44 results about "Quantum Fourier transform" patented technology

The invention relates to the technical field of vehicle-gauge-level password protection, and discloses a vehicle-gauge-level post quantum password acceleration and side channel protection device. The device comprises a quantum key injection unit, a quantum noise analysis unit, a post quantum cryptography acceleration engine, a side channel feature extraction unit and a protection strategy generator. The quantum key injection unit performs format standardization processing on input quantum key information; the quantum noise analysis unit collects a power consumption time sequence signal and an electromagnetic radiation signal of the cryptographic operation chip, and extracts a quantum noise characteristic spectrum through a quantum Fourier transform algorithm; the post quantum cryptographic acceleration engine adopts a lattice-based cryptographic algorithm to implement layered acceleration operation on the target encrypted message data; a side channel feature extraction unit constructs a space-time joint side channel feature tensor according to the quantum noise feature spectrum; the protection strategy generator identifies the physical fragile area according to the tensor and generates a corresponding protection strategy instruction. The device integrates a quantum cryptography acceleration function and a side channel protection function, and is suitable for a vehicle-specification-level scene.

The invention discloses an intelligent operation and maintenance system for oil and gas field pipeline leakage detection, which comprises a quantum enhanced distributed optical fiber sensing unit, a leakage positioning unit and a self-healing unit, and is characterized in that quantum enhanced optical fibers implanted with nanoscale gratings are arranged along the outer wall of a pipeline, and a compressed laser light source is utilized to trigger vibration and sound wave signals; the superconducting quantum edge node performs quantum Fourier transform preprocessing on the signal, and realizes sub-meter accurate positioning by combining a space-time convolutional neural network model with pipeline physical parameters; and finally, the system drives the directional microwave device to activate the intelligent coating at the leakage point, the shape memory polymer microcapsule pre-buried in the pipeline coating is triggered to be broken and expanded, a self-adaptive sealing layer is formed, and full-closed-loop automatic response from quantum-level sensing to molecular-level repairing is completed. Detection and repair are completed autonomously, manual intervention is not needed, zero commuting time occupation is achieved, and the corresponding repair speed can be increased to the second level from the traditional day / hour level.

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

The invention discloses an underwater robot imaging algorithm optimization method based on deep learning, and relates to the technical field of underwater robots, and the method comprises the steps: firstly carrying out the dynamic capture of an underwater light field through employing a curved surface CMOS array sensor, and adaptively adjusting the focal length of the curved surface CMOS array sensor according to the change of the light intensity of a scene, and activating the local pixels when the scene changes; designing a quantum convolution kernel, mapping classical convolution operation into a quantum circuit, constructing a hybrid calculation pipeline, and performing quantum state joint coding and cross-domain feature fusion on optical and acoustic data to obtain fused data; through quantum Fourier transform and quantum convolution, data of different modalities are fused, the accuracy and robustness of imaging are improved, weights of optical images and sonar data can be dynamically adjusted under different water turbidity and illumination conditions, the fusion effect is improved, model errors are reduced, metasurface parameters can be adjusted in real time, sub-wavelength wavefront regulation and control are achieved, and the method is suitable for large-scale popularization and application. And the adaptability and robustness of the imaging system are improved.

A quantum computer program may receive a mean, a standard deviation, and a discretization for a target normal distribution; determine a number of iterations t based on the mean and standard deviation; identify a value n from the discretization and value X0 from the mean; initialize n qubits in register q and an ancilla; apply a quantum Fourier transform and a +X0 gate to q; apply a Y-Rotation with angle π / 2 to the ancilla; apply a controlled +1 gate to q controlled by the ancilla; apply a Hadamard gate to the ancilla; measure the ancilla; set a value C to a value of the measured ancilla; repeat from the Y-Rotation t times; apply an inverse quantum Fourier transform to q; and output amplitudes of basis states of q as the normal distribution. The program may use qubit-scaling to reduce the number of iterations needed.

