109 results about "Quantum algorithm" patented technology

An efficient simulation system of quantum algorithm gates for classical computers with a Von Neumann architecture is described. In one embodiment, a Quantum Algorithm is solved using an algorithmic-based approach, wherein matrix elements of the quantum gate are calculated on demand. In one embodiment, a problem-oriented approach to implementing Grover's algorithm is provided with a termination condition determined by observation of Shannon minimum entropy. In one embodiment, a Quantum Control Algorithm is solved by using a reduced number of quantum operations.

A method and device for performing a quantum algorithm where the superposition, entanglement with interference operators determined for performing selection, crossover, and mutation operations based upon a genetic algorithm. Moreover, entanglement vectors generated by the entanglement operator of the quantum algorithm may be processed by a wise controller implementing a genetic algorithm before being input to the interference operator. This algorithm may be implemented with a hardware quantum gate or with a software computer program running on a computer. Further, the algorithm can be used in a method for controlling a process and a relative control device of a process which is more robust, requires very little initial information about dynamic behavior of control objects in the design process of an intelligent control system, or random noise insensitive (invariant) in a measurement system and in a control feedback loop.

The invention provides a route selection method for a modeling quantum genetic algorithm in a wireless network. In the method, a hierarchical node management model is established through interaction among convergence nodes, cluster head nodes, inter-cluster nodes and end nodes, and the energy state management of each target node is realized. The route selection method for a node comprises the following steps of: firstly, reading the state information, and optimizing the initial popularization in the quantum genetic algorithm; then, calculating the optimal route between the source node and the target node by using the full coherency, the dynamic quantum revolving door and other strategies through the characteristics such as efficient searchability, parallel quantum calculation and the like of the quantum genetic algorithm. The overall energy consumption of the network is kept to be minimized to the furthest extent, and the life of the wireless sensor network is prolonged.

The invention relates to a micro-grid economic and optimal operation and scheduling method based on an improved quantum genetic algorithm. The micro-grid is in a grid-connected mode operation state and comprises multiple micro sources and loads, wherein the loads comprise electric loads and thermal loads; and the micro sources comprise a micro turbine, a wind turbine, a photovoltaic cell, a fuel cell, a storage battery and an electric vehicle. The method comprises the following steps: S1, state information of each load and each micro source in the micro-grid is acquired; S2, with minimum of operation cost and pollutant treatment cost as a target, a multi-target economic scheduling model is built; S3, the improved quantum genetic algorithm is adopted for carrying out optimal solution on the multi-target economic scheduling model, and the optimal active power of each micro source is acquired; and S4, according to the optimal active power of each micro source, active power output by each micro source is controlled. Compared with the prior art, the micro-grid formed by distributed power sources operates in a more economic, flexible and environment-friendly mode, and power generation advantages of the distributed power sources can be taken.

The invention discloses a quantum information feature extraction method based on CTP financial data. Data issued by an exchange is processed by means of a quantum information algorithm model, a superposed-state quantum information presentation mode is firstly adopted to effectively describe the diversity of transaction data, description and processing by means of a quantum algorithm are facilitated on the basis, the data processing capacity of a quantum information algorithm model established on the basis of a quantum quick-calculation strategy and a quantum high-speed fuzzy hash method is improved remarkably, the calculation complex of the model is reduced remarkably, response delay is effectively reduced, the calculation complex of the algorithm is reduced, the response delay is reduced, and feature extraction and feature classification of the CTP financial data are achieved on the basis of the quantum information algorithm model.

The invention discloses an improved quantum genetic algorithm-based micro-grid energy storage locating and sizing optimization method. The method comprises the following steps: establishing an energy storage locating and sizing optimization model, wherein the energy storage locating and sizing optimization model comprises a target function formula and a constraint formula; improving a quantum genetic algorithm; and solving the energy storage locating and sizing optimization model by using the improved quantum genetic algorithm. According to the method, the energy storage locating and sizing optimization model is established, energy storage whole life cycle period cost, peak clipping-valley filling earning and grid loss earning are taken as targets, and the trend, energy storage charge-discharge and energy storage charge-discharge energy balance are constrained and considered; the quantum genetic algorithm is corrected, the dynamic adjustment strategy of a quantum revolving door revolving angle is used for improving the search efficiency, and a selection operation implemented by a simulated annealing method and a good point set cross operation can avoid local optimum; a 34-node micro grid is adopted to carry out verification so as to indicate that the disclosed algorithm is feasible, and the convergence efficiency of the quantum genetic algorithm and the ability of jumping out of local optimum are effectively improved.

