34 results about "Schrödinger equation" patented technology

The invention relates to the technical field of financial science and technology, in particular to an enterprise credit risk quantification method, which comprises the following steps of: writing finance, Internet of Things, bill chains and remote sensing data characteristics into a data lake in a homomorphic encryption manner to generate a federated event grid; a causal topology hypergraph is constructed, topology and multi-scale frequency domain features are extracted to form node representation, and node states and weights are updated through fractional order graph differential; the mapping hypergraph is a silicon light Mach-Zehnder phase, and node state superposition impact pulse is injected into a photon interference network to obtain optical readout; the spiking neural network-reinforcement learning agent reads out the generation management action to form a reserve tensor; and solving a discrete Schrodinger equation in combination with the tensor and graph Laplacian, and outputting a risk entropy potential and a prediction period default probability confidence interval through fractional order path integral correction. According to the invention, privacy protection, high-order structure identification and long-tail sensitivity are realized, and real-time and auditable credit risk assessment is realized.

This Continuation-in-Part extends the wave-interference-based collapse model first proposed in the Modified Schrödinger Equation (MSE) framework to five foundational quantum phenomena: tunneling, entanglement, measurement collapse, time asymmetry, and the resolution of Many-Worlds interpretations.The invention models collapse as a physical consequence of interference between the observer wave and the quantum system wavefunction, characterized by a curvature-based localization mechanism. This framework enables tunable collapse control, non-binary measurement outcomes, and outcome selection through engineered interference, providing a unified physical mechanism with broad technological applications.

We propose a hybrid wave-based logic model for optical computing that integrates both Total Wave Modified Schrödinger Equation (TWMSE) formulations and non-TWMSE interference field logic. This system enables deterministic collapse behavior through physical wave interactions, rather than relying on conventional transistor logic or probabilistic quantum models. In the TWMSE regime, collapse thresholds are governed by field interference between signal and control waves, allowing dynamic selection of tasks based on intensity and phase alignment. In the generalized non-TWMSE regime, similar collapse-like logic can be achieved using thresholded interference models that are classically engineered for optical domain systems. Together, these formulations enable adaptive task selection, nonlinear logic gating, and scalable parallel processing in optical chips. Our architecture supports real-time wavefield decisions and is compatible with standard photonic components such as interferometers, microring resonators, variable attenuators, and optical threshold comparators. The result is a unified logic framework for next-generation AI hardware that harnesses both quantum-inspired and classical wave interference dynamics.

A computing device including a processor configured to simulate a quantum device at least in part by receiving a single-particle Hamiltonian matrix that describes an initial Hamiltonian operator. The initial Hamiltonian operator may model a plurality of parts of a quantum device. Simulating the quantum device may further include estimating a reduced density matrix associated with a first part, estimating a plurality of eigenvectors and eigenvalues of the reduced density matrix, and generating a transformed Hamiltonian matrix. Generating the transformed Hamiltonian matrix may include transforming the single-particle Hamiltonian matrix into a natural-orbital basis of the first part such that the transformed Hamiltonian matrix has a reduced dimensionality. The natural-orbital basis may be spanned by a subset of the eigenvectors of the reduced density matrix. Simulating the quantum device may further include generating and outputting an estimated solution to a Schrödinger equation that includes the transformed Hamiltonian matrix.

A method for generating a training dataset for use in training a machine learning model to predict the solubility of a material in at least one solvent, the method comprising: inputting a selection of hypothetical materials (solute and solvent) from a parameter space; using a thermostat to set a specific temperature value;Using a classical computer to apply a path integral molecular dynamics (PIMD) technique to calculate a free energy change between a first state of the solute-solvent system and a second state of the solute-solvent system, wherein the forces acting on the nuclei of the solute-solvent system used by PIMD are determined by numerically solving the electronic Schrödinger equation of a quantum system representing the solute-solvent system on a quantum computer; calculating the solubility of the solute in the solvent at the specific temperature value; adding an entry to the training dataset;

