2749 results about "Quantum computer" patented technology

The AI-enhanced cellular modeling and simulation platform is a computational system designed to enhance biomedical research and development and personalized medicine and wellness. This platform integrates simulation modeling, machine learning and artificial intelligence, multi-omics data, and sophisticated data fusion and decision-support techniques to create comprehensive models of cellular systems and processes across multiple scales. It enables researchers and clinicians to simulate complex biological interactions, predict disease progression, and design or optimize treatment strategies or medical devices with improved accuracy and efficacy. The system's architecture allows for integration of various components, including real-time data processing, federated learning, and quantum computing enhancements. From personalized drug discovery and cancer therapies to synthetic biology and epidemiological analysis, this platform offers powerful tools for understanding and manipulating cellular systems and bioengineered systems. By bridging the gap between molecular-level interactions between cells and materials and organism-wide effects, it enables significant advancements in healthcare and biological sciences.

The invention relates to the technical field of document retrieval and information processing in the data processing technology, in particular to a document retrieval method based on multistage indexing and feature clustering, which comprises the following steps: performing high-dimensional space mapping on multi-modal features such as texts and images through a quantum embedding layer to generate cross-modal joint feature representation; a first-level index of a multi-level index architecture is dynamically initialized based on a meta-clustering algorithm, and semantic blocks of a second-level index are divided in combination with a multi-head self-attention mechanism. And an optimal transmission matrix is generated by using a Sinkhorn algorithm to align cross-node feature distribution. The multi-target mixed retrieval strategy is fused with vector retrieval, keyword retrieval and graph retrieval results, and weight distribution is dynamically adjusted. Through collaborative optimization of quantum calculation, federated learning and causal reasoning, a closed-loop technical architecture from feature analysis to dynamic index construction is formed, the problems of insufficient cross-modal fusion, static clustering deviation and semantic association deficiency are solved, and the precision, efficiency and dynamic adaptability of heterogeneous document retrieval are improved.

The invention relates to the technical field of cloud computing, and discloses a resource scheduling method, device and equipment, and the method comprises the steps: generating a multi-dimensional data topological graph of cloud environment monitoring data, decomposing a to-be-scheduled job set into quantum computing unit sets which can be processed in parallel, and adding priority labels for the quantum computing unit sets through a quantum heuristic algorithm, according to priority labels and a multi-dimensional data topological graph, physical resources of a cloud environment are divided into non-uniform resource fragments matched with task requirements, based on the non-uniform resource fragments, resource scheduling is carried out through an improved hybrid particle swarm optimization algorithm, and weighting and fitness evaluation and resource constraint correction are introduced. According to the resource scheduling method and device, the multi-dimensional data topological graph is generated to comprehensively present the resource state and association, then the to-be-scheduled job set is decomposed into the quantum computing unit sets, the priority labels are added, and then the non-uniform resource fragments are divided for resource scheduling, so that the resource adaptation accuracy is improved, and the scheduling efficiency and the resource utilization rate are improved.

The invention discloses a market supervision data security protection method and system based on a dynamic encryption strategy, and relates to the technical field of information security. The method comprises the following steps: generating an initial seed input improved four-dimensional hyperchaotic system, and generating a dynamic encryption parameter set through chaotic mapping iteration; the method comprises the following steps: carrying out adaptive fragmentation on market supervision data to be encrypted to generate a data sub-block set, carrying out dynamic S-box-based symmetric encryption on odd index sub-blocks, carrying out a chaotic stream encryption mode associated with a current dynamic sub-key on even index sub-blocks, and generating a unique quantum chaotic fingerprint for each encrypted sub-block; a searchable encryption index is jointly constructed by using a post-quantum encryption algorithm and a lattice-based encryption algorithm and is used for carrying out query operation under the condition that data is not decrypted; the encryption security, privacy protection capability and quantum computing attack resistance of the market supervision data are remarkably improved, and meanwhile, an efficient, flexible and extensible data security protection scheme is provided.

Systems and methods are disclosed for optimization, management, and merging of processes. This system integrates a multifaceted technological framework, including generative artificial intelligence, quantum computing simulations, and blockchain technology. It features a user interface for inputting diverse workflow requirements, a generative AI module for processing these inputs, and a quantum computing module for simulating and optimizing workflows. The system utilizes blockchain for secure workflow deployment and a suite of specialized engines for prompt management, data extraction, analysis, optimization, deployment orchestration, and continuous monitoring. These components ensure the system's adaptability to user-specific needs, scalability across various industries, and capability for integration with existing enterprise systems. This invention revolutionizes BPM by streamlining processes, enhancing efficiency, and maintaining high security and customization standards.

