1430 results about "Quantum state" patented technology

The invention provides a security encryption communication method and system based on quantum key management. The method comprises the following steps: acquiring system state data, and generating node state data, network connection diagram data and a system state matrix; receiving a communication request data packet, and generating a request feature vector, a service weight coefficient and a service demand matrix; the method comprises the following steps: collecting real-time network state data, constructing an enhanced Bayesian network model, and generating a network state scoring matrix; acquiring key pool state data, establishing a key consumption prediction model, and generating a key resource distribution matrix; constructing a multi-objective optimization model, and generating a scheduling strategy matrix; and executing the scheduling strategy and performing performance evaluation. According to the method, the quantum state de-coherence effect and the channel noise influence are considered, efficient management and safe distribution of quantum keys are achieved by establishing a complete evaluation and prediction system, and the performance and reliability of a communication system are 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 multi-mode interaction method for an accompanying robot, and relates to the technical field of robot interaction.The multi-mode interaction method comprises the steps that voice, visual and tactile signals are converted into quantum states through multi-mode quantum state coding, emotion weights are dynamically fused, and unified quantum representation is constructed; the dynamic quantum decision engine analyzes environmental noise and user emotion intensity in real time based on a quantum measurement theory, generates an adaptive strategy through dynamic modal weight distribution, and solves a multi-modal instruction conflict; holographic reinforcement learning optimization is combined with quantum acceleration calculation and classical reinforcement learning, the reward function weight is dynamically adjusted, cross-modal knowledge migration is achieved through the quantum tunneling effect, and the system strategy is continuously optimized. The problems that a traditional multi-mode interaction system is rigid in mode switching, high in emotion recognition error rate, lack of self-adaptive optimization of a feedback strategy and the like are solved, and the interaction efficiency and the user experience are improved.

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 an image generation method based on a mixed quantum classical condition generative adversarial network. The method comprises the following steps: firstly, converting a random condition label and a sample real condition label into one-hot codes, processing input noise and the random condition label by using a quantum circuit, performing measurement to convert a characteristic quantum state into a classical characteristic vector, and obtaining generated image data from the characteristic vector through a classical single-layer neural network. And transmitting the sample real image data and the real condition label into a discriminator to obtain a real image discrimination result, and transmitting the generated image data and the random condition label into the discriminator to obtain a generated image data discrimination result. And calculating discrimination loss based on the two discrimination results, training a discriminator and a quantum condition generator, obtaining a trained mixed quantum classical condition generative adversarial network, and generating a condition image. Based on the above scheme, the problems of unstable classical GAN training and many training parameters are solved, the limitation of the quantum GAN in a condition generation task is broken through, and the application of the quantum generative adversarial network in scenes such as image generation and pattern recognition in the field of real artificial intelligence is further promoted.

Methods and systems are disclosed for solving a differential problem using a hybrid computer system. The differential problem defines a differential equation, and a target function defines an approximate solution to the differential equation. The target function is defined as a sum of basis functions with parameterized coefficients. The method comprises receiving or determining a quantum circuit defining operations of a parameterized quantum model of the differential equation, and determining the solution to the differential problem based on the parameterized quantum model and, optionally, a loss function associated with the differential problem. The quantum circuit defines operations for encoding primitive elements (e.g., terms such as f(x), f(x) / dx, g(x), etc.) of the differential equation in a plurality of quantum states of quantum elements of the quantum processor. Each quantum state of the plurality of quantum states corresponds to a set of (parametrized or unparametrized) coefficients associated with the basis functions, of which at least one quantum state of the plurality of quantum states corresponds to a set of parametrized coefficients associated with the basis functions. The determination of the solution includes varying the variational parameters to determine a set of optimal parameters. The varying of the variational parameters includes: translating the operations of the quantum circuit into control signals for control and readout of the quantum elements of the quantum register; applying the operations of the quantum circuit to the quantum elements based on the control signals; determining classical measurement data by measuring one or more comparisons, e.g. overlaps, between pairs of quantum states from the plurality of quantum states; computing a loss value based on the loss function and the classical measurement data; and adjusting the variational parameters based on the loss value.