The invention discloses a machining wear prediction method, and relates to the technical field of machining monitoring and intelligent prediction. The method specifically comprises the following steps that the quantum state dynamic state of microscopic particles on the contact interface of the cutter and a workpiece is described through a quantum mechanics equation frame, and the frame is constructed based on a Schrodinger equation containing dissipation items; in response to input machining parameters and cutting force data, the total energy of the machining process is output through a data driving prediction module, and the machining parameters comprise the cutting speed, the feeding amount, the tool rake angle, the cutting depth and the cutting width; when the total energy output exceeds a set threshold value, analyzing a quantum mechanics equation through a solving module embedded with physical constraints to obtain microscopic particle wave function probability distribution; on the basis of wave function probability distribution, particle transition behaviors are calculated through a cross-scale mapping module, the macroscopic tool abrasion loss is associated, and therefore an abrasion prediction value is generated. The method aims at improving the accuracy of tool wear prediction based on the quantum mechanics theory and the quantum machine learning technology.

A method for evaluating stability of a corrosion-resistant material. The method is implemented by means of a damped Schrödinger equation transformed on the basis of a Mathieu equation. The damped Schrödinger equation transformed on the basis of a Mathieu equation is: equation (1), wherein ψ the molecular motion state of the corrosion-resistant material, formula (2), formula (3), formula (4), the second term c of the equation is a "spatial damping" term, and on the basis of various properties of the corrosion-resistant material, h is a reduced Planck constant, m is the mass of a particle, Ko is a wave number, and Vo is a constant term, so that parameters a and b are calculated. Therefore, the stability of the material can be evaluated.

The invention relates to the technical field of sample labeling, in particular to a quantum inspired active learning type defect detection sample labeling method which can reduce the manual labeling amount and the labeling cost. Specifically, sample representativeness and uncertainty are balanced through unified process design, firstly, a center cluster set is obtained based on Hamiltonian operator clustering, secondly, the quantum entanglement degree is calculated, a representative sample set is screened, residual unlabeled sample sets are processed in combination with virtual time evolution and a Schrodinger equation, and a to-be-labeled sample set is obtained through a fusion result; a budget scene does not need to be distinguished, sample selection can be adaptively optimized, the labeling efficiency is improved, and the problem of strategy simplification is effectively solved; in addition, samples are mapped into quantum states through self-supervised learning, clustering precision is optimized based on Hamiltonian operators, quantum entanglement is utilized to quantify sample association, uncertainty is captured by means of virtual time evolution and a Schrodinger equation, the quality of labeled samples can be improved, and the problem of representation limitation of a classical framework is solved.

A system and method for implementing artificial intelligence using deterministic wave interference and collapse logic derived from the Total Wave Modified Schrödinger Equation (TWMSE). An artificial agent is modeled as a system wavefunction interacting with one or more observer wavefunctions representing electromagnetic, gravitational, weak, or strong fields. A collapse function determines when interference exceeds a threshold, producing deterministic action or comprehension. Field parameters adapt through feedback to enable learning, residual interference forms resonant memory, and computation is performed directly on optical, electromagnetic, or neuromorphic hardware. The invention provides a unified framework—Total Wave Artificial Intelligence (TWAI)—that integrates action, understanding, learning, memory, and physical embodiment through field-based collapse rather than probabilistic inference.

This invention relates to the field of traffic safety technology, specifically to an efficient simulation method for quantum systems based on parallel order reduction. The method includes the following steps: receiving the physical parameters of the quantum system and simulation requirements, whereby the physical parameters include electron mass, potential well size, and initial wave packet parameters; and the simulation requirements include simulation physical time and accuracy requirements. Based on the physical parameters, a time-dependent Schrödinger equation describing the dynamic behavior of the quantum system is established, and the Schrödinger equation is rearranged into matrix form using the Kronecker product. This invention utilizes Arnoldi to reduce the order of the matrix-form Schrödinger equation. By reducing the order, the large matrix in the original space is projected into a relatively small subspace, improving the efficiency of the simulation solution. The reduced-order Schrödinger equation is solved using a time-parallel algorithm. This approach overcomes the time step limitation imposed by the CFL condition, ensuring that a stable solution can be obtained with fewer time steps.