The invention discloses a biometric fingerprint authentication method based on a quantum fuzzy commitment, which comprises a registration phase and an authentication phase. The registration phase comprises the following steps of: firstly, constructing a fuzzy commitment set to produce code words required for the commitment phase by using a quantum error correcting code space without self-dual constraint, and applying a noise addition transformation used for fuzzy proving to the code word; and then, constructing a quantum hash algorithm, and mixing, diffusing and encrypting a random quantum sequence so as to realize the security of using one key at one time in the sense of information theory. The authentication phase comprises the following step of opening the fuzzy commitment set by using a quantum fuzzy commitment to obtain random information for decrypting keys Messa. A new quantum fuzzy commitment system is constructed by combing the quantum hash algorithm on the basis of entangling assistant quantum error correcting codes. Compared with other similar fingerprint authentication methods, the biometric fingerprint authentication method based on a quantum fuzzy commitment has prominent advantages in the aspects of storage security and authentication security of biometric data, and the quantum biometric performance and the security of biological template information storage and transmission can be increased.

The invention discloses a high-voltage switch cabinet insulator electric field optimization method based on a quantum genetic algorithm. The method comprises the following steps that 1) a high-voltage switch cabinet insulator geometric model is built; 2) the high-voltage switch cabinet insulator model is subjected to electrostatic field simulation to obtain the maximum electric field intensity value, and structural factors for influencing the electric field distribution and the maximum field intensity are determined through changing variable structural parameters; 3) a population is initialized; 4) an objective function is determined, and a fitness degree function is calculated, wherein the objective function of an individual is the electric field intensity corresponding to the parameters; 5) for the individual population consisting of binary gene codes, the variation is carried out after the selection and the full-interference crossing; and 6) whether the quantum genetic operation stop condition is met or not is judged, if the stop condition is not met, the operation returns to the first step, and if the stop condition is met, the corresponding response value is calculated according to the optimized structure parameters obtained in the fifth step, and the maximum electric field intensity value is obtained. The method can realize the optimization on the high-voltage switch cabinet insulator electric field.

The invention relates to independent component analysis global search method of realizing the high spectrum fine classification under no prior knowledge situation, the method including: reading in the high spectral data, the establishment of independent component analysis model based on the kurtosis, the center of the data, the ball of data, the iterative solution based on quantum genetic algorithm, independent component compositor, two value of the image, the feature classification. The invention method can established on the circumstance of no data background model, using the self high statistical data to achieve the feature fine unsupervised classification of the high spectral data; at the same time, avoided to plunge in the local best solution problem in the independent component analysis solution process, and compared with the traditional genetic algorithm, the invention used quantum genetic algorithm has less number of iterations, fast convergence, high search efficiency and the strong overall search capability and so on features.

The invention relates to a quantum computer quantum processing unit, a quantum circuit and a quantum circuit quantum algorithm, and belongs to the technical field of computers. The quantum processingunit (QPU) is composed of five modules and is controlled by a classic device. The quantum circuit defines two n quantum bit inputs |x) and |y) based on an SHOR algorithm. A control register and a target register are arranged. Gates Gc, G'c and Gt are defined for each algorithm. The quantum circuit quantum algorithm is a design scheme of a quantum processing architecture based on a Shor algorithm.The influence of feedback control on the proposed architecture is considered. The period searching during large number decomposition can be effectively ensured by utilizing feedback adjustment, so that the optimal performance of the quantum algorithm is effectively realized.

The invention relates to a polynomial point expressed low expansion ratio anti-quantum-attack encryption algorithm, and belongs to the field of computers. The algorithm comprises the following steps that S1 the relevant encryption parameters of an RLWE public key encryption scheme are set; S2 a public and private key pair is generated according to the encryption parameters; S3 a file to be encrypted is inputted to generate a plaintext, the plaintext space is expanded to reduce the ciphertext expansion ratio, and the plaintext is directly coded to the value of the polynomial value assignment point so as to reduce the computing complexity; S4 the file is encrypted through the encryption algorithm so as to generate the ciphertext; S5 the ciphertext is decrypted through the decryption algorithm so as to obtain the plaintext; and S6 the plaintext is converted into the binary stream and the original file is outputted. The new public key cipher system having high encryption efficiency, low ciphertext expansion ratio and actual usability is constructed so that the huge risk that the quantum algorithm possibly decodes the conventional public key cipher can be resisted.

