33 results about "Quantum" patented technology

The invention discloses a rolling bearing generalization fault diagnosis method based on a quantum physical information neural network, and the method comprises the following steps: S1, obtaining vibration signals and working condition parameters in the operation process of a rolling bearing, and carrying out the preprocessing and domain division to obtain a meta-training set and a meta-test set; s2, constructing a quantum-physical information neural network model which comprises a quantum path and a physical path; s3, feature fusion and classification; and S4, based on physical perception element learning training, repeating inner ring-outer ring iteration until the model is converged. Compared with the prior art, the rolling bearing fault diagnosis field generalization method based on the quantum physical information neural network has the advantage that the field offset problem existing in a traditional fault diagnosis method is solved.

The invention discloses a coal rock gas dynamic reservoir-forming prediction method based on quantum physical adsorption, and relates to the field of coal rock gas dynamic reservoir-forming evaluation, and the method comprises the steps: building a gas quantum physical adsorption dynamics prediction model based on a non-equilibrium dynamics mechanism; dispersing the burial-uplift evolution process of the coal rock reservoir into a plurality of key evolution nodes; under the formation temperature corresponding to each key evolution node, respectively carrying out a non-equilibrium adsorption kinetics experiment of methane to obtain a non-equilibrium adsorption kinetics data set corresponding to each experiment; performing parameter inversion on the gas quantum physical adsorption kinetics prediction model according to the unbalanced adsorption kinetics data set and the temperature of each stratum to obtain a kinetics adsorption coefficient set and methane adsorption phase density; according to the parameters obtained by inversion and the prediction model, predicting the quantum physical adsorption behavior of the coal rock gas; according to the predicted adsorption behavior, coal rock gas dynamic reservoir forming is predicted, and the process that the adsorption capacity changes along with time can be described.

A method for simulating a quantum-capacitance response of a material configuration comprises (a) constructing a non-interacting Hamiltonian for the material configuration based on input data; (b) computing a natural-orbitals basis for each of a plurality of parts of the material configuration under the non-interacting Hamiltonian; (c) projecting the non-interacting Hamiltonian in the natural-orbitals basis to obtain a non-interacting quantum-mechanical description for each part; (d) constructing an interacting Hamiltonian by adding an electron-interaction term to the non-interacting Hamiltonian for each of the plurality of parts; (e) for each of a plurality of representative points in a sample space of at least one tunable parameter of the material configuration, using a sums-of-Gaussians procedure to assemble a basis of Gaussian states for approximating low-energy eigenstates of the material configuration under the interacting Hamiltonian; (f) for each of a plurality of vicinities of representative points in the sample space, combining bases of Gaussian states assembled for nearby representative points to form an extended basis; and (g) forecasting the quantum-capacitance response within the sample space using the extended basis.

A method for simulating a quantum-capacitance response of a material configuration comprises (a) constructing a non-interacting Hamiltonian for the material configuration based on input data; (b) computing a natural-orbitals basis for each of a plurality of parts of the material configuration under the non-interacting Hamiltonian; (c) projecting the non-interacting Hamiltonian in the natural-orbitals basis to obtain a non-interacting quantum-mechanical description for each part; (d) constructing an interacting Hamiltonian by adding an electron-interaction term to the non-interacting Hamiltonian for each of the plurality of parts; (e) for each of a plurality of representative points in a sample space of at least one tunable parameter of the material configuration, using a sums-of-Gaussians procedure to assemble a basis of Gaussian states for approximating low-energy eigenstates of the material configuration under the interacting Hamiltonian; (f) for each of a plurality of vicinities of representative points in the sample space, combining bases of Gaussian states assembled for nearby representative points to form an extended basis; and (g) forecasting the quantum-capacitance response within the sample space using the extended basis.

This parameter adjustment device comprises a determination means for, for a quantum annealing machine having a structure indicated by an LHZ model, performing at least one of: setting a quantum annealing time to a value that is one time the product of Dirac's constant and the reciprocal of a coefficient value of a term of a longitudinal magnetic field of the Hamiltonian of a model embedded in the LHZ model; and setting a four-body interaction coefficient value to a value the magnitude of which is at least five times the coefficient value of the term of the longitudinal magnetic field of the Hamiltonian of the model embedded in the LHZ model.