System and method for simulated quantum annealing to solve optimization problems. The method comprises performing simulated quantum annealing by: generating quantum annealing simulations of an objective function that represents an optimization problem by initializing a guiding wave function with a variational ansatz, wherein the guiding wave function represents a ground state wave function of a quantum optimization Hamiltonian that the objective function represented as a classical Hamiltonian and a non-commutating driving term causing quantum fluctuations; stochastically evolving the quantum annealing simulations under a time-dependent driving schedule according to an imaginary-time Schrödinger equation supplemented by the guiding wave function until a predetermined condition is met; and outputting a plurality of output states responsive to the predetermined condition being met, each output state representing a solution to the optimization problem of the application-specific parameters within the application-specific constraints.

The invention relates to the technical field of molecular electronic structure calculation, and provides a diatomic molecule electronic structure calculation method and system, and the method comprises the steps: obtaining a medium-range potential energy curve and a dipole moment through solving an electronic Schrodinger equation based on the structure and electronic state properties of a diatomic molecule, and obtaining a whole-range potential energy curve through the perturbation theory; wherein when the Schrodinger equation of electrons is solved, the position of an atomic nucleus is fixed, and kinetic energy items, related to the atomic nucleus, in the total Hamiltonian amount of diatomic molecules are ignored. The method can meet the current requirements in the fields of hypersonic aircraft thermal design, reentry aircraft thermal design, ablation process detection, combustion process regulation and control, target identification and diagnosis, earth atmospheric environment monitoring and evaluation, celestial body formation and evolution, plasma transport simulation and the like, and has important engineering application value.

The invention relates to a method for solving the Schrödinger equation ( H Ψ = E Ψ ) . In this eigenvalue equation, the Hamilton operator describes (H) the physical problem. The procedure is designed to find the corresponding wavefunction (Ψ) and energy (E) to solve the eigenvalue problem. The procedure includes the following steps: - Transforming the eigenvalue problem ( H Ψ = E Ψ ) into a nonlinear differential equation by replacing the wavefunction (Ψ) by Ψ = g ⋅ ef is replaced, - Inserting EQN011 into the eigenvalue problem, where (f) is a numerical function and (g) is a modulation function, which is important for excited states, - Applying an iterative process to calculate (f) and adjust (g), which can be terminated when sufficient accuracy is achieved, - Determine the wave function (Ψ) by inserting the determined values ​​for (f) and (g) into equation EQN011.

This invention presents a systems-level application of observer-induced collapse theory, enabling targeted localization of quantum states using engineered observer wavefunctions across three domains: quantum memory control, biological feedback systems, and AI-guided collapse operations. Building upon the Modified Schrödinger Equation (MSE), collapse is modeled as a curvature-driven localization event initiated by dynamic convergence between an external observer wave Ψo(t) and the system wavefunction Ψp(t), satisfying Ψp ′(t)>δ. The invention implements this principle through three interlinked models: (1) quantum memory write / read collapse, (2) biological signal-induced collapse for diagnostics or feedback devices, and (3) AI-generated observer waves for active system control and optimization. Each framework supports both physical and algorithmic implementation, including analog interference sources, neural feedback circuits, and reinforcement-trained models. This Continuation-in-Part introduces observer-controlled wave collapse as a functional mechanism for quantum information storage, medically responsive systems, and decision-optimized AI systems, offering a unified framework for engineered collapse in probabilistic environments.

Encoding a target state on a quantum computing system (QCS) using a classical computer to model the QCS using a time-dependant Schrodinger equation: the equation includes boundary conditions (BCs) pro

The invention provides a spatial layout automatic division method based on quantum mechanical simulation and competitive region growth. The method comprises three core stages of quantum system modeling, wave function evolution simulation and constraint region allocation. According to the method, firstly, functional attributes of space units are converted into quantum mechanical parameters, and optimal distribution of the positions of the space units is achieved through three-stage Schrodinger equation evolution including a high-temperature quantum state, a medium-temperature coherent state and a low-temperature ground state; and then, based on a quantum simulation result, generating a spatial layout meeting the area proportion requirement of each partition by adopting a weighted Voronoi initialization and competitive boundary adjustment algorithm, and finally, carrying out image processing to obtain a layout scheme. According to the method, through organic combination of a quantum mechanics framework and a region growth mechanism, automatic conversion from functional requirements to spatial layout is realized, the spatial relationship reasonability is kept while the area constraint is met, and a physically inspired calculation solution is provided for the fields of building information modeling and spatial planning.

