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电网灾害拓扑脆弱性边界值评估方法、装置、设备及介质

Resumen de: CN122571209A

本申请涉及电网技术领域，公开了一种电网灾害拓扑脆弱性边界值评估方法、装置、设备及介质；其方法包括：获取电网拓扑数据与灾害场景下的故障概率分布数据，构建以电网拓扑数据为骨架、以故障概率分布数据为权重的属性图数据；将属性图数据输入至预先构建并训练好的电网脆弱性边界评估模型中，得到脆弱性边界值评估结果；其中，电网脆弱性边界评估模型包括图神经网络层、量子神经网络层以及融合分析层。本申请能够满足大规模电网在灾害场景下对脆弱性实时评估与精准预警的应用需求。

Contrôle de la sortie d’un dispositif spintronique à bit probabiliste

Resumen de: FR3172221A1

L’invention a pour objet un procédé de fabrication d’un dispositif spintronique (D1) comprenant : une jonction tunnel magnétique (MTJ) ; un transistor de polarisation (Tpol) monté en série avec la jonction tunnel magnétique (MTJ) ;un circuit de détection (DET) ayant une entrée (edet) connectée à un premier nœud de détection (NC1) et une sortie (sdet) pour générer un signal de détection (Vout) ; le circuit de détection comprenant au moins un premier inverseur (INV1) comprenant un premier transistor NMOS (TINV1,N) et un second transistor PMOS (TINV1,P) ayant chacun :une grille avant (G1,N ,G1,P) ; une grille arrière (G2,N ,G2,P) formée par une couche isolante (BOX) enterrée dans un substrat semi-conducteur (2) ;un circuit de contrôle (CONT) configuré pour appliquer une tension de commande (Vcmd) non-nulle sur la grille arrière (G2,N ,G2,P) d’au moins l’un parmi le premier ou le second transistor. Figure pour l’abrégé : Fig. 2a

MACHINE-BASED LLM OUTPUT SUPERVISION

Resumen de: US20260236750A1

0000 Apparatus and methods for high-dimension validation of large language model (“LLM”) output. The apparatus and methods may leverage the power of Hybrid AI/ML and Quantum GANs to scrutinize LLM output from various angles. The apparatus and methods may discriminate between LLM-generated and verified facts. The methods may include analyzing the information provided by LLMs through different lenses, including metaphors, emotions, video, image analysis, cultural context, and simulations, utilizing Hybrid AI/ML models to identify patterns and relationships. This may enable a more accurate understanding of the data and help identify any inconsistencies or discrepancies in the output. The apparatus and methods may incorporate analysis to evaluate the implications of the information provided by LLMs and ensure that it aligns with standards and guidelines, utilizing Quantum GANs to generate alternative scenarios and assess the reliability of the data.

CONTROL APPARATUS AND CONTROL METHOD

Resumen de: US20260236818A1

A control apparatus includes a digital processing circuit and a digital-to-analog converter (DAC). The digital processing circuit generates a first control command group including a plurality of first control commands for controlling a plurality of first qubits, and a second control command group including a plurality of second control commands for controlling a plurality of second qubits, each of the second control commands having the same frequency as that of a corresponding one of the first control commands. In addition, the digital processing circuit performs frequency-multiplexing on third and fourth control command groups of different frequency bands by adding offsets to the first and second control command groups, to generate a digital multiplexed signal. The DAC performs digital-to-analog conversion on the digital multiplexed signal, to generate an analog multiplexed signal.

TWO-DIMENSIONAL CONVEYOR-MODE SPIN QUBIT SHUTTLING DEVICES

Resumen de: US20260236813A1

0000 Spin qubit shuttling devices and methods for their use are provided. The devices enable the electrons of an electron spin qubit to be translated in a two-dimensional (2D) plane with high spin fidelities. The 2D translational motion can be used to maneuver the electrons around low valley splitting regions in a semiconductor channel and/or to bring electrons in a qubit processor into close proximity to allow for spin coupling beyond nearest neighbor interactions. As such, the spin qubit shuttling devices have applications in quantum computing systems, including in quantum links and qubit registers.

ROUTING QUANTUM CIRCUITS USING MACHINE LEARNING

Resumen de: US20260236819A1

0000 A method, computer program product, and system for routing quantum circuits. A structure of a quantum circuit to route is encoded in an environment using a reinforcement learning agent. A noise of a built routed quantum circuit is encoded in a cost function, such as by measuring the noise in the layer(s) of gates of the built routed quantum circuit. The structure of a quantum circuit refers to the sequence of quantum gates applied to qubits. A cost function refers to a mathematical function that measures how well the predictions of the machine learning model align with the actual target values. Quantum circuit routing is then performed using a trained machine learning model based on the structure of the quantum circuit and minimizing the cost function, which reduces the gate count and noise since the structure facilitates the routing task and noise minimization as encoded in the cost function.