The invention provides a distribution network fault location method based on an improved quantum cuckoo algorithm. Distribution network fault location is modeled into high-dimensional combination optimization; a distribution network fault location section is expressed by using a quantum double-chain code; with an improved Levy flight algorithm, updating of a value of each dimension of a quantum cuckoo algorithm is optimized; and the quantum double-chain code is processed by variation by combining a differential evolution algorithm, so that an optimal solution to the distribution network fault location combination and an optimal solution is calculated. According to the invention, an optimized objective function of the distribution network fault location model is established; optimization calculation of the objective function is performed based on the improved quantum cuckoo algorithm; a fault section is identified; and verification is performed by using a distribution network example. Moreover, fault point location under the condition of multi-point simultaneous fault occurrence can be processed.

The invention provides a radio-frequency antenna impedance self-adaption matching device and method with the quantum algorithm applied. The radio-frequency antenna impedance self-adaption matching device with the quantum algorithm applied comprises a sensor measuring unit, a control unit and a matching unit, wherein the sensor measuring unit is electrically connected with the control unit, the control unit is electrically connected with the matching unit, the matching unit is electrically connected with the sensor measuring unit, and the matching unit is externally connected with an antenna. The invention further provides a self-adaption matching method of the radio-frequency antenna impedance self-adaption matching device with the quantum algorithm applied. Through the radio-frequency antenna impedance self-adaption matching device and method with the quantum algorithm applied, according to the quantum technology, a radio-frequency antenna impedance matching mathematical model is established. The radio-frequency antenna impedance self-adaption matching device and method with the quantum algorithm applied has the advantages of being high in matching speed, high in precision, good in effect, and applicable to real-time matching.

The invention discloses a multi-target intelligent power distribution network self-healing recovery method based on a quantum genetic algorithm. The method uses a node-layered forward and backward substitution method for flow calculation and uses a quantum genetic algorithm for self-healing recovery reconstruction of multiple targets of a power distribution network. The quantum genetic algorithm utilizes qubits to encode chromosomes and uses quantum revolving doors to adjust the chromosomes, so that in a relatively small population scale, the algorithm quickly converges to a global optimal solution. Island determination in the reconstruction is achieved by means of flow calculation, and the dimension of an infeasible solution is lowered. With power distribution network losses and switch action frequency as reconstruction targets, the method achieves comprehensive optimization of multiple targets and has practical value.

A quantum gate performs the superposition operation of a Grover's or of a Deutsch-Jozsa's quantum algorithm in a very fast manner. This is done by performing all multiplications by using logic gates that immediately outputs the result. The superposition operation includes performing the Hadamard rotation over an input set of vectors for producing a set of rotated vectors, and calculating the tensor product of all the rotated vectors for outputting a linear superposition set of vectors. The tensor product of all the rotated vectors is carried out by the logic gates.

A compiler for a gate-based superconducting quantum computer compiles hybrid classical/quantum algorithms for quantum processing cells with different configurations. The compiler inputs the algorithm and outputs code in a target language executable by a quantum processing cell of a quantum processing system that can execute the algorithm. The compiler includes various functionality, such as: parsing, analyzing control flows, addressing, compressing, and translating. The compiler optimizes algorithms in various manners using the functionality. Some optimizations include addressing efficiently, compressing based on simulations, and translating for efficient execution of parametric functions. The compiler may function in the environment of a cloud quantum computing system. The cloud quantum computing system may receive algorithms from remote access nodes for execution on local classical and quantum computing systems.

The disclosure describes various aspects of quantum computer simulators. In an aspect, a method for characterizing a quantum computer simulator includes identifying simulator processes supported by the quantum computer simulator, generating, for each simulator process, characteristic curves for different gates or quantum operations, the characteristic curves including information for predicting the time it takes to simulate each of the gates or quantum operations in a respective simulator process, and providing the characteristic curves to select one of the simulator processes to simulate a circuit, quantum program, or quantum algorithm that uses at least some of the gates or quantum operations. In another aspect, a method for optimizing simulations in a quantum computer simulator is described where a simulator process is selected for simulation of a circuit, quantum program, or quantum algorithm based on characteristic curves that predict a time it takes for the simulation to be carried out.

The invention discloses a method for calculating the Ramsey number of an r-homogeneous hypergraph based on an adiabatic quantum algorithm. The method comprises the following steps: researching an r-dimensional adjacency matrix representation form corresponding to an r-homogeneous hypergraph, giving a mapping rule gN, r (G) between the r-homogeneous hypergraph and a binary string, and mapping a Ramsey number R (m, n, r) of the r-homogeneous hypergraph into a combined optimization problem; solving a cost function of the combined optimization problem; defining a final-state Hamiltonian quantity of the adiabatic quantum algorithm by utilizing the solved cost function; the adiabatic quantum algorithm evolves the state of the L-bit register from the ground state of the initialized Hamiltonian tothe ground state of the final Hamiltonian; and after adiabatic evolution is finished, adopting a proper measurement method to measure the final state of the system, so that the solution of the combinatorial optimization problem can be obtained with a relatively high probability. The invention provides a method for solving an r-homogeneous hypergraph Ramsey number combination optimization problemby using an adiabatic quantum algorithm. The method has an acceleration effect on solving the Ramsey number of the graph compared with a classical algorithm.