The invention discloses a method and a system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cathode Spectroscopy) simulation according to an electronic structure of molecules of a target material; obtaining at least one effective excitation operator based on parameters in the coefficient of each excitation operator in UCCSD simulation and by combining all the excitation operators; constructing a quantum circuit according to all the effective excitation operators; determining energy level distribution of molecules of the target material based on the quantum circuit; and determining the reaction activity of the molecules of the target material according to the energy level distribution of the molecules of the target material. According to the method, in the process of obtaining the effective excitation operator, an ADAPT-VQE algorithm does not need to be executed, so that the analysis cost of the physical and chemical properties of the material can be reduced, and the analysis efficiency of the physical and chemical properties of the material can also be improved.

The invention discloses a data annotation method and system of a collaborative computing architecture based on quantum computing, and belongs to the field of data annotation. The method comprises the steps that S1, multi-modal data are input and preprocessed; s2, extracting features of each mode after preprocessing; s3, coding the features of each mode into a quantum state, and carrying out mode fusion; s4, performing label reasoning on the quantum state after modal fusion, and performing label constraint optimization by using a quantum approximate optimization algorithm; s5, based on a quantum Bayesian network or an approximate causal graph generation method, generating explanation according to a modal contribution causal path, and deducing marginal contribution of each modal to final label prediction by using a joint probability measurement result; and S6, outputting a labeling result. According to the method, a quantum-classical cooperative computing architecture is designed, the efficiency and accuracy of multi-modal data labeling are remarkably improved, the interpretability, the distributed processing capacity and the high-dimensional feature modeling capacity of the system are enhanced, and a brand new solution thought is provided for development of the multi-modal labeling technology.

The invention discloses a market supervision data exchange platform migration and security enhancement method and system based on a credential environment, and relates to the technical field of network security. In the data migration process, the consistency and privacy protection of the data are ensured through Hash check and a multi-party security computing technology; a domestic commercial cryptographic algorithm and a quantum resistance encryption technology are introduced, so that the protection capability of the platform to existing security threats is effectively improved, and the resistance to future quantum computing threats is enhanced; an intrusion detection system and a virtual honeypot node are integrated, and a defense strategy is monitored and updated in real time in combination with a deep learning model, so that novel attack behaviors can be detected and coped with in real time; according to an intrusion detection alarm and a block chain audit result, a security policy and resource allocation are dynamically adjusted in combination with a machine learning technology, it is ensured that high-risk nodes are monitored in time, resource allocation is automatically optimized, and the resource utilization efficiency and security of the system are improved.

The invention provides an intelligent lock control method and system based on dynamic identity verification, and relates to the technical field of artificial intelligence, and the method comprises the steps: building a multi-dimensional risk assessment model comprising an operation time interval, a biological characteristic change rate and a spatial position parameter, and obtaining a risk assessment score; according to the risk assessment score, performing preliminary adjustment on the biological characteristic data, and performing encryption processing and characteristic enhancement on the preliminarily adjusted biological characteristic data in combination with a dynamic key to obtain processed biological characteristic data; performing collaborative calibration on the processed biological characteristic data according to the risk assessment score to obtain calibrated biological characteristic data; and encrypting the calibrated biological characteristic data through an anti-quantum computing encryption protocol, and carrying out weighted fusion on the encrypted characteristic data, the dynamic key, the environmental adaptability score and the risk assessment score to generate a final unlocking instruction. According to the invention, the safety and robustness of the intelligent lock are improved.

The invention provides a data quality detection and improvement system for a large language model, and relates to the technical field of code quality management. The data analysis and characteristic extraction module is used for extracting structured and semantic characteristics of codes and constructing a code distribution diagram; the multi-dimensional quality detection module comprehensively evaluates the data set quality from three aspects of semantic diversity, structural consistency and error mode; the code optimization and verification module generates an optimization suggestion based on a detection result, and verifies the effectiveness of an optimization scheme through dynamic evaluation and unit testing; the feedback and self-adaptive optimization module is combined with developer feedback and runtime performance test to dynamically adjust a repair strategy, and the complex code repair efficiency is improved through quantum computing auxiliary path search; according to the method, full-process automation from quality detection to optimization verification is achieved, the method is suitable for multi-dependency and multi-module complex code repair tasks, and the quality and efficiency of the code life cycle are improved.