Verwendung verrauschter Upload-Gatter zur Regularisierung in Quanten-Reuploading-Schaltkreisen

Resumen de: DE102025104501A1

Verfahren zum Regularisieren der Verlustlandschaft eines Reuploading-Schaltkreises in einem Quantencomputer, gekennzeichnet durch folgende Merkmale:Bereitstellen von Eingabedaten;Codieren der Eingabedaten unter Verwendung von verrauschten Codiergattern in dem Quantencomputer, um verrauschte Eingabedaten zu erzeugen; und Anwenden der verrauschten Eingabedaten auf den Reuploading-Schaltkreis.

LOW-TEMPERATURE ELECTRONIC SYSTEM WITH SUPERLATTICE THERMAL MATERIALS

Resumen de: WO2026170024A1

A cooled electronic system includes an electronic device, a vacuum chamber, a cryogenic cooling system, and an electrical signal line. The vacuum chamber encloses the electronic device. The cryogenic cooling system cools the electronic device and includes a precooling system and cooling stages. A cooling stage supports the electronic device. The electrical signal line couples to the electronic device and includes a superlattice structure. The superlattice structure is disposed at one or more of the cooling stages, is in a thermal conduction path along the electrical signal line to thermally isolate the electronic device, and transmits signals to or from the electronic device.

SYSTEMS, APPARATUSES, AND METHODS FOR QUANTUM ARTIFICIAL INTELLIGENCE

Resumen de: WO2026167196A1

A classical computing entity of a hybrid quantum-classical computing system may generate one or more quantum circuits at least in part through operation of program code characterized by an artificial intelligence (AI) and/or machine learning architecture; provide the one or more quantum circuits (e.g., for receipt by a quantum computer); and receive measurement results generated by performance of at least one quantum circuit of the one or more quantum circuits by the quantum computer. The classical computing entity may utilize the measurement results and the program code characterized by an artificial intelligence (AI) and/or machine learning architecture to (a) update a model, (b) evaluate a loss function, (c) generate one or more updated quantum circuits for performance by the quantum computer, and/or (d) determine and/or provide a solution to a problem.

OPTICAL DEVICE, METHOD OF MANUFACTURING OPTICAL DEVICE, QUANTUM COMPUTER, AND METHOD OF CONTROLLING QUANTUM COMPUTER

Resumen de: WO2026167808A1

An optical device(100) includes a substrate(10), a cantilever(20) that extends in a first direction on the substrate(10), includes diamond having a color center(21), and has an end which is a fixed end and another end which is a free end, an optical waveguide(30) that includes a first portion and a second portion that interpose the color center(21) therebetween in a second direction intersecting the first direction, extend in the second direction and are away from the cantilever(20), the first portion andthe second portion including diamonds, and a pair of electrodes(40,41) provided so as to interpose a part of the cantilever(20) located closer to the another end than the color center(21) therebetween.

DEVICE AND METHOD FOR OPERATING A SEMICONDUCTOR SPIN QUBIT QUANTUM COMPUTER

Resumen de: US20260239896A1

A method of operating a quantum chip comprising the steps of calibrating voltage parameters pertaining to voltages to be applied to the plurality of gate electrodes, selecting a path along selected ones of a plurality of shuttling lanes between a position of a qubit and a selected manipulation zone, determining at least one shuttling voltage time course to be applied to an associated subset of the plurality of gate electrodes to move the qubit from the current position to the selected manipulation zone, moving the qubit along the selected ones of the plurality of shuttling lanes from the current position to the selected manipulation zone by applying the shuttling voltage time courses, determining, for the selected manipulation zone a manipulation voltage time course to be applied to the associated subsets of the plurality of gate electrodes to manipulate the qubit, and manipulating the qubit at the selected manipulation zone.

Systems and Methods for Integrated Circuits (IC) Design using Quantum Evolution Algorithms (QEAs) in Connection with Computer Aided Design (CAD) Software

Resumen de: US20260236658A1

0000 A computer implemented algorithm for designing complex electrical circuitry is disclosed which includes combining complex circuit design and quantum evolution optimization algorithm (QEA) to achieve efficiency, accuracy, and fast rate of convergence.