This invention discloses a quantum correction method for drift-diffusion transport in gallium nitride (GaN) power devices in advanced packaging and an electrothermal coupling simulation method for three-dimensional integrated modules. The method obtains the sub-band energy levels, corresponding wave functions, and potential distributions along the quantum confinement direction by self-consistently solving the one-dimensional stationary Schrödinger equation and the two-dimensional Poisson equation. The convergence of the self-consistent algorithm is improved by modifying the Poisson equation. Furthermore, quantum correction of the drift-diffusion equation is achieved by modifying the conduction band. Based on quantum confinement effects and drift-diffusion transport theory, this invention studies the quantum effects of the two-dimensional electron gas in the triangular potential well formed by GaN polarization and the quantum correction method for the drift-diffusion transport model. It evaluates the steady-state operating characteristics of advanced packaged power devices containing quantum effects and further investigates the electrothermal coupling simulation method between the device and the three-dimensional integrated module to evaluate the thermal management capabilities of the three-dimensional integrated module, demonstrating significant application value.

The application discloses a carrier transport simulation method and device, a medium and an electronic device. The application determines initial conditions and / or boundary conditions of carrier transport in a semiconductor device, and determines a Poisson equation and a Schrodinger equation corresponding to a closed quantum model. The carrier density in the semiconductor device is determined based on the initial conditions and / or the boundary conditions, the Poisson equation and the Schrodinger equation, so as to realize simulation of the carrier transport in the semiconductor device, and further realize research on the carrier transport in the semiconductor device.

This Continuation-in-Part extends the wave-interference-based collapse model first proposed in the Modified Schrödinger Equation (MSE) framework to five foundational quantum phenomena: tunneling, entanglement, measurement collapse, time asymmetry, and the resolution of Many-Worlds interpretations. The invention models collapse as a physical consequence of interference between the observer wave and the quantum system wavefunction, characterized by a curvature-based localization mechanism. This framework enables tunable collapse control, non-binary measurement outcomes, and outcome selection through engineered interference, providing a unified physical mechanism with broad technological applications.

The application provides a neural network prediction method and device for two-dimensional quantized vortex dynamics, and the method comprises the following steps: S1. For a flow field to be predicted, a two-dimensional vortex dynamics equation of the flow field is determined, and the two-dimensional vortex dynamics equation is converted into a Schrodinger equation of a quantum system; S2. Wave function evolution data of the quantum system is obtained according to the Schrodinger equation, and a wave function data set is generated; S3. A full connection layer neural network model is constructed, and phase integration is performed on the full connection layer neural network model; S4. A normalization factor is introduced into the full connection neural network model; S5. The full connection layer neural network model is trained by using the wave function data set; S6. The trained full connection layer neural network model is used to predict a wave function according to a given initial value; and S7. The predicted wave function is converted into flow field evolution. According to the method provided by the application, the conservation law of the system can be ensured in the prediction of the Schrodinger system, so that the accuracy of the flow field prediction can be ensured in a long period.

A method for node cluster assignment in a graph includes identifying neighboring nodes of a first node in the graph, calculating one or more elements of a graph Laplacian of the graph, the one or more elements of the graph Laplacian corresponding to the first node and the neighboring nodes, initializing a first wavefunction associated with the first node with an initial value, evolving the first wavefunction associated with the first node over time based on the initial value, the one or more elements of the graph Laplacian, and previous states of wavefunctions of the neighboring nodes to generate a time-evolved wavefunction vector, and identifying a cluster assignment of the first node based on the time-evolved wavefunction vector.

The invention refers to a method for solving the Schrödinger equation (Ψ=EΨ), wherein a Hamilton operator () describes the physical problem underlying the eigenvalue problem, the method being adapted to find a corresponding wave function (Ψ) and an energy (E) to solve the eigenvalue problem, the method comprising the following steps: transforming the eigenvalue problem (Ψ=EΨ) into a non-linear differential equation by replacing the wave function (Ψ) byΨ=g·efEQN001and inserting EQN011 into the eigenvalue problem, where f is a numerical function which needs to be computed and g is a modulation function, finding a solution for the numerical function (f) in an iterative process, aborting the iterative process when an abort condition is fulfilled, and with the found solution for the numerical function (f), calculating the wave function (Ψ) from EQN011.