The invention belongs to the technical field of power system simulation application, and particularly relates to a power system simulation optimization method based on data driving. Based on a data-driven dynamic adaptive space-time segmentation and cooperation model, a fast-varying electromagnetic transient process is mapped to a quantum processor, a slow-varying electromechanical transient process is reserved in a classical computer, a power grid node voltage is coded into quantum bit amplitude, a power grid is dynamically equivalent to quantum Hamiltonian, and a quantum Hamiltonian is obtained. And decoupling the quantum domain of the fast-changing electromagnetic transient state and the classical domain of the slow-changing electromechanical dynamic state to realize self-adaptive balance simulation precision and efficiency. Quantum calculation sparse codes and dynamic error correction are constructed, non-uniform code distance distribution is achieved, cross-scale data transmission errors are reduced, high-frequency harmonic distortion is avoided, high fault-tolerant simulation is achieved under limited quantum resources, code distances are dynamically adjusted through reinforcement learning of a DDPG strategy, noise fluctuation and power grid working condition changes are responded in real time, and resources and fault-tolerant balance are optimized.

The invention provides a multi-party collaborative anti-quantum signature method and system based on homomorphic Hash, and relates to the technical field of digital signatures, the system comprises a plurality of participants and a verification party, and the method is specifically as follows: each participant generates a pair of public and private keys, the public key is composed of a total public key, a total signature matrix and a total Hash matrix of all participants; based on the public and private keys, all participants perform multi-party signature on the target message through a homomorphic hash function, and a generated signature is composed of total hash challenge values of all participants, total response vectors of all participants and commitment value high-order difference values of all participants; according to the signature, the verifier recovers the high order of the total commitment value, further calculates the total hash challenge value, and verifies the validity of the signature through comparison of the total hash challenge value; according to the method, multi-user collaborative signature is realized, and the security of resisting malicious opponents under a quantum computer is obtained.

The invention discloses a method and system for assimilating meteorological satellite hyperspectral error non-Gaussian distribution data based on quantum computing, and the method carries out the generalized quality control of meteorological satellite hyperspectral data in consideration of an outlier value on the observation brightness temperature and equivalent data of a satellite hyperspectral infrared detector channel. Comprising the steps of channel optimal selection considering quantum information entropy, deviation correction based on artificial intelligence generalized integration generation type deep learning and cloud detection based on a minimum residual method to remove cloud view field point data, so that quality control data is obtained. And performing quantum space solution on the quantum non-Gaussian increment four-dimensional variational assimilation model compatible with error Gaussian distribution and non-Gaussian distribution based on quality control data to obtain analysis field data, and solving the problem that the brightness temperature assimilation of the hyperspectral infrared channel with error non-Gaussian distribution (or obvious non-Gaussian characteristics) is limited in the prior art. Meanwhile, the method is high in solving speed, and the obtained analysis field data has good precision and calculation timeliness.

The invention provides an anonymous Internet of Things identity authentication method and device based on an anti-quantum computing password. A key generation device sends a public key to a message sending end and a message receiving end, and sends a private key to an authentication server; the authentication server generates a blind parameter based on the private key, and sends the blind parameter to the message sending end; the message sending end performs blind operation based on the blind parameter, the public key and the to-be-transmitted message to obtain a blind message, and sends the blind message to the authentication server; the authentication server performs post-quantum signature on the blind message based on the private key to obtain a to-be-solved blind signature, and sends the to-be-solved blind signature to the message sending end; the message sending end carries out blind resolution operation on the to-be-resolved blind signature to obtain a target signature; the message sending end sends the to-be-transmitted message and the target signature to a message receiving end; and the message receiving end performs post-quantum verification on the target signature based on the public key, and if verification succeeds, processing is performed based on the to-be-transmitted message. Through the scheme of the invention, the user data security can be improved.

The invention discloses a federated learning method based on quantum transfer learning, relates to the cross technical field of quantum computing and federated learning, and aims to solve the problem of performance bottleneck of traditional federated learning under non-independent identically distributed data. The local model of each client is fused with a classic convolutional layer and a quantum convolutional layer; during local training, firstly, classic features are extracted by a classic convolutional layer, and then the classic features are coded and input into a quantum convolutional layer to generate quantum features; and the two features are spliced and then classified, and model parameters are uploaded. And the server side adopts a FedAvg algorithm to aggregate parameters so as to update the global model. According to the method, a transfer learning mechanism is introduced to optimize the initialization of the quantum layer, and an experimental result shows that the classification performance and robustness of the method are remarkably superior to those of a traditional federated CNN model on a non-IID image data set, and the method is particularly suitable for a privacy protection cooperative computing scene.