DEVICE FOR MANIPULATING QUBITS FOR A SEMICONDUCTOR SPIN QUBIT QUANTUM COMPUTER

Resumen de: US20260239895A1

A manipulation zone for a quantum processor comprising a plurality of gate electrodes arranged on a semiconductor heterostructure. The plurality of gate electrodes comprises a first finger gate assembly arranged at a first path in the semiconductor heterostructure and a second finger gate assembly arranged at a second path in the semiconductor heterostructure.The first path and the second path meet at an interface. The first finger gate assembly and the second finger gate assembly are configured to be supplied with at least one voltage V, to move along the first path formed and/or the second path at least one qubit, and/or to manipulate a current spin state of the at least one qubit located at the first path and/or the second path.

TUNING AND CONTROL OF CRYSTAL DEFECT EMISSIONS

Resumen de: AU2024223450A1

An optoelectronic device, comprises: a substrate; an optical waveguide on the substrate; a pair of Bragg reflectors formed in the waveguide to define a resonant cavity between the reflectors; a piezoelectric material on the substrate in proximity to the waveguide; and electrodes configured to apply an electric field to the piezoelectric material so as to tune a wavelength of light emitted from the cavity. A quantum computing device, comprises: a crystalline material comprising a crystal defect; one or more doped layers in the crystalline material over the defect in proximity to the defect; a surface carrier donor material on a surface of the crystalline material over the one or more doped layers in proximity to the defect; an electrode over the surface carrier donor material in proximity to the defect; and control circuitry, which is configured to apply a voltage to the electrode to control a state of the defect.

APPARATUS FOR PROVIDING CONTROL SIGNALS FOR CONTROLLING A QUANTUM COMPUTER

Resumen de: US20260236815A1

0000 The invention refers to an apparatus 720 for determining signals for generating a solution of a problem using a quantum computer. A providing unit 721 provides a problem description indicative of a first and second portion of the problem. A determination unit 722 determines a trial state representation based on a variational approach. The trial state representation comprises a first and second part representing the first and second portion, respectively. A translation unit 723 translates the trial state representation into an operation trial state description comprising a) second operations determined based on the second part and b) first operations determined based on the first part. A providing unit 724 provides signals for controlling the quantum computer such that the representation of the trial state representation is prepared. The signals referring to the first operations and signals referring to the second operations are performed by different parts of the quantum computer.

Preprocessing for Correlated Topological Quantum Error Correction

Resumen de: US20260236822A1

A computer-implemented method for correcting one or more errors in a quantum computing system can include obtaining, by a computing system comprising one or more computing devices, a plurality of weighted detection graphs, each of the plurality of weighted detection graphs being descriptive of a plurality of error detection measurements and having a plurality of weights, each of the weights respectively determined according to an error probability. The method can include generating, by the computing system, a plurality of reweighted detection graphs based at least in part on a correlation between physical errors in the quantum computing system. The method can include correcting, by the computing system, one or more errors in a quantum computing system based at least in part on a global decoding of the plurality of reweighted detection graphs.

VARIATIONAL ANALOG QUANTUM ORACLE LEARNING

Resumen de: US20260236821A1

A method includes configuring a quantum annealer based on a parameter of a Hamiltonian and performing annealing using the configured quantum annealer to obtain output samples, wherein each sample of the output samples indicates state values of elements of the quantum annealer for a set of indices of the output samples. The method also includes providing, to an oracle, the output samples to obtain a set of oracle outputs. The method also includes determining an expectation based on the set of oracle outputs and updating a parameter indexed by the set of indices based on the expectation and a learning rate parameter.

DETERMINATION OF CONDITION OR CHARACTERISTIC OF A TARGET

Resumen de: US20260235995A1

A device or system configured to: receive a set of data associated with a monitored target, the set of data having N features, where N is a natural number greater than one; input the N features of the received set of data into a trained neural network for determining a condition or characteristic of the target with a plurality of sets of historical data associated with the target, each set of the plurality of sets of historical data having N features, the neural network at least having N inputs and one or more outputs, the neural network having one or more hidden layers, each hidden layer being a tensor network in the form of a matrix product operator, MPO, with a respective plurality of tensors and having a respective predetermined activation function per hidden layer or per tensor in the MPO; and input the N features into the neural network, determining a condition or characteristic of the target by processing the one or more outputs. Also, a device or system configured to train such neural network.

周辺分布および同時分布に基づく量子生成ネットワークのトレーニング

Resumen de: US20260228591A1

In an embodiment, a parameterized quantum circuit is initialized on a quantum computer for a Quantum Neural Network (QNN) with trainable parameters to learn a first conditional distribution of a training dataset. A marginal distribution is loaded on a first set of qubits and the first joint distribution on a second set of qubits. The QNN is operated on the marginal distribution to predict the first conditional distribution. The QNN is operated on the marginal distribution and first conditional distribution to generate a second conditional distribution for the input data and second output data. A second joint distribution is generated from the second conditional distribution and loaded onto a third set of qubits. Joint quantum measurements are extracted from the second and first joint distributions to train the QNN to learn the first conditional distribution.