Various embodiments of the present disclosure provide systems and methods for generally generating and transforming physical quantum representations of multi-dimensional tensor data objects. Specifically, various embodiments enable the rapid and efficient generation of a physical quantum representation representing the Fourier transform of a multi-dimensional tensor data object based at least in part on manipulating another physical quantum representation of the multi-dimensional tensor data object itself via quantum manipulation operations. Information may be extracted from the generated physical quantum representation to determine the Fourier transform of the multi-dimensional tensor data object. Accordingly, various embodiments may comprise quantum manipulation operations for a tensor-form quantum Fourier transform (TQFT) for a multi-dimensional tensor data object. Various embodiments for the TQFT are advantageously comprehensive, versatile, and applicable to any quantum representation form for a multi-dimensional tensor data object. The TQFT may be performed in any quantum computing system and / or simulated quantum computing system.

The invention belongs to the technical field of system design optimization driven by artificial intelligence, and discloses a training course planning service method and system. A correlation feature matrix of scene fluctuation parameters and resource requirements is extracted through a quantum principal component analysis module, a system health degree attenuation signal is analyzed in combination with quantum Fourier transform, and dynamic scene features are generated; constructing a parameter tuning instruction set based on a quantum annealing algorithm, and driving a genetic algorithm to optimize design topology; and the micro-optimization units are distributed to the digital twin platform by using quantum superposition state mapping, and the collaborative verification module solves a resource reuse strategy through a variable component sub-algorithm to form a data closed-loop feedback link. According to the method, the problem of mismatching of static data and dynamic requirements is solved, and the real-time responsiveness and the resource optimization efficiency in a complex scene are improved.

A recording medium storing a program for causing a computer to execute: determining a number of control qubits using a relationship between a first arithmetic operation time for each of multiple kinds of modular exponentiation calculation processing in an arithmetic operation of prime factorization and a second arithmetic operation time for each of a plurality of measurement and classical conditional arithmetic operations in inverse quantum Fourier transform processing on results of the multiple kinds of modular exponentiation calculation processing in the arithmetic operation of the prime factorization; determining a circuit pattern for performing the arithmetic operation of the prime factorization by executing the multiple kinds of modular exponentiation calculation processing and the inverse quantum Fourier transform processing, based on the number of control qubits; generating a quantum circuit using the circuit pattern; and performing the arithmetic operation of the prime factorization by using the quantum circuit.

The invention discloses a touch screen multi-modal interaction fault prediction and maintenance system based on intelligent diagnosis, and the system employs a multi-modal perception fusion unit to fuse the multi-dimensional perception data of a touch screen in quantum touch interaction, neural gesture recognition, electroencephalogram voice cooperation and iris eye movement tracking interaction modes, overcomes the limitation of single-modal data, and improves the accuracy of the multi-modal interaction fault prediction and maintenance of the touch screen. Quantum Fourier transform and a quantum principal component analysis algorithm are used for carrying out quantum state feature extraction on fused data, the feature extraction efficiency and accuracy are improved, the uniqueness of fault features is enhanced through quantum entanglement, different fault modes can be distinguished, and then the fault prediction accuracy is improved. A fault prediction value is calculated based on a quantum fault prediction formula, a weight coefficient is dynamically adjusted to adapt to different fault modes and data changes, a maintenance strategy comprehensively considering a plurality of target factors is generated by applying a quantum multi-objective optimization algorithm according to the prediction value and a preset threshold value, and optimal configuration of maintenance resources is realized.

