8 results about "Density matrix" patented technology

The invention relates to the technical field of bridge construction safety monitoring, and discloses a road and bridge construction multi-sensor data fusion safety early warning system. The system comprises a data preprocessing and quantum state characterization module, a heterogeneous tensor field construction and quantum correlation analysis module, a quantum topological structure analysis and risk area identification module, a non-equilibrium tensor field evolution and risk early warning module and an early warning output and visualization module. The method comprises the following steps: uniformly mapping multi-source heterogeneous sensor data into a density matrix in a high-dimensional Hilbert space, calculating quantum correlation degree quantity among the data to construct a multi-dimensional heterogeneous tensor field and a quantum correlation topological graph, and identifying a risk area and a propagation path by calculating topological invariants of the topological graph. And the risk critical point is predicted by monitoring entropy generation rate evolution of the tensor field. According to the method, the heterogeneous data can be deeply fused, the weak links of the structure can be identified from the system level, the risk evolution trend can be prospectively pre-judged, and the early-stage and interpretable early warning of the construction risk can be realized.

The present application relates to the technical field of quantum state preparation, and particularly relates to a multi-quantum state preparation method, comprising: S1, randomly initializing an Ansatz circuit parameter; S2, inputting an initial quantum state into a variational quantum circuit under a current circuit parameter configuration to obtain a corresponding output state density matrix; S3, calculating a loss value between the output state density matrix and a target state according to the output state density matrix, feeding back the loss value to a classical optimizer, updating the Ansatz circuit parameter, returning to S2 until a preset condition is reached, and obtaining a trained variational quantum circuit; and S4, using the trained variational quantum circuit to realize preparation of multiple groups of target quantum states. The present application learns and approximates to prepare any target quantum state by constructing a quantum neural network structure with expression capability.

The application discloses a method for calculating an interplanetary cross scaling coefficient according to particle phase space density correlation characteristics, comprising the following steps: obtaining particle flux sequences of a standard A star and a to-be-scaled B star; under a T89c external magnetic field model, respectively calculating a modified third adiabatic invariant and a second adiabatic invariant of the A star and the B star, and calculating a local magnetic field intensity; performing uniform grid division on time and the third adiabatic invariant, and performing logarithmic uniform grid division on the first adiabatic invariant and the second adiabatic invariant; obtaining a local pitch angle and energy in the grid; screening out points with data in the same grid to obtain particle phase space densities of the A star and the B star respectively; calculating a particle phase space density average in the grid; respectively establishing particle phase space density matrices of the A star and the B star; screening out points with data in the same grid of the particle phase space density matrices of the two stars to obtain a cross scaling coefficient of the B star.

The application discloses a kind of main distribution network power flow model no solution traceability and correction method, it is related to power system dispatching technical field, including, acquisition real-time measurement data pre-processing, obtain quantum noise intensity coefficient;Quantum state density matrix is generated based on quantum noise intensity coefficient, and quantum fidelity is obtained by characteristic decomposition mapping;Based on quantum fidelity, the minimum eigenvalue is extracted, and the fault node coordinates are located by no solution traceability mapping, and the fault severity index is obtained by negative exponential mapping;Based on fault severity index, no solution traceability grade is divided, and fault scene is output;Based on fault scene, the set of power flow inversion control instructions is obtained, and the power flow no solution risk early warning value is corrected.The quantum fidelity mapping accurately locates the power grid fault source, eradicates the main distribution network model no solution problem, promotes the landing of quantum sensing industry and improves the fault response speed.

The application discloses a two-bit and three-bit unknown state entanglement determination method based on a variational quantum circuit, and comprises the following steps: generating quantum states of a plurality of known state labels based on uniform sampling of a random matrix to obtain a quantum state data set containing a two-bit data set and a three-bit data set; extracting observable operator expectation values from the quantum state data set to generate a classical feature vector; encoding the classical feature vector to an initial quantum state through a parameterized quantum gate; constructing a variational quantum circuit, and making the initial quantum state evolve through the variational quantum circuit to obtain an output state; constructing an objective function based on quantum measurement results of the output state, and outputting an entanglement determination result of the quantum state data according to the objective function value. Compared with a quantum state tomography method which depends on complete density matrix reconstruction, the method only uses observable operator expectation values highly related to entanglement determination as input, and thus significantly reduces measurement resource consumption and classical post-processing burden.

This invention discloses a method and system for hydrological uncertainty analysis based on probability density envelopes, relating to the field of hydrology and water resources technology. The method includes: collecting time series data of hydrological elements and preprocessing them; generating a uniform grid and performing kernel density estimation at the grid points to obtain density estimates; resampling each series to obtain the density matrix of the samples; calculating the standard error of the grid points; constructing candidate subsets, prioritizing the minimization of the probability density envelope area and minimizing the difference between upper and lower overprobabilities as secondary objectives, and optimizing the selection of the optimal multiplier; using the optimal multiplier to calculate the lower and upper probability density envelopes at the grid points and calculating the overprobabilities; extracting feature parameters; and comparing and analyzing the uncertainties of hydrological elements at different stations based on the feature parameters. This invention does not require a pre-defined distribution, can adaptively construct the minimum area simultaneous confidence band, and provides multi-dimensional uncertainty indicators, providing a scientific basis for watershed hydrological analysis and risk management.

This application proposes a quantum state tomography method, apparatus, and storage medium. The quantum state tomography method includes: receiving quantum system specifications and measurement constraints; preparing multiple quantum state replicas based on the quantum system specifications and measurement constraints; analyzing the multiple quantum state replicas based on Hamiltonian evolution to obtain a manifold of a predetermined quantum state; selecting an optimal measurement basis according to the manifold of the predetermined quantum state; acquiring measurement data of the multiple quantum state replicas under the optimal measurement basis to form a compressed measurement set; and generating a compressed measurement protocol based on the compressed measurement set, including: selecting a preset reconstruction algorithm and reconstructing the quantum state density matrix based on the compressed measurement set and the preset reconstruction algorithm. Based on this, this application can exponentially reduce the amount of measurement data, achieve complete state reconstruction of large-scale quantum systems, and ensure reconstruction fidelity.

The application discloses a pseudo-pure state preparation method and device based on radio frequency field inhomogeneity. The pseudo-pure state preparation method comprises the following steps: performing a first unitary operation on a thermal equilibrium state of a nuclear magnetic resonance sample to obtain a first quantum state; performing a second unitary operation on the first quantum state, so that diagonal elements corresponding to nuclear spin polarization components in a density matrix of the first quantum state are rotated to a preset direction, and off-diagonal elements corresponding to nuclear spin polarization components are rotated to a direction perpendicular to the preset direction, to obtain a second quantum state; applying a radio frequency field with predetermined parameters to the second quantum state by using a radio frequency coil to perform a non-unitary operation, to obtain a third quantum state; and performing a third unitary operation on the third quantum state to rotate nuclear spin polarization components in the third quantum state to an initial direction, to obtain a pseudo-pure state of the nuclear magnetic resonance sample. The method does not need to use a gradient field, so that the preparation difficulty is reduced, and the preparation time is shortened.