A hybrid quantum-classical (HQC) computer system, which includes a classical computer and a quantum computer, solves linear systems. The HQC computer system splits the linear system to be solved into subsystems that are small enough to be solved by the quantum computer, under control of the classical computer. The classical computer synthesizes the outputs of the quantum computer to generate the complete solution to the linear system.

The application discloses a ciphertext decryption method and related equipment applied to ciphertext encrypted according to an RSA algorithm, and the method comprises the following steps: acquiring a large number in ciphertext and a public key of the ciphertext; selecting a number smaller than the large number as a base of a discrete logarithm problem, selecting 1 as a modulus power operation result corresponding to the base, and converting the base and the modulus power operation result into an initial quantum state; inputting the initial quantum state into a quantum computing module for solving the discrete logarithm problem to obtain a first target quantum state in which a solution result of the discrete logarithm problem is stored; extracting the solution result from the first target quantum state, and calculating a private key of the ciphertext based on the solution result; and decrypting the ciphertext based on the private key to obtain plaintext of the ciphertext. Through the technical scheme, the private key can be recovered according to the disclosed information in the case that the private key is not disclosed, and then the ciphertext is decrypted, so that the related technical blank is filled.

The invention provides an electric vehicle charging demand prediction and scheduling method based on artificial intelligence, relates to the technical field of electric vehicle charging management, and integrates charging station historical data, user behavior modes and external environment factors through multi-mode deep learning, quantum computing optimization and dynamic user portrait generation technologies. Compared with a traditional method, the method has the advantages that the prediction error is reduced by about 30%, the prediction is particularly prominent in peak hours and extreme weather conditions, and meanwhile, charging resources in a region are integrated into a unified management unit through a virtual energy pool and an ecological self-adaptive scheduling mechanism, so that the prediction efficiency is improved. Distribution of the charging piles, new energy power generation and energy storage equipment is dynamically optimized, the utilization rate of the charging piles is increased by about 35%, and the utilization rate of new energy is increased by about 25%. According to the effect, resource waste is reduced, the contradiction between supply and demand of the charging station is relieved, more efficient charging service is provided for electric vehicle users, and meanwhile green development of an energy system is promoted.

The invention discloses a switch load balancing method based on fuzzy logic control, and the method comprises the following steps: S1, monitoring a network state in real time through quantum sensing equipment, and obtaining related parameters; s2, transmitting the parameters to a fuzzy logic controller for processing; s3, generating a load distribution strategy according to a predefined rule; s4, transmitting the preliminary strategy to each switch node in the block chain network, and recording related data; s5, verifying the data by using a distributed consensus mechanism of the block chain; s6, dynamically evaluating a node trust value based on an enhanced fuzzy trust model, and selecting nodes meeting requirements to participate in a load balancing game decision; s7, carrying out cooperative calculation on the selected nodes by utilizing a game theory cooperation mechanism, and generating a globally optimized load distribution strategy; and S8, optimizing a load distribution strategy through a quantum genetic algorithm, and performing automatic execution through an intelligent contract. According to the method, the advantages of fuzzy logic, the block chain and quantum computing are combined, and the intelligence and safety of load balancing are improved.

The invention relates to the technical field of quantum computing, and discloses a quantum circuit mapping method and system based on deep reinforcement learning, according to the method, an original logic quantum circuit is analyzed and simplified into a ZX-graph, then the ZX-graph is converted into a quantum circuit dependency graph, the computing complexity is remarkably reduced, and the quantum circuit mapping efficiency is improved. A large-scale quantum circuit mapping task can be processed within reasonable time, a Markov decision process environment is constructed through a quantum circuit dependency graph and quantum chip parameters, a deep reinforcement learning agent is trained by using the Markov decision process environment, and an optimal mapping strategy optimization model is obtained. Through the optimal mapping strategy optimization model, the corresponding optimal quantum bit mapping scheme can be output to the current to-be-mapped logic line, so that the method can be adapted to quantum chips of various topological structures, and the generalization ability and adaptability of the mapping scheme are improved.

