder, and the model parameters are dynamically calibrated in combination with the quantum Bayesian optimization algorithm, so that the accuracy and reliability of bearing life prediction are improved.

A system and method for distributing quantum entanglement using optically protected fiber optical paths is described. In some embodiments, multiple optical paths are used to connect a source site to a receiver site. Quantum entangled particles are transmitted from the source site to the receiver site using a first one of the multiple optical paths and related service channel information is transmitted from the source site to the receiver site using a second one of the multiple optical paths. In response to a failure of either the first or second optical path, an entanglement distribution controller automatically updates the routing such that the service channel information and the quantum entangled particles are routed concurrently on a remaining one of the first or second optical path.

The invention provides a three-dimensional-TDOA positioning method based on distributed microphone array cooperative positioning, and relates to the technical field of TDOA positioning, and the method comprises the steps: constructing a self-adaptive dynamic microphone array; a quantum entangled state sensor is introduced into a microphone node signal acquisition front end, and the arrival time difference of a target signal is measured; constructing a deep learning model, predicting sound velocity change according to environmental factors, and dynamically adjusting a sound velocity value in TDOA measurement; the microphone array node optimizes a positioning strategy through a reinforcement learning algorithm according to self measurement data and interaction information with other nodes; fusing the data, and based on fusion result data, executing a TDOA estimation improved algorithm; based on a TDOA calculation result, performing three-dimensional space search by adopting a quantum annealing algorithm to solve an optimal position of the target; and multi-source information is fused to add constraint conditions for a positioning algorithm, and a positioning result is optimized. According to the method, sub-centimeter-level positioning precision can be realized, and application scenes with extremely high positioning precision requirements are met.

The invention relates to a cross-trust-domain data security convergence system, method and device and a medium, and belongs to the technical field of network security. The system comprises a quantum enabling resource layer, an intelligent security control layer and a security execution layer, the quantum enabling resource layer comprises a quantum entangled state pre-distribution network and a quantum random number source cluster; the intelligent security control layer comprises a dynamic trust evaluation engine and a policy arrangement center which are respectively used for carrying out dynamic trust evaluation on a cross-domain communication requester and generating a session security policy packet; and the security execution layer comprises a cross-domain intelligent security gateway and an authentication auditing block chain, and is used for performing identity authentication and key generation under the constraint of the session security policy packet, executing cross-trust-domain data security convergence based on the generated key, and recording to form a security narrative chain for auditing traceability and authentication. The system can effectively support large-scale, high-real-time and high-security cross-network and cross-domain data security convergence.

The invention discloses a high-precision quantum sensing environment physical quantity real-time monitoring system and method, and belongs to the technical field of environment monitoring. The system comprises a quantum sensing front end, a signal excitation and regulation module, a quantum classical hybrid computing engine, an edge cloud collaborative transmission module and a terminal application module. The quantum sensing front end adopts a quantum entanglement sensing array integrated by NV color center diamond and a rubidium atom gas chamber to synchronously sense a magnetic field, temperature, pressure and vibration; the signal excitation and regulation module optimizes regulation parameters and inhibits noise through a quantum optimal control algorithm; a quantum-classical hybrid calculation engine is combined with a quantum neural network and classical multi-algorithm collaboration to realize efficient resolving and data fusion of quantum state features. According to the invention, the monitoring precision, the real-time response speed and the anti-interference capability are obviously improved, synchronous monitoring of multiple physical quantities is supported, and the system is suitable for various scenes such as industry, scientific research and deep space exploration, and has wide application value.

The invention discloses a social group member dynamic management method and system, and relates to the field of social network analysis, and the method comprises the steps: obtaining online interaction data and offline co-occurrence data of social group members, cleaning the online interaction data and the offline co-occurrence data, and converting the cleaned online interaction data and offline co-occurrence data into a structured data set; importing the structured data set into a graph database to obtain an initial weight, calculating a dynamic attenuation weight, and constructing a basic relation network; and converting an edge weight matrix in the basic relation network into a quantum bit entanglement state, measuring the quantum bit entanglement state to form a quantum probability amplitude, setting a quantum entanglement judgment threshold, and generating a quantum relation thermodynamic diagram through a Grover algorithm. Through the technical scheme of combining quantum calculation and dynamic entropy analysis, accurate management and risk prevention and control of the social group membership are realized, an edge weight matrix of a basic relation network is converted into a quantum bit entanglement state, and a quantum relation thermodynamic diagram is generated by using quantum measurement and a Grover algorithm.

This invention relates to a method for detecting and countering unmanned aerial vehicles (UAVs). It deploys a multi-dimensional sensing network for instantaneous scanning across the entire frequency band, simultaneously acquiring noise characteristics of radio signals, material characteristics in the terahertz band, and Doppler effect characteristics. These are mapped to a virtual twin to reconstruct the physical parameters, communication protocols, and behavioral patterns of the target UAV. A deep comparison is then performed using a camouflage sample library generated by an adversarial generative network to generate a holographic target profile containing three-dimensional motion vectors, energy characteristics, and potential threat intent. Quantum entanglement signals are used to interfere with the target's quantum-encrypted communication link, generating a controllable plasma cloud to selectively attenuate its navigation and image transmission signals. The controllability of the target is assessed, and uncontrollable targets are driven away using coded acoustic waves. Control commands incorporating bio-inspired obstacle avoidance algorithms are sent in stages to guide the UAV to an intelligent recovery pod. This invention achieves accurate detection, intelligent identification, secure countermeasures, and reliable takeover of UAVs, enhancing airspace security capabilities.

The invention relates to a multi-modal sentiment analysis method based on a large language model and quantum computing, and belongs to the technical field of multi-modal feature alignment and fusion. The multi-modal sentiment analysis method comprises the steps of constructing a multi-modal sentiment analysis data set, extracting text features and multi-granularity image sentiment description features by using the large language model and a target detection technology, carrying out multi-level fusion on the image emotion description and the original text to obtain cross-modal potential emotion association information; designing a cross-modal feature fusion mechanism based on a parameterized quantum circuit, and performing efficient fusion on multi-modal features by using quantum superposition and quantum entanglement features to generate unified emotion feature representation; performing sentiment classification based on the sentiment feature representation, and outputting a sentiment analysis result; according to the method, cross-modal potential emotion association can be effectively captured, the fusion efficiency and expression ability of multi-modal features are improved, the method is remarkably superior to the prior art in emotion analysis tasks, and the robustness and accuracy are high.

The invention relates to the technical field of slope engineering stability evaluation, in particular to a strip mine slope fatigue instability dynamic evaluation method and system based on a quantitative model. The method comprises the following steps: acquiring physical field parameter data of a strip mine slope; preprocessing the physical field parameter data; establishing a fatigue damage dynamic evaluation model; quantitative characterization parameters of the slope damage state are obtained; constructing a chaotic phase change enhancement model, a path connectivity enhancement model and a health state analysis model; and obtaining analysis results of mechanism early warning, path prediction and probability forecasting. According to the method, a standard field theory and a quantum entanglement enhancement algorithm are introduced, a dynamic evaluation system driven by a physical rule is constructed, multi-physical field perception and a fractional order chaos model are fused, and 97% high-precision identification and 63-day advanced early warning of a damage path are realized; by creating a mechanism-path-probability three-dimensional intelligent evaluation system, a major span from passive monitoring to active regulation and control and full life cycle decision making is realized.