A method for performing state estimation for a microgrid system includes: obtaining a general quantum state estimation model for swing- bus-contained microgrid systems; establishing a state estimation formulation through quantum language; assigning multiple quantum registers used during a quantum state estimation iteration; generating a quantum-circuit-based state estimation solver for performing quantum phase estimation, controlled rotation, and inverse quantum phase estimation; generating a preconditioned quantum linear sol for an illconditioned state estimation iteration; iteratively optimizing voltage and residual vectors while iteratively updating preconditioned errors by the quantum-circuit-based state estimation solver, the optimizing and updating iterations continuing until the preconditioned quantum linear solver reaches convergence; obtaining a quantum state estimation model for hierarchical-based microgrid systems including droop and / or secondary control modes; establishing an enhanced quantum state estimation framework and generating an enhanced state estimation output for controlling one or more parameters of the microgrid system.

The invention discloses a liquid cooling electronic equipment cavity flow field prediction method based on a quantum physics neural network, and relates to the technical field of electronic equipment thermal management and computational fluid mechanics numerical prediction. Comprising the following steps: constructing a physical model of flow and heat transfer in the liquid cooling cavity; collecting or generating multi-source supervision data, and performing normalization processing; constructing a hybrid physical neural network structure with a quantum feature head; designing a total loss function containing multiple physical constraints and local weighted terms; carrying out iterative training by adopting a late time and hot plume region oversampling strategy; and utilizing the trained quantum physical neural network to quickly predict the flow field and the temperature field in the cavity under different working conditions. By constructing a hybrid physical neural network model and integrating multi-source supervision, partial differential equation residual error, boundary condition constraint and gradient sensing items of local thermal plume and thermocline in a loss function, high-precision prediction of a three-dimensional flow field and a temperature field in the liquid cooling cavity is realized.

The application discloses a method for preparing a two-dimensional ultracold atomic gas by optimizing adiabatic compression, and belongs to the technical field of ultracold atomic physics and optical lattice. The method takes the quantum adiabatic evolution of a three-dimensional ultracold atomic gas in an adjustable period optical lattice as a physical model basis, and equivalently describes the motion of atoms in the lattice bound direction as a one-dimensional quantum harmonic oscillator system varying with an external parameter. In the lattice compression process, the instantaneous energy level structure of the system evolves with time, and the minimum energy gap region between the lowest energy level and the first excited state is the main source of non-adiabatic transition. A non-adiabatic parameter is introduced to simultaneously describe the relationship between the instantaneous energy gap and the scanning rate of the parameter, which is used for quantitative evaluation of the adiabaticity of the system, and the Landau-Zener non-adiabatic transition model is combined to design and optimize the scanning curve of the lattice compression. The scheme can effectively reduce the probability of non-adiabatic excitation in the compression process, and significantly shorten the lattice compression time under the premise of ensuring the adiabatic evolution of the system.

This invention discloses a quantum-inspired adaptive crushing and spatiotemporal coordination mining method, belonging to the field of ore mining technology. It includes: real-time acquisition of ore and rock parameters during drilling to construct a three-dimensional dynamic barrier field characterizing the crushing difficulty; dynamic adjustment of the crushing equipment's operating frequency and energy waveform based on the barrier field value, achieving efficient crushing through coherent enhancement with the inherent frequency of the ore and rock; mapping crushing points to transportation units to construct spatiotemporal coordination unit pairs, defining the coupling relationship between discharge rate and arrival time using a preset state correlation function; maintaining a probabilistic superposition state of candidate paths for the mobile equipment, triggering probabilistic collapse decisions based on the local environment; and dynamically adjusting the coupling strength of the coordination unit pairs based on mining efficiency to evolve the optimal coordination mode. Inspired by quantum mechanics, this invention achieves on-demand energy supply, precise crushing-transportation coordination, and intelligent path decision-making through classical physics field simulation, significantly improving energy utilization, system robustness, and overall production efficiency.

The invention provides a clump electrostatic field force quantum radiation expression and an application method thereof, and relates to the crossing field of basic physics theory and applied physics. According to the clump electrostatic field force quantum radiation expression, traditional electromagnetic parameters are replaced with the constant number of clump characteristics radiated in basic charge unit time, and quantization expression of electrostatic force calculation is achieved. According to the invention, by introducing a sub-momentum exchange model and a small month constant, a quantum radiation expression of an electrostatic field force uses a Planck constant, a light velocity and a quantum number to successfully eliminate charge dimensions of basic charges e and epsilon 0; the formula and the derivation process completely provide a new understanding mode for a microscopic, clear and innovative operation mechanism of the electric field force from the angle of quantum radiation.