The invention discloses an anti-quantum serial digital certificate implementation method. The method comprises the following steps: generating a traditional cryptographic algorithm key pair and an anti-quantum cryptographic algorithm key pair; submitting a certificate request; splicing the traditional cryptographic algorithm public key and the anti-quantum cryptographic algorithm public key to form a dual-cryptographic algorithm public key, and generating a digital certificate according to the dual-cryptographic algorithm public key; signing the digital certificate by using a traditional cryptographic algorithm private key and an anti-quantum cryptographic algorithm private key; and splicing and combining the traditional cryptographic algorithm signature value and the anti-quantum cryptographic algorithm signature value into a dual-cryptographic algorithm signature value, putting the dual-cryptographic algorithm signature value into a signature value item of the digital certificate, so that the digital certificate forms a hybrid serial digital certificate, and returning the hybrid serial digital certificate to the client. The invention further discloses a device for implementing the quantum serial digital certificate implementation method, computer equipment and a storage medium. According to the method, the problems of poor compatibility, low storage efficiency, slow verification speed and the like of the existing digital certificate under the threat of quantum computing are solved.

The invention relates to the technical field of quantum computing, and provides a polariton quantum computing simulation method and related device.The method comprises the steps that parameterized quantum circuits are generated based on micromodels used for describing polaritons for all to-be-computed excitation states respectively, and the parameterized quantum circuits are generated based on initial Hamiltonian of polaritons in a ground state; the target Hamiltonian amount of the polariton in the current excitation state is obtained, then the value of each parameter is adjusted at least once, and the target energy of the corresponding excitation state is obtained. In the primary adjustment process, parameter updating is carried out on the quantum circuit, a reference quantum state of the corresponding excitation state is obtained by utilizing the updated quantum circuit, reference energy of the corresponding excitation state is obtained based on the reference quantum state and in combination with the target Hamiltonian, and then when a set convergence condition is met, the target Hamiltonian is obtained. And taking the reference energy as target energy of the corresponding excited state. The polaritons are simulated through the quantum computer, and the simulation efficiency is improved.

The invention discloses an anti-quantum composite digital certificate implementation method. The method comprises the following steps: generating a classical cryptographic algorithm key pair and an anti-quantum cryptographic algorithm key pair; combining the classical key algorithm public key and the anti-quantum cryptography algorithm public key to obtain a public key algorithm identifier and a dual-algorithm public key combination; respectively performing signature processing on the certificate request by using a classical cryptographic algorithm private key and an anti-quantum cryptographic algorithm private key, and combining two signature results to obtain a signature algorithm identifier and a dual-algorithm signature value combination; submitting a composite digital certificate application request to a CA certificate authority; and verifying the dual-algorithm signature value combination by using the dual-algorithm public key combination in the composite digital certificate application request through the CA certificate authority, and issuing the digital certificate if the verification is passed. The invention also discloses a device for realizing the anti-quantum composite digital certificate realization method, computer equipment and a storage medium. According to the invention, dual security assurance under the threat of quantum computing is realized.

The invention discloses an equipment identity authentication and data encryption method and related equipment thereof, and the comprehensive effects of identity credibility, key security superposition and channel encryption capability enhancement are realized by introducing a mixed key system and a double digital signature mechanism into an equipment identity authentication and data encryption process. Meanwhile, a national cryptographic algorithm and a post-quantum algorithm are adopted, and the two cryptographic systems cooperate in parallel in an authentication and encryption link, so that the whole system has a robust anti-attack ability in both a traditional computing environment and a potential quantum computing environment, the accuracy of identity authentication is ensured by a dual signature mechanism, and the counterfeiting difficulty and tampering detection ability are remarkably improved. According to the method, the bidirectional verification chain is constructed in the authentication process, the safety is guaranteed by using the mixed key in the session stage, the safety robustness and the expandability of the system are improved through multi-layer protection, and the whole-process protection of the identity, the key and the data is realized, so that the safety robustness and the expandability of the system are integrally improved.

The invention provides a secure communication method and system based on a QRNG and a Beidou positioning terminal. A sending end and a receiving end of communication preset a pre-shared initial key, and a space-time reference parameter group is obtained through Beidou positioning; a secret key packaging secret key is generated by using a national secret SM4 algorithm; monitoring time-space parameter deviation in a communication process in real time, and triggering a key updating protocol when the time-space parameter deviation exceeds a threshold value; and after the receiving end verifies the Hash verification value, decrypting to obtain the primary encryption key, and restoring the plaintext data. According to the system, the generated true random number sequence is used as an encryption key, so that the unpredictability and randomness of the key are fundamentally enhanced, and quantum computing attack and man-in-the-middle attack are effectively resisted. The use of the pre-shared key mechanism and the key packaging key improves the response speed and efficiency of the communication system. And meanwhile, the position parameter and the timestamp are deeply fused to the key generation process, so that the spatio-temporal information is more difficult to counterfeit, and the defense capability of the system is further improved.