The invention discloses a power distribution network fault recovery method and system based on reinforcement learning, and the method comprises the steps: firstly carrying out the modeling of a power distribution network as a weighted directed graph model, and designing a data transmission protocol and a result receiving analysis mode of a quantum-classical hybrid architecture on this basis; meanwhile, designing a quantum reinforcement learning algorithm and strategy optimization based on a weighted directed graph model, training by using training data, representing states and actions by using quantum states, constructing and updating a strategy network and a value network through quantum gate operation, and designing a quantum reward function; when a power distribution network has a fault, the classic calculation part obtains state data after the fault according to a weighted directed graph model, encodes the state data and transmits the state data to the quantum calculation part, the quantum calculation part calculates an optimal fault recovery strategy through an algorithm and feeds the optimal fault recovery strategy back to the classic calculation part, and the classic calculation part converts the optimal fault recovery strategy into an actual control instruction to execute fault recovery work. According to the invention, efficient and reliable recovery of the power distribution network fault can be realized.

The invention relates to the technical field of quantum communication security, and discloses a quantum key distribution secure communication system based on a quantum mechanics principle. The system comprises a quantum state preparation unit which controls a quantum emission device to output a quantum state sequence containing a preset polarization angle and a phase modulation photon group; a quantum channel feature extraction unit captures channel environment interference parameters and constructs a photon polarization distribution matrix; a quantum communication security evaluation unit receives the matrix, and calculates a channel security coefficient threshold through a quantum bit error rate analyzer; the quantum key dynamic optimization unit generates an optimized key segmentation strategy in combination with a security coefficient threshold and a historical key negotiation record; the quantum key rotation control unit switches quantum state modulation parameters according to a segmentation strategy and a time window; and the quantum node synchronization management unit monitors node clock offset and injects a calibration signal to realize key distribution time slot alignment. The system can dynamically cope with environmental interference, and improves the security and adaptability of quantum key distribution.

The invention provides a molecular dynamics quantum variation simulation method and device.The molecular dynamics quantum variation simulation method comprises the steps that an initial quantum state of a target molecular system is measured to obtain a position basis vector set, then the position basis vector set and momentum basis vectors of the initial quantum state are used for constructing a parameterized quantum circuit, and the parameterized quantum circuit is obtained; and iteratively updating the parameters in the parameterized quantum circuit until the target evolution time is reached, thereby obtaining the final quantum state of the target molecular system. According to the method, a large-scale molecular simulation problem can be solved on a shallow quantum circuit, it is guaranteed that the circuit depth is only related to the Hamiltonian of a system and does not increase along with simulation time, and due to the fact that the depth of the quantum circuit is not related to evolution time, the quantum circuit depth can be improved. The method provided by the invention can be applied to simulating the processes of structural evolution, phase change and the like of the material under a long time scale.

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 an image classification method based on an extensible quantum convolutional neural network, and relates to the technical field of image classification, and the method comprises the steps: carrying out the preprocessing of to-be-classified image data, and then carrying out the slicing processing; converting the slice data into quantum state information through angle coding; a quantum system is constructed, the quantum system comprises a quantum feature extraction part and a quantum classification measurement part, the quantum feature extraction part comprises a quantum variational circuit model with a quantum convolutional layer, and the model can perform feature extraction on quantum state information by using alternating single quantum bit gates and double quantum bit gates; training a quantum variational circuit model by using a part of quantum state information; and inputting the other part of quantum state information into the trained quantum variational circuit model, and measuring the output quantum state of the quantum variational circuit model. According to the method, the problems that traditional deep learning is high in computing resource demand, limited in quantum computer scale and the like are solved, and a novel and practical method is provided for efficient image classification.