The invention discloses a quantum field theory high-performance coprocessor based on path integration and a method thereof, and belongs to the field of high-energy physical calculation, particle collision simulation, quantum color dynamics and quantum gravity calculation. Comprising a functional integral discretization engine (FIDE), a Feynman graph automatic generator (FAGG), a Wick contraction accelerator (WCA), a reformer group flow engine (RGFE), a path integral Monte Carlo sampler (PIMCS), a correlation function calculation unit (CFCU), a symmetry breaking detector (SSBD), a vacuum energy extractor (VEE), a Fermi determinant solver (FDS), a topological charge calculator, a circle graph integral optimizer, a Ward identical verifier and a cross-theory mapper. A hardware acceleration interface; according to the invention, an ASIC + GPU + quantum mixed framework is adopted, leading-edge applications such as LHC collision cross section prediction, quark gum plasma simulation, dark substance interaction calculation, early universe phase change research, quantum gravitational non-perturbation effect and the like are supported, and accurate inspection of a particle physical standard model and new physical search beyond the standard model are promoted.

The invention discloses a time sequence fusion and classification method based on a quantum evidence theory. The method comprises the following steps: converting a time sequence to a frequency domain based on DFT; screening a front low-frequency component by using TFI; amplitude and phase features are extracted respectively, and a GFN model is established; the CDGFN is constructed to represent the two-dimensional uncertainty at the same time; generating a quantum basic probability amplitude QBPA function represented by a complex value in a quantum evidence theory (QET); using a quantum evidence combination rule (QECR) in the QET to fuse the multi-frequency information to generate quantum basic probability distribution (QBPD); and finally, performing classification decision based on the quantum Pignistic probability in the QET. According to the method, the complex number dual Gaussian fuzzy number (CDGFN) and the frequency domain feature extraction technology are introduced, so that the problems of missing of two-dimensional uncertainty expression, difficulty in time domain alignment, low small sample classification precision and the like in an existing time sequence classification method are effectively solved, and the classification accuracy is improved.

The invention relates to the technical field of hydrology and water resources, in particular to a complex water area flow direction recognition method and system driven by multi-source data, and the method comprises the following steps: S1, constructing a standardized water area feature data set through integrating multi-dimensional information of hydrological observation, remote sensing images and topographic data, and through denoising, space-time alignment and feature extraction; and S2, based on a quantum path superposition principle, fusing multi-source data and fluid mechanics constraints, and constructing a physical enhanced quantum path guidance model of flow direction probability distribution through non-Hermitian evolution and an adaptive weight strategy. According to the invention, through innovative combination of multi-source data depth fusion and quantum mechanics principles, the dynamic evolution process of complex water area water flow under multi-factor interference is accurately described, and the precision and robustness of flow direction identification and the adaptability to complex terrains are significantly improved. And efficient and reliable technical support is provided for shipping safety, pollution prevention and control and other applications of complex water areas.

Apparatus and method for compiling and executing hybrid classical-quantum programs. For example, one embodiment of a method comprises: reading source code specifying both non-quantum operations to be performed by a host processor and quantum operations to be performed by a quantum accelerator; compiling the source code to generate a target object file, wherein portions of the source code specifying the quantum operations are compiled into quantum basic blocks (QBBs) in the target object file, each QBB comprising one or more quantum instructions to be executed by the quantum accelerator and wherein portions of the source code specifying the non-quantum operations are compiled into native instructions to be executed by the host processor.

The invention discloses a multi-modal flow channel health monitoring and intelligent diagnosis method, and relates to the technical field of electronic equipment thermal management, and the method comprises the steps: collecting a multi-modal signal in real time, carrying out the timestamp alignment through a hardware timestamp counter, and generating a multi-modal signal matrix; based on the multi-modal signal matrix, acoustic texture features are extracted through recurrence plot transformation, and the acoustic texture features are fused with the fractal feature vector and the magnetic field gradient feature matrix to generate a multi-modal feature tensor; and performing node-level feature aggregation on the multi-modal feature tensor through a dynamic space-time diagram attention network to generate a fault probability thermodynamic diagram, and generating a runner health index through a weighted probability integral algorithm. According to the method, physical field conversion of fault probability distribution and high-sensitivity identification of weak abnormal signals are realized through a quantum mechanics potential energy field conversion and tunneling effect driven non-maximum suppression algorithm.