A method of addressing a first set of quantum computing nodes in a network, wherein the network further comprises a controller node comprising N qubits, and wherein each quantum computing node of the first set comprises one or more ancillary qubits of a set of M ancillary qubits, is disclosed. The method comprises obtaining, at the controller node, information indicating a number of quantum computing nodes within the first set; determining, at the controller node, an initial quantum state for the N qubits, and a unitary operator U of the initial quantum state; preparing, at the controller node, the N qubits in the initial quantum state; applying, at each quantum computing node of the first set, a Hadamard gate operation to put each of the one or more ancillary qubits into an equal superposition state; applying, at the controller node, M controlled unitary gate operations on the N qubits, wherein the mth controlled unitary gate operation is controlled by the mth ancillary qubit of the set of M ancillary qubits, wherein the mth controlled unitary gate operation based on an applied unitary operator that is equivalent to a number of applications of the unitary operator U, and wherein m = 1, …, M; applying, at the first set of quantum computing nodes, an inverse quantum Fourier transform operation to the set of M ancillary qubits; and performing, at each quantum computing node of the first set, a measurement on each of the one or more ancillary qubits, to obtain at least a first addressing bit of an address for the quantum computing node.

A quantum circuit, configured to process n qubits and d additional qubits, includes: a d-qubit Quantum Fourier Transform circuit configured to apply a d-qubit Quantum Fourier Transform to the d additional qubits; a plurality of parity-fan-out gates controlled by the n qubits and configured to control the additional d qubits, wherein each of the plurality of parity fan-out gates is coupled to a corresponding one a plurality of sets of additional phase gates that also apply phase angles to the d additional qubits, wherein quantum circuit implements a unitary of a bit function and wherein the sets of additional phase gates apply the phase angles to the d additional qubits based on a Walsh-Hadamard Transform of a conversion of the bit function to a binary number; and a d-qubit Inverse Quantum Fourier Transform circuit configured to apply a d-qubit Inverse Quantum Fourier Transform to the d additional qubits.

The application belongs to the technical field of artificial intelligence driven system design optimization, and discloses a training course planning service method and system. A quantum principal component analysis module is used to extract a correlation feature matrix of scene fluctuation parameters and resource demand, a quantum Fourier transform is used to analyze system health degree attenuation signals, and dynamic scene features are generated. A parameter tuning instruction set is constructed based on a quantum annealing algorithm to drive a genetic algorithm to optimize the topology. A quantum superposition state mapping is used to distribute micro-optimization units to a digital twin platform, and a variation quantum algorithm is used by a collaborative verification module to solve resource multiplexing strategies to form a data closed-loop feedback link. The application solves the problem of static data and dynamic demand mismatch, and improves real-time responsiveness and resource optimization efficiency in complex scenarios.

The invention relates to a computer-implemented method (100) for solving at least one differential equation of at least one physical model, comprising at least the following steps: training (102) at least one neural operator (10) using input training data and output training data associated with the at least one differential equation, wherein the at least one neural operator (10) performs at least one Fourier transform using at least one learning quantum Fourier transform quantum circuit (20), wherein the neural operator (10) and the learning quantum Fourier transform quantum circuit (20) are trained such that the at least one neural operator (10) outputs at least one functional relationship between the input training data and the output training data;and determining (104) at least one solution (28) of the at least one differential equation using the at least one trained neural operator (10). The method (100) exhibits increased time efficiency.;

The invention discloses a microwave frequency conversion system based on quantum computing, and the system comprises a microwave collection unit which is used for collecting a multi-beam microwave signal, and carrying out the quantum state coding of the multi-beam microwave signal based on quantum Fourier transform, so as to obtain a quantum spectrum tensor space corresponding to the multi-beam microwave signal; the quantum encryption unit is used for performing quantum parallel processing of frequency spectrum components and encrypted information on the compressed quantum state data and the encrypted key stream based on a controlled phase revolving door so as to obtain encrypted quantum state data; and the frequency conversion unit is used for carrying out quantum bit coupling strength adjustment on the encrypted quantum state data based on a quantum control pulse sequence so as to obtain the multi-beam microwave signal subjected to frequency conversion. According to the invention, more efficient spectrum analysis and processing are realized through quantum Fourier transform, so that the signal processing speed is increased.