The invention discloses a password security enhancement method based on secret communication, and particularly relates to the technical field of password security. Transmission and information negotiation of a quantum state are realized by constructing a quantum communication channel and a classical communication channel; after the photons are coded and transmitted, the time delay condition of the photons is analyzed, if the delay is abnormal, a pulse light source simulates photon signals, the trigger probability of the detector is recorded, the time window deviation is judged, delay data and the trigger probability deviation are comprehensively evaluated, the security vulnerability risk caused by non-ideality of the photon detector is quantified, and the security vulnerability risk is evaluated. The method comprises the steps of dividing risks into a high level, a middle level and a low level, implementing corresponding management, dynamically adjusting a compression ratio of privacy amplification by utilizing fuzzy logic according to the middle risk level in combination with a preliminary key bit error rate and a detector risk value, strengthening the anti-eavesdropping capability of a key, and improving the security of a quantum key distribution system through real-time monitoring and dynamic adjustment. The time migration attack is defended, and the long-term security of encrypted communication is guaranteed.

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 embodiment of the invention provides an equipment predictive maintenance method and device based on artificial intelligence, relates to the technical field of data processing, and aims to adjust a model focus by identifying statistical characteristics of data and paying attention to characteristics with most significant changes. Moreover, the training sample set of the feature extraction model is adjusted based on the abnormal evaluation result, abnormal data can be suppressed, the model is protected from being interfered by the data, and the feature extraction effect can be optimized. Quantum state modeling can better capture a nonlinear relation in data, information loss of a traditional linear dimension reduction algorithm is avoided, and therefore the expressive power of features after dimension reduction is improved. According to the embodiment of the invention, through data compression and optimization feature extraction based on quantum state amplitude, the prediction precision and reliability of the model are improved, the quality of data input into the classifier model is ensured, and the risk of misjudgment is reduced.

The present technology pertains to systems and methods for one-way authentication of quantum channels. A transmitter generates an entangled quantum state comprising a first state and a second state, modulates the second state according to a clock-synchronized pattern, and transmits it through a quantum channel to a receiver. The first state is retained and measured at the transmitter to extract quantum-state information. Authentication is performed based on this information, without requiring feedback from the receiver. The quantum-state information may be derived using quadrature measurements, Gaussian tomography, or other statistical analyses to detect whether the second state underwent irreversible interactions such as eavesdropping or decoherence. The system enables secure unidirectional quantum authentication, reduces protocol complexity, and supports real-time anomaly detection. It is compatible with continuous-variable quantum states, quantum key distribution (QKD), and scalable communication architectures.

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 discloses a quantum computing fluid dynamics simulation method based on a lattice Boltzmann method, and the method combines the parallelism of quantum computing with the advantages of the lattice Boltzmann method. An efficient fluid dynamics solving framework is constructed through a collision operator in a non-equilibrium correction term linearization lattice Boltzmann equation which is obtained by deducing through a Chapman-Enskog theory and a Maxwell equilibrium state function, wherein the non-equilibrium correction term linearization lattice Boltzmann equation contains an adjustable relaxation parameter. The quantum state in the Hilbert space can be converted through a quantum logic gate due to the characteristics of quantum calculation, so that the problem of complex calculation in fluid mechanics is efficiently solved. According to the method, the actual problem is coded into the quantum state vector of the quantum bit, the vector is directly changed through quantum operation to solve the problem, the quantum bit state does not need to be iterated one by one, for example, in the matrix and vector multiplication process, operation can be completed only by using a quantum logic gate to act on the input quantum state, and therefore the calculation efficiency is remarkably improved.

The invention discloses a seal removing and document repairing method based on quantum state collaborative regulation and control, and relates to the field of document image processing and quantum computing cross technology, the method comprises the following steps: obtaining to-be-processed information, and carrying out quantum-classical feature collaborative preparation; the character stroke continuity is guaranteed through quantum entangled state modeling and entanglement degree constraint iteration, texture decoupling is achieved through quantum wavelet transform and Gram-Schmidt orthogonalization, and adaptive filling is conducted in combination with a quantum generative adversarial network; dynamic quantum phase adjustment is used for counteracting superposition interference of stamps with different transparency, and quantum neural network noise reduction and multi-scale quantum Fourier sharpening are used for optimizing image quality; checking the repair result, if the repair result does not reach the standard, returning to the edge sharpening link to perform decoupling and filling the edge sharpening link to readjust the parameter; and for special scenes such as inclination, multi-color overprinting and ultra-thin frames, quantum rotation correction, color channel separation and boundary annihilation operator processing are used, finally, high-precision, high-naturalness and high-adaptability restoration of seal removal is achieved, and high fidelity of results is guaranteed.