The task of the invention is to construct a low-altitude management system for controlling safe flight of all nationwide low-altitude aircrafts in real time through a low-altitude management wide area network by adopting a new-generation information technology, integrating remote sensing and GPS navigation technologies and the like. The axiom physics is a physical basic theory of a new generation of information technology, GPS navigation technology and the like. The invention depends on five laws in'axiom physics' to solve the world problem of physics publication. Wherein the macroscopic axiom physics constructed by two object essential laws is expected to replace the classical mechanics and relativistic theory. The microcosmic axiom physics created by two particle natural laws can derive five public settings in quantum mechanics, and has potential to replace quantum mechanics. In addition, a particle phase invariant theorem is deduced according to a basic force law in a particle access theory.

Methods, systems, and techniques for detecting errors in qubits within a quantum computing system. In at least one embodiment, at least one quantum check operator is used to couple data qubits with syndrome qubits, a parity-check code is used to couple the syndrome qubits with measure qubits, and the measure qubits are measured to determine whether any errors are present in the data qubits. In at least one embodiment, codewords are coupled to one or more ancilla qubits based at least in part on a binary matrix associated with one or more non-Calderbank-Shor-Steane ("non-CSS") quantum codes, and the one or more ancilla qubits are used to obtain information about any errors present in the codewords.

The invention discloses a Gaussian sum method for solving a multi-body Schrodinger equation through a tensor neural network, and relates to the field of quantum physics. According to the method, the kernel decomposition technology of the coulomb kernel is introduced into the framework of solving the multi-body Schrodinger equation through the tensor neural network, and the problem of low calculation efficiency caused by difficult coulomb kernel tensor representation is successfully solved. On the basis of an existing tensor neural network framework, a Gaussian sum decomposition method is introduced for development, a set of complete self-adaptive secondary processing strategy is developed for high-dimensional integral calculation of electron-atomic nucleus and electron-electron interaction with the maximum time and memory overhead, the memory overhead is remarkably reduced, and meanwhile the calculation efficiency is effectively improved.

The invention introduces a Total Wave structure of the Modified Schrödinger Equation (MSE) that deterministically governs quantum collapse using co-evolving field-specific wave-functions. Unlike conventional quantum mechanics, which treats wavefunction collapse as a postulated or probabilistic phenomenon, this invention models collapse as a structured outcome of wave interference from multiple physical fields—electromagnetic, gravitational, strong nuclear, and weak nuclear—each governed by its own nonlinear MSE.The system wavefunction Ψp evolves under the influence of these field-specific observer waves Ψj, and collapse occurs when the total interference term exceeds a defined threshold. This model supports not only collapse but also resonance (sub-threshold wave alignment) and non-collapse (persistent superposition), forming a tri-state mechanism of existence.The Total Wave MSE formalism applies to quantum hardware design, computation, sensing, and AI-guided control. By treating collapse as an engineered interference event, the invention enables deterministic reality selection across multiple domains. It extends the scope of earlier MSE patents and proposes that this structure represents a scalable, tunable, and physically grounded Theory of Everything (TOE).

A system and method for trading and risk management are disclosed. The invention introduces a Q-Score framework derived from the Total Wave Modified Schrödinger Equation (TWMSE), using five quantum physics indicators: price curvature, phase interference, amplitude-amplitude interaction, amplitude-charge interaction, and volatility-price correlation. A genetic algorithm optimizer adapts indicator weights by asset and regime, generating buy, sell, or neutral signals. Collapse-based logic enables abstain states, reducing false positives. Integrated risk protocols include adaptive sizing, pyramiding, and turnover controls. Tests on equities and FX in August 2025 confirm robustness, supporting institutional use in adaptive, explainable platforms. This Continuation-in-Part extends prior wave-collapse inventions into the domain of financial markets, providing a physics-inspired, adaptive, and transparent system that bridges theoretical innovation with practical trading execution across diverse asset classes.

The invention discloses a quantum radiation algorithm and system based on cluster dynamic nuclear force and electric field force unification, and relates to the technical field of crossing of theoretical physics, quantum field theory and high-energy physics, and by introducing a cluster dynamic nuclear force-electric field force unification quantum radiation expression, Yukawa potential is regressed in a short-range region, and is degraded into coulomb force in a long-range region, so that the Yukawa potential in a short-range region is reduced. Seamless transition of two kinds of force is achieved, different energy regions are automatically adapted by introducing the nuclear vibration frequency, and equations do not need to be manually switched.