A hardware quantum gate for running quantum algorithms in a very fast manner exploits the fact that a large number of multiplications required by an entanglement operation of the quantum algorithm provides a null result since only one component per row of the entanglement matrix U_F is not a null. The entanglement operation generates an entanglement vector by permuting pairs of opposite components of a linear superposition vector, depending on the value assumed by the function f. More specifically, if function f is null in correspondence to the vector identified by the first (leftmost) n qubits in common with the two n+1 qubit vectors, in which a pair of opposite components of the superposition vector is referred to, then the corresponding pair of components of the entanglement vector is equal to that of the superposition vector, otherwise it is the opposite.

The invention provides a reactive power optimization method for a 10 kV distribution network on the basis of a quantum genetic algorithm. Firstly, a model with the smallest active network loss is established, quantum bit probability amplitude coding is carried out on control variables to establish individuals of a solution space of the model instead of directly adopting numerical values of the control variables for coding, due to the fact that probability amplitude means equal probability adding of all possible states, the length of quantum coding by adopting the probability amplitude can be smaller than that of traditional binary coding, and therefore the computational efficiency of an algorithm is improved. According to the method, a new quantum crossing method is put forward, the update targets of two individuals with quantum revolving door updated are exchanged, population diversity can be improved, and the situation that the individuals converge to locally optimal solutions of the individuals is avoided. The reactive power optimization method for the 10 kV distribution network on the basis of the quantum genetic algorithm can shorten the operation cycle, improve the computational efficiency, has a chance to escape the locally optimal solutions and enter a new searching space, and the algorithm can finally converge to a globally optimal solution.

The embodiment of the invention discloses a data search method, device and equipment based on an analog quantum algorithm, and belongs to the technical field of computers. The method comprises the following steps: obtaining a plurality of candidate data to be searched, creating a first search path, obtaining a first processing function corresponding to the first search path, traversing at least two groups of numerical value sets of the first search path, and based on the analog quantum algorithm, obtaining an output value of the first processing function, under the condition that the output value of the first processing function is converged, taking a plurality of numerical values in the numerical value set corresponding to the converged output value as values of a plurality of coefficients respectively to obtain a second search path, and searching the target data by adopting the second search path. By traversing the at least two groups of numerical value sets and obtaining the outputvalues corresponding to the traversed numerical value sets, the frequency of traversing is low, accurate values of multiple coefficients can be quickly obtained, so that the efficiency of obtaining the second search path is improved, and the target data can be quickly searched by adopting the second search path.

The invention provides a sending mail encryption method based on a quantum security key, which is applied to mail sending equipment. The method comprises the following steps that S1 ', before a mail is sent, mail sending equipment carries out identity verification through a quantum password management service system, the mail sending equipment reads a quantum security key preset in a built-in quantum security chip and carries out symmetric entity identity authentication with the quantum password management service system, and finally an authentication result is returned; S2 ', after the user completes login authentication in the step S1, when a mail needs to be sent, a sender needs to use a preset key in the quantum security chip to make an application for obtaining a mail encryption key to a quantum password management service system. By adopting the technical scheme, the threat of the environment with increasingly severe network attacks to the mailbox sending environment is solved, the security threat brought by a quantum computer and a quantum algorithm in the future is prevented, and the scheme is easy to implement.

The invention discloses a hybrid quantum algorithm-based intelligent vehicle dispatching management system and a working method thereof. According to the system and the method, a hybrid quantum particle swarm optimization algorithm is disclosed through dividing a quantum particle swarm into two sub-phase particle swarms according to features of an optimization variable on the basis of using an improved quantum algorithm and an improved particle swarm algorithm; an elite quantum mean value and chaotic disturbance theory combined quantum evolution algorithm is designed on the basis of deeply researching advantages and boundedness of a tabu search algorithm in problem solution; and a simulated annealing algorithm and quantum algorithm combined hybrid quantum optimization algorithm is disclosed to solve demand-uncertain vehicle path problems; and a target function and a constraint condition of a dynamic vehicle path problem model are given. Simulated analysis results indicate that the method is capable of improving the convergence speed and convergence reliability, and is an effective method for solving demand-uncertain vehicle path problems.