The invention discloses an equipment intelligent management and control system for a high-grade clean laboratory, and the system comprises a multispectral imaging module which comprises a visible light camera and a laser displacement sensor; the quantum edge computing node is integrated with a quantum computing coprocessor; the self-adaptive calibration actuator comprises a nanoscale piezoelectric driving mechanism; the federal learning cloud platform is used for realizing multi-laboratory model cooperative training; and the augmented reality interaction terminal displays the equipment pose deviation in real time. Visible light and laser displacement sensing can be combined, holographic monitoring of the equipment state is achieved, quantum Fourier transform is used for accelerating image processing, and dynamic compensation, multi-laboratory cooperative training supporting and differential privacy protection data security injection are achieved through piezoelectric ceramic driving and a hybrid control algorithm.

The application discloses a quantum adder, an operation method and related devices. The quantum adder comprises a plurality of chips connected through an EPR module. One chip is used for processing one data segment. The data segment comprises an addend segment and a summand segment. The chip comprises: an addition module, which is used for obtaining an addition result and carry information of the data segment based on a quantum Fourier transform; a loading module, which is used for loading the carry information transmitted through the EPR module on the addition result and the carry information obtained by the chip based on the addition module, so as to update the addition result and the carry information of the chip; and an inverse quantum Fourier transform module, which is used for converting the latest addition result into a binary string. According to the embodiments of the application, the efficiency of the addition operation in quantum computing can be improved.

Various aspects of phase error estimation in a quantum communication system are provided. In some aspects, a semiclassical quantum fourier transform (SQFT) may be applied to incoming quantum states. Measurements results from the SQFT may be used to estimate a phase error. Various SQFT circuitry is further described, including parallel SQFT circuitry and sequential SQFT circuitry.

This invention discloses a molecular dynamics calculation method and system based on quantum simulation. The method first applies a discrete quantum Fourier transform to the atomic coordinates of the molecular system, mapping the original plane wave basis to a system containing only O(N) atoms. 2 The invention constructs a plane-wave bibasic quantum mechanics equation; then, it constructs and solves the electronic structure Hamiltonian on a quantum computer to obtain the ground state energy. This quantum energy is combined with the classical empirical potential energy according to predetermined weighting coefficients to calculate the total synthesized energy, from which the atomic forces are determined. The integration time step is then adaptively adjusted based on a comparison of the quantum energy change between consecutive time steps with a preset threshold. This adaptive mechanism shortens the time step to ensure accuracy when quantum effects are significant, and lengthens the step to improve efficiency when changes are gradual. This invention significantly reduces Hamiltonian complexity, balancing quantum accuracy and classical efficiency, and is applicable to various fields such as drug screening, materials design, and catalytic reaction simulation.

This invention discloses a microwave frequency conversion system based on quantum computing, comprising: a microwave acquisition unit for acquiring multi-beam microwave signals and performing quantum state encoding on the multi-beam microwave signals based on quantum Fourier transform to obtain the quantum spectral tensor space corresponding to the multi-beam microwave signals; a quantum encryption unit for performing quantum parallel processing of the compressed quantum state data and the encryption key stream based on controlled phase rotation gates to obtain encrypted quantum state data; and a frequency conversion unit for adjusting the qubit coupling strength of the encrypted quantum state data based on a quantum-controlled pulse sequence to obtain the multi-beam microwave signals after frequency conversion. This invention achieves more efficient spectral analysis and processing through quantum Fourier transform, thereby improving the speed of signal processing.

The present disclosure provides a system and method for a quantum money scheme. The system includes a bank note generator module configured for instantiating a set of elliptic curves, an abelian group, and a group action operation based on isogenies. The module initializes two registers in a joint state, computes the group action operation in superposition, applies a quantum Fourier transform to the first register, measures the first register to obtain a measurement outcome, and outputs a banknote comprising the measurement outcome as a serial number and a money state. The system may also include a verification module for verifying the banknote. The method follows similar steps. The quantum money scheme can be instantiated by isogenies over ordinary elliptic curves.