The invention relates to a quantum system eigenstate acquisition method and device, computer equipment and a storage medium, and relates to the technical field of quantum computing. The method comprises the following steps: constructing probability distribution, and initializing the probability distribution to obtain equal probability distribution; constructing a quantum circuit, sampling a bit string for the equal probability distribution, generating an initial quantum state, and enabling the initial quantum state to act on the quantum circuit to obtain an initial state acting result; calculating a target loss function and a gradient value of the target loss function according to the initial state action result; performing gradient descent optimization on the gradient value of the target loss function until the variation free energy of the quantum circuit model converges, and obtaining the probability of the bit string and a quantum circuit obtained by variation; the probabilities of the bit strings are ranked progressively, the bit strings ranked progressively are obtained to serve as calculation bases, and the quantum circuits obtained through variation act on the ranked calculation bases to obtain corresponding energy eigenstates.

The invention discloses an image classification method based on a multi-quantum filtering convolutional neural network, and the method comprises the steps: compressing a pixel value of an obtained image, and coding the compressed pixel value into a corresponding quantum state through a quantum revolving door; and inputting the quantum state into a quantum convolutional neural network to obtain an image label predicted value, training the quantum convolutional neural network by using the predicted value and a loss function to obtain a trained quantum convolutional neural network, the quantum convolutional neural network including a quantum convolutional layer, a quantum measurement attention layer, a pooling layer and a full connection layer, the quantum convolution layer comprises G quantum filters; and inputting an image needing to be detected into the trained quantum convolutional neural network to complete image classification. According to the method, the multi-topology quantum convolutional neural network is combined with a quantum bit measurement attention mechanism, so that the problem of great loss of entanglement information in a measurement stage is effectively solved, the method can better adapt to a quantum calculation environment, and the advantages of quantum calculation are exerted.

The invention discloses a quantum approximate optimization method and device based on easy Hamiltonian, and belongs to the technical field of quantum computation.The quantum approximate optimization method comprises the steps that a binary constraint optimization problem in intelligent decision making and resource configuration is converted into a linear constraint equation; preparing the initial state of the quantum circuit into an initial state corresponding to the special solution of the linear constraint equation; a variable component sub-circuit composed of a target Hamiltonian and an easy-to-drive Hamiltonian is designed, so that quantum state evolution is strictly limited in a feasible sub-space; a final quantum state is simulated and measured through Hamiltonian to obtain a candidate solution, and parameters are iteratively adjusted by using a classical optimization algorithm to approach an optimal solution. According to the method, convergence is accelerated through special solution initialization, the number of iterations is reduced, the evolutionary process is guaranteed to always meet constraint conditions through peaceability, and the solving efficiency and the success rate are remarkably improved.

Embodiments of a present disclosure relate to communication systems and more particularly to a system and a method for a point-to-point decoy differential phase shift (DPS) Quantum Key Distribution (QKD). The system includes a source QKD device and a destination QKD device. The source QKD device generates and transmits one or more quantum states comprising a series of N coherent pulses with one or more phases to the destination QKD device. The destination QKD device receives, and records time information and corresponding detector units associated with each photon detection event in the received quantum states. The source and destination QKD devices use decoy states to detect and prevent attacks, such as Photon-Number-Splitting (PNS) attacks. The system allows for the secure generation of a secret key between the source and destination QKD devices.

The invention discloses a method and a model for generating a quantum state set, and the method comprises the following steps: adding depolarization noise to any target quantum state through a non-unitary forward process, and converting the target quantum state into a completely mixed state; and de-noising the complete mixed state by using a trainable reverse process, and recovering the complete mixed state to the target quantum state. According to the method, more stable convergence performance is achieved based on the convex optimization method, the pure state and the mixed state can be effectively generated, excellent fidelity is achieved, and the huge potential in the aspect of coping with complex quantum generation tasks is shown.