The invention discloses an intelligent traffic dynamic path optimization method based on an infinite graph structure, which solves the problem of a unique solution of a p-Laplace Schrdinger equation on a dynamic traffic network by defining a pseudo-metric constraint and a weighted space of the traffic network, combining positive qualification of a potential function and designing a differential analysis process for a parameter range. And therefore, real-time path optimization is realized. According to the method, a traffic network is abstracted into an infinite weighted graph, nodes are intersections, side weights are real-time passing time, network geometric conditions and potential function constraints are verified, judgment branches are selected according to traffic state parameters, and road network flow steady-state distribution is determined through a unique solution. An energy inequality or a convex regularization test function is respectively constructed for congestion and non-congestion situations, uniqueness of a solution is proved in combination with a limit process, and a signal lamp period and a path recommendation strategy are dynamically adjusted, so that the problems of difficulty in congestion propagation modeling and low real-time path planning precision in a dynamic road network are solved.

A time-dependent Hamiltonian, H(t), of the quantum system comprising time-dependent terms representing the control signal is identified. A control problem is defined for evolving one or more time-dependent operators, I(t), from one or 10 more initial operators into one or more respective target operators under the dynamics of an equation of motion given by the time-dependent Hamiltonian, wherein each eigenstate of the one or more time-dependent operators is a solution to the time-dependent Schrödinger equation given by the time-dependent Hamiltonian, allowing a control signal based on the control problem to be determined. The time dependent operator may be a Hermitian operator with a vanishing total time-derivative, and the time dependent operator’s eigenstates may be non-degenerate, and represented by tensor networks or matrix product operators.

The application relates to a quantum gate simulation and control parameter optimization method based on numerical calculation, which sequentially comprises the following three modules: a model Hamiltonian matrix representation module which can calculate the matrix representation of the model Hamiltonian according to specific problems; a system time evolution and fidelity calculation module which uses the Hamiltonian matrix to discretely solve the Schrodinger equation, gives the corresponding time evolution matrix, and calculates the gate operation fidelity by using the obtained time evolution matrix; and a control parameter optimization module which calls the previous two modules, adopts a local optimization algorithm or a global optimization algorithm to optimize the control parameters and the quantum gate operation time, and gives the optimal control parameters and the gate operation time. The application solves the problem that the gate fidelity of the current superconducting quantum computing system cannot meet the requirements of reliable operation of practical quantum algorithms, can simulate the detailed process of quantum gate operation through the numerical calculation method, and improves the quantum gate operation fidelity through the optimization of the control parameters.

A system and method for cryptographic decryption using deterministic collapse resonance based on the Total Wave Modified Schrödinger Equation (TWMSE). An encrypted problem state is encoded as a system wavefunction, while candidate solutions are represented as observer wavefunctions. A collapse field with tunable parameters ensures destructive interference cancels incorrect candidates and constructive resonance deterministically selects the correct solution. Unlike brute-force search or probabilistic quantum measurement, the method achieves decryption in a single engineered collapse. Hardware embodiments include optical photonic systems, neuromorphic processors, and resonant field architectures. Applications extend to RSA, Diffie-Hellman, elliptic curve cryptography, lattice-based post-quantum protocols, blockchain, and secure messaging frameworks. Proof-of-concept demonstrations on small instances, including factorization of $N=15$, illustrate feasibility at toy scale. Scaling to larger cryptosystems is envisioned through adaptive parameter control, resonance calibration, and experimental implementation.

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.

A method for generating a training dataset for training a machine learning model to predict a specific property of a material is disclosed. The method comprises repeatedly performing the following: selecting a hypothetical material from a parameter space, wherein the parameter space is defined by a set of material parameters describing materials; using a quantum computer to numerically solve an electronic Schrödinger equation for a quantum system representing the selected material; using the solution to the electronic Schrödinger equation to obtain the specific property of the selected material; adding an entry to the training dataset, the entry indicating the selected material and a label, the label indicating the obtained specific property.