A quantum computing service provides a quantum algorithm development kit that enables a customer to define a quantum task, a quantum algorithm, or a quantum circuit using an intermediate representation. The quantum computing service is then configured to automatically translate the quantum task, quantum algorithm, or quantum circuit into a specific representation specific to a particular quantum computing technology selected by the customer to be used to execute the customer's quantum task, quantum algorithm, or quantum circuit.

The invention discloses a method for applying an anti-quantum certificate to a TLS1.2 handshake process, which realizes the application of an MLDSA anti-quantum signature algorithm and an MLKEM anti-quantum key encapsulation mechanism in the handshake process by expanding a cipher suite and a signature algorithm field of a TLS1.2 protocol. The method specifically comprises the following steps: defining a cipher suite supporting MLKEM and an MLDSA signature algorithm enumeration value; the client declares algorithm support in ClientHello, and the server responds and returns a certificate chain containing the double-antibody quantum certificate; after the client verifies the certificate, the pre-master key is encapsulated by using MLKEM, and the server de-encapsulates the derived session key; and the two parties send Finished messages to each other to complete handshake. According to the scheme, on the premise that a TLS1.2 basic framework is not changed, the communication security is enhanced through double-resistance quantum algorithm integration, international and national cryptographic algorithms are supported, quantum computing attacks can be resisted, meanwhile, adaptation of the international and national cryptographic algorithms is supported, compatibility with an existing system is ensured, the security risk of a traditional cryptographic algorithm in a quantum environment is solved, and the security risk of the traditional cryptographic algorithm in the quantum environment is reduced. And a standardized solution is provided for anti-quantum upgrade of the TLS1.2 protocol.

The invention provides a nonlinear data generation and processing method based on light quantum and a light quantum computer, and the method comprises the steps: obtaining a nonlinear function and attribute information of a nonlinear layer; according to the frequency spectrum number and the attribute information of the nonlinear function, constructing an initial light quantum circuit; measuring the initial light quantum circuit, and determining a target function corresponding to the initial light quantum circuit according to a measurement result; loss information of the target function is determined, whether the initial light quantum circuit is applied or not is determined according to the loss information, and if yes, the initial light quantum circuit serves as a target light quantum circuit; and performing operation on input data of the nonlinear layer based on the target light quantum circuit. According to the method, the low-energy-consumption characteristic of photon calculation, the nonlinear characteristic of light quantum calculation and the general programmable capability of electronic calculation can be fused, and high-energy-efficiency calculation can be carried out on input data of a nonlinear layer. In addition, the method also has the advantages that the complexity of a quantum circuit is smaller, and the participation of a nonlinear optical device is not needed.

The invention discloses a battery fault diagnosis method and device, and belongs to the technical field of battery management. The method comprises the following steps: synchronously acquiring multi-dimensional signals in a battery operation process through a multi-modal sensor array; performing encoding processing on the multi-dimensional signal through a pulse encoder to obtain a standardized pulse time sequence; based on a federated transfer learning framework, training the quantum pulse neural network in combination with a physical constraint loss function to obtain a trained battery fault diagnosis model; inputting the standardized pulse time sequence into the battery fault diagnosis model, and calculating a battery fault category and a thermal runaway probability through quantum inference; and triggering a corresponding security policy according to the thermal runaway probability and a preset threshold. By adopting the technical means of multi-mode signal fusion, quantum calculation acceleration and distributed learning, accurate and rapid diagnosis of battery faults is realized, and the method has the advantages of high precision, low delay and low power consumption.

The embodiment of the invention discloses an intelligent traffic cooperative control optimization method, device and equipment based on quantum key distribution and digital twinning, and relates to the technical field of intelligent traffic. The method comprises the following steps: transmitting traffic data and spatial information through the quantum secure communication network, and constructing a traffic digital twin mapping model based on the traffic data and the spatial information; the traffic digital twin mapping model is configured to map to obtain a physical traffic system operation state corresponding to the traffic data and the spatial information; accessing the digital twin mapping model into a quantum computing environment, and generating a traffic control strategy based on the operation state of a physical traffic system by using a preset quantum algorithm; and transmitting the traffic control strategy to traffic equipment in a physical traffic system for execution, synchronously transmitting the traffic control strategy to a digital twin mapping model for simulation execution, and optimizing and adjusting the traffic control strategy according to a difference comparison result of a feedback actual execution result and a simulation execution result.