Disclosed in the present application are a terahertz refractive index-optical rotation common-optical-path joint measurement method and system based on a quantum weak value amplification effect, and an application of the system. The method comprises: performing pre-selection, wherein a polarization state α of an incident terahertz wave emitted by a terahertz time-domain spectral unit is used as a pre-selected quantum state, the polarization state α being selected by means of a first polarizer; performing post-selection, wherein a polarization state α+π2 selected by means of a second polarizer is used as a post-selected quantum state; before measurement, making the post-selected quantum state and the pre-selected quantum state orthogonal to each other; and performing two instances of common-optical-path joint weak coupling, wherein two instances of weak coupling are sequentially performed on the terahertz wave and a sample to be subjected to measurement that is on a common-optical-path joint measurement unit. In the present application, the high-sensitivity characteristic of quantum weak measurement in which a signal is amplified but technical noise is not amplified is used, and by means of common-optical-path joint measurement, the refractive index and optical rotation of a measured chiral drug can be jointly measured with high sensitivity, without the need to change an optical path, thereby realizing high-sensitivity conformation recognition of the chiral drug.

The invention relates to the technical field of power system optimization scheduling and quantum computing, in particular to a power transmission section quantum search method, device and system based on topology specific cut set search. The key power transmission section searching method based on quantum approximate optimization comprises the following steps: firstly, obtaining a power grid model and a corresponding quantum line model by combining power grid operation data, and performing quantum evolution and measurement on the quantum line model to obtain a quantum state result of a power transmission section; setting a starting value en0 and a final value en2 of a target cut value and a cut value margin em; enabling en1 to traverse a numerical interval [en2, en0] at a set interval, solving a quantum state result for each en1, and obtaining an expected cut value and a corresponding section result; and screening a section result meeting the screening condition as an optimal power transmission section and outputting the optimal power transmission section. According to the method, improvement is carried out on the basis of a quantum approximate optimization algorithm, a multi-stage topology specific cut set search optimization strategy is introduced, the optimal solution of the quantum loss function is approached stage by stage, and the accuracy of a quantum topology search result is improved.

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.

A quantum element (QE) at a network node stores a first quantum state constituent (QSC) of an entangled quantum state characterized by a non-factorable quantum relationship among QSCs comprising the first QSC and a second QSC stored at another QE at another network node. Managing one or more quantum error management (QEM) operations includes: (1) providing a schedule for the QEM operations that is based at least in part on at least a portion of a time over which the first QSC is stored at the first QE and an estimated fidelity of the entangled quantum state after at least one of the QEM operations, or (2) providing a type of one or more QEM operations selected from two or more different types based at least in part on a number of resource quantum elements available at the first node after the first QSC is stored at the first QE.

The invention relates to a training method and device of a quantum generative adversarial network, equipment and a storage medium. The method comprises the steps that the Rayleigh divergence relation between real quantum state data and forged quantum state data output by a generator is constructed, a first loss function is constructed based on the Rayleigh divergence relation, and the first loss function is used for enabling the difference between the forged quantum state data output by the generator and the real quantum state data to be minimum; constructing a second loss function of the discriminator, wherein the second loss function is used for maximizing the probability that the discriminator outputs a false first discrimination result and a true second discrimination result; and alternately executing the first training of the generator and the second training of the discriminator until a training cut-off condition is reached, and completing the training of the quantum generative adversarial network. By adopting the method, the quantum generative adversarial network can be prevented from falling into a barren plateau phenomenon, so that the training effect of the quantum generative adversarial network is improved.

The invention relates generally to systems and methods estimating a target outcome using a combination of quantum computing and a Monte Carlo simulation. A quantum processor loads variables and distributions into a quantum system, begins a quantum walk, performs arithmetic operations with the variables and distributions to initiate the steps in the quantum walk, and ultimately performs a quantum estimation of the quantum state to estimate a target variable.