マルチデータ量子生成ネットワークの学習および推論

Resumen de: EP4787229A1

0001 In an embodiment, a parameterized quantum circuit is initialized on a quantum computer for a Quantum Neural Network (QNN) with an ansatz architecture. Input data, which includes a quantum representation of a multi-dataset and an initial state of the QNN, and labels, is received. The quantum representation of the multi-datasets on the QNN is loaded and a first dataset of the multi-dataset is labelled. A label-controlled circuit associated with label-controlled input qubits of the ansatz architecture for the QNN is determined, based on the labelled first dataset. A universal circuit associated with the ansatz architecture for a prediction circuit associated with the QNN is determined, based on labelled first dataset. The prediction circuit is determined based on the label-controlled circuit and the universal circuit. The prediction circuit is trained and configured to generate predictions associated with the loaded fractionally weighted data portfolios.

TUNABLE CAPACITOR FOR SUPERCONDUCTING QUBITS

Resumen de: US20260236817A1

An exemplary tunable capacitor in a quantum system includes a pair of qubits, and a capacitive coupling element coupled between the pair of qubits. The capacitive coupling element includes a plurality of gate terminals. The capacitive coupling element is configured to receive a respective gate voltage at each of the plurality of gate terminals and to adjust a capacitance of the capacitive coupling element in response to the respective gate voltage received at each of the plurality of gate terminals. The capacitance of the capacitive coupling element is configured to control a coupling strength between the pair of qubits.

２値最適化問題のための最適化汎関数を量子計算のためのコスト関数に変換するための技術

Resumen de: EP4787248A1

0001 The disclosure relates to method of converting an optimization functional for a binary optimization problem into a cost function for a quantum computation. The method comprises representing a first optimization variable among a plurality of binary optimization variables of the optimization functional as a first product of binary transformed variables, wherein the first product comprises a first plurality of factors, wherein each factor among the first plurality of factors corresponds to a subset of the plurality of optimization variables that includes the first optimization variable. The method further comprises converting each of the binary optimization variables or the binary transformed variables into a continuous variable; converting the optimization functional into the cost function, wherein the cost function comprises the transformed and continuous variables; and selecting a plurality of the subsets for the quantum computation.

QUANTUM READOUT AND CONTROL

Resumen de: US20260236814A1

0000 An FRC module comprises an integrated RF/FPGA-based qubit control system that integrates analog bandwidth DACs/ADCs with a System on Chip including processors and a large FPGA. RF channels can be controlled by a single module with a high channel density and the channels can be re-programmed into any feedback configuration. The embodiments support FPGA-level optimal filtering, state discrimination and feedback for qubit control; and a clock-synchronized state machine for time-critical quantum algorithms such as gate optimization.

High Current Column Grid Array Pillars

Resumen de: US20260240010A1

0000 A column grid array for low-voltage, high-current delivery uses pillars formed from bundles of parallel conductive filaments consolidated into metallic plugs at each end with an unconstrained compliant span between the plugs. The pillars are joined in a two-dimensional grid between opposing substrates to deliver aggregate current with controlled impedance while accommodating differential displacement without plastic deformation. Interleaving power and return pillars reduces loop inductance and transient droop. Optional sleeves or elastomer collars manage lateral stability; spare pillars and test features enable in-situ continuity verification and activation of redundancy. Methods include preparing filament bundles, consolidating ends by metallurgical bonding, joining plugs to substrate pads, and arranging pillars at grid pitch suitable for wafer-scale or module-scale power distribution.

MODE ENGINEERING FOR QUANTUM LOGIC SPECTROSCOPY

Nº publicación: US20260237537A1 13/08/2026

Solicitante:

QUANTINUUM LLC [US]
Quantinuum LLC

Resumen de: US20260237537A1

A controller of an atomic system controls voltage sources to cause first and second atomic objects of an object crystal to experience a coupling force. The object crystal is confined at a target location of a confinement apparatus that defines an axis thereat. The coupling force includes a component that is perpendicular to the axis. The controller causes the voltage sources to generate voltage signals that cause the object crystal to experience an axial confinement corresponding to a transition region for selected motional modes of the object crystal. When the atomic objects experience the coupling force and the object crystal experiences the axial confinement corresponding to the transition region, the selected motional modes form mixed motional modes. The controller causes manipulation sources to generate manipulation signals that are incident on the target location and that address the mixed motional modes to cause an entangling interaction between the atomic objects.