A quantum circuit, configured to process n qubits and d additional qubits, includes: a d-qubit Quantum Fourier Transform circuit configured to apply a d-qubit Quantum Fourier Transform to the d additional qubits; a plurality of parity-fan-out gates controlled by the n qubits and configured to control the additional d qubits, wherein each of the plurality of parity fan-out gates is coupled to a corresponding one a plurality of sets of additional phase gates that also apply phase angles to the d additional qubits, wherein quantum circuit implements a unitary of a bit function and wherein the sets of additional phase gates apply the phase angles to the d additional qubits based on a Walsh-Hadamard Transform of a conversion of the bit function to a binary number; and a d-qubit Inverse Quantum Fourier Transform circuit configured to apply a d-qubit Inverse Quantum Fourier Transform to the d additional qubits.

The application belongs to the technical field of heating system, and relates to a heating system environment sensing and multi-point water quality optimization dosing method, wherein real-time sensing and uploading of water quality data are realized through multiple sensor nodes, then deep periodic characteristics of the water quality data are extracted by using quantum state space mapping and quantum Fourier transform, a global optimal medicament combination strategy is solved in a constructed quantum optimization model by combining a quantum annealing algorithm, a medicament compatibility matrix is constructed by using tensor decomposition technology to integrate medicament characteristics and pipe network parameters, each dosing terminal calculates a dosing amount based on local sensing, consistency of dosing decisions is ensured through a PBFT consensus mechanism, finally, a flow velocity distribution characteristic of the pipe network is combined, a lead control algorithm is used to correct medicament injection time lag, dynamic prediction and accurate control are realized, and therefore, a breakthrough is realized in local adaptability, global coordination and dynamic responsiveness of the distributed dosing control system, and efficiency and stability of water quality regulation of the heating system are significantly improved.

A quantum circuit, configured to process n qubits and d additional qubits, includes: a d-qubit Quantum Fourier Transform circuit configured to apply a d-qubit Quantum Fourier Transform to the d additional qubits; a plurality of parity-fan-out gates controlled by the n qubits and configured to control the additional d qubits, wherein each of the plurality of parity fan-out gates is coupled to a corresponding one a plurality of sets of additional phase gates that also apply phase angles to the d additional qubits, wherein quantum circuit implements a unitary of a bit function and wherein the sets of additional phase gates apply the phase angles to the d additional qubits based on a Walsh-Hadamard Transform of a conversion of the bit function to a binary number, and a d-qubit Inverse Quantum Fourier Transform circuit configured to apply a d-qubit Inverse Quantum Fourier Transform to the d additional qubits.

A signal spectrum analysis method and apparatus, an electronic device, and a readable storage medium. The signal spectrum analysis method comprises: acquiring quantum superposition states obtained by performing quantum Fourier transform on signals to be analyzed, and acquiring a first mapping relationship and a preset tolerance error (S10); searching the first mapping relationship for a target sampling count matching the preset tolerance error, the target sampling count being inversely proportional to the preset tolerance error, and the preset tolerance error being characterized as a difference between a quantum probability distribution and an actual probability distribution of a same signal (S20); measuring the quantum superposition states a number of times equal to the target sampling count to obtain measurement results, the quantity of the measurement results being the target sampling count (S30); and, on the basis of the measurement results, determining a target quantum probability distribution of the signals to be analyzed (S40). The method solves the technical problem of low accuracy of quantum Fourier transform in spectral analysis.

This application discloses an audio steganography method, apparatus, and electronic device based on a quantum generative adversarial network (GAN). The method, applied at a transmitting end, includes: embedding the information to be steganized into original quantum initial-state data to obtain dense quantum initial-state data; performing time-domain feature processing on the dense quantum initial-state data through a generative network and obtaining the corresponding frequency-domain quantum state data; performing frequency-domain refinement processing on the frequency-domain quantum state data; converting the obtained frequency-domain refined data into target quantum state audio data through an inverse quantum Fourier transform; transmitting the target quantum state audio data to a receiving end through a quantum channel; and transmitting the quantum circuit parameters corresponding to the generative network to the receiving end through a classical channel. Implementing this application embodiment can optimize the time-frequency mixing processing flow while ensuring secure audio data transmission, effectively improving the imperceptibility of the steganographic information, thereby enhancing the security of information hiding.

The application discloses a pattern recognition method and device, and the method comprises the following steps: preparing a first quantum state based on the serial number of a reference sequence and the serial number of a target sequence; measuring the first quantum state on a specified quantum bit to obtain a first measurement result; performing inverse quantum Fourier transform on the first quantum state to obtain a second quantum state in response to the first measurement result being a target value; obtaining a target wave number based on a second measurement result; and obtaining an identification result of the to-be-identified object and the target object by using the target wave number and a preset threshold. The efficiency of pattern recognition is improved by using the embodiment of the application.

The invention discloses a distribution line fault positioning method and device and computer equipment. The method comprises the following steps: acquiring original signals acquired by each acquisition node in a distribution line to be tested at the same sampling moment according to a GPS time synchronization signal; performing quantum Fourier transform on the original signal to obtain a time-frequency characteristic of the original signal, and screening a fault signal from the original signal according to the time-frequency characteristic; determining energy characteristics of to-be-detected grids in the to-be-detected distribution line in a preset sampling time period according to the fault signal, and screening out a fault grid from the to-be-detected grids according to the energy characteristics; and determining the fault type of the to-be-detected distribution line according to the energy characteristics of the fault grid, and determining the fault position of the to-be-detected distribution line according to the target acquisition node corresponding to the fault grid. The wide-area synchronous measurement technology is adopted, the type of the fault in the distribution line is accurately judged, and the position of the fault is accurately positioned.

Systems, apparatuses, methods, and computer program products are disclosed for preparation of a quantum state encoding an approximate normal distribution (QSEAND) in a set of qubits. An example method includes initializing the set of qubits by preparing the set of qubits in an initial quantum state. The example method also includes encoding the approximate normal distribution in the quantum state of the set of qubits, wherein encoding the approximate normal distribution comprises preparing the set of qubits to be in a quantum state representing a plurality of Fourier coefficients, and applying an inverse quantum Fourier transform to the set of qubits in the quantum state representing the plurality of Fourier coefficients to obtain the QSEAND. The example method also includes utilizing the QSEAND, wherein the utilization alters or transfers the QSEAND.

The invention provides an intelligent processing method and device for a streptococcus pneumoniae serological response image, and relates to the field of data processing. According to the method, multispectral image data of a reaction product is obtained by using quantum dots with tunable emission characteristics in a composite reaction system, spectral components are generated through quantum Fourier transform and quantum matrix decomposition, and a spectral mode with unique spectral characteristics is obtained through quantum calculation optimization. Then, blind source separation and a deep self-encoding network are adopted to generate independent spectral components, and quantitative analysis and result optimization are completed in combination with spectral characteristics and concentration information. And finally, based on the quantitative analysis result, carrying out classification and identification, outputting the spectral mark and concentration value of each reaction product, and realizing accurate characterization of the reaction products. By implementing the technical scheme provided by the invention, the processing precision of the streptococcus pneumoniae serological response image can be improved.

The invention relates to the technical field of electronic information technology anti-counterfeiting, in particular to an intelligent document seal positioning method based on quantum compressed sensing and a pre-auditing system, which focuses on quantum and classical collaborative seal positioning technology, constructs a'preprocessing, sparse representation and positioning 'layered architecture, and realizes full-process fusion. The traditional limitation is broken through by a three-level noise reduction mechanism, median filtering, a quantum circuit and PSNR (Peak Signal to Noise Ratio) constraint; a dynamic mixed sparse base is adopted to adapt to various document types. Features are accurately extracted through multi-scale quantum Fourier transform, and a complex scene is adapted in combination with sub-pixel fitting. An error compensation closed loop is formed by means of quantum gate calibration, traditional bottlenecks in the aspects of positioning precision, processing efficiency and robustness are broken through, and a brand new solution is provided for government affair document seal positioning.