230 results about "Quantum gate" patented technology

The invention relates to the technical field of wireless communication, and discloses a wireless communication adaptive method and system based on a data transmission state, and the method comprises the steps: obtaining multi-source data, carrying out the preprocessing of the multi-source data, obtaining a CSI compression matrix, predicting the channel coherence time, dynamically adjusting the CSI sampling interval, and defining a load-channel coupling factor; obtaining cross-layer data based on the CSI compression matrix, performing fusion through a rotation matrix to obtain a fusion matrix, and extracting a physical layer fusion feature and an application layer fusion feature to calculate a multi-target state score; establishing a 5G power compensation mechanism based on cross-layer data, calculating a four-dimensional influence tensor, performing tensor decomposition and optimal action selection, and decomposing T into a core tensor and a factor matrix; selecting an optimal parameter combination through modular product calculation; based on cross-layer data, a quantum entanglement feedback mechanism is introduced, data is fed back, entanglement state association cross-layer indexes are designed, a quantum gate is adjusted through entanglement state design, and a model is updated in real time in combination with incremental learning.

The invention discloses a method for effectively simulating general quantum computing based on a classical circuit network, and relates to the technical field of quantum computing simulation, and the method comprises the following specific steps: converting data into a voltage signal through input voltage coding, constructing a single-bit gate and a two-bit gate by using an operational amplifier and an analog multiplier, and constructing a single-bit gate and a two-bit gate; according to the invention, the general quantum computation is simulated by a classical circuit network, an n-bit unitary matrix is decomposed and reconstructed by means of input voltage coding quantum state and voucher / two-bit gate modular design, and the high-efficiency simulation of general quantum computation is realized. Quantum gate linear transformation is reproduced, quantum calculation universality is achieved, voltage signals and data are converted through a reflection formula, signal distortion is avoided, multi-level gate circuit cascading is supported, and a flexible and stable platform is provided for quantum algorithm verification and the like.

The invention relates to the technical field of power system energy storage optimization, and discloses a terminal micro-grid energy storage optimization configuration method and system and a computer readable storage medium. Comprising the steps of generating load demand probability distribution and a new energy output confidence interval through deep learning and Bayesian probability modeling based on historical load and new energy monitoring data, extracting boundary parameters and mapping the boundary parameters into a quantum state initial solution set, and generating a quantum coding instruction set; a quantum algorithm population is initialized, a non-dominated solution set sequence is generated through quantum gate evolution operation, and a Pareto leading edge output optimization configuration scheme is screened; verifying feasibility in combination with local voltage data, and generating an executable control instruction set after fine tuning of capacity-position weight; and driving the energy storage unit to execute charging and discharging operation, collecting operation data, updating model parameters, finally separating probability weights and quantum deviations, adjusting a Bayesian model and resetting quantum gate parameters to generate a calibration instruction set. According to the invention, the energy storage configuration efficiency and precision can be obviously improved.

A system and method for inducing spin locking onto superconducting qubits, via a control drive, during performance of a quantum gate between the superconducting qubits is described. Spin locking may prolong the coherence times of the superconducting qubits involved in the gate, therefore reducing the risk that a fault occurs due to interference by noise in the environment. In order to induce spin locking, pulses may be directed at the superconducting qubits for the duration of the gate. The pulses may be determined and optimized by optimal coherence control methods and applied using a control drive. The pulse profiles may be determined in a manner that is specific to the given gate, to the superconducting qubits involved in the gate, and to the quantum hardware upon which the superconducting qubits and the gate are implemented.

A method of performing an encoded gate on a logical qubit, wherein the encoded gate includes the port portion and an ancillary portion, and wherein a lower surface of the port portion is coupled to an upper surface of the ancillary portion, includes performing a first plurality of stabilizer measurement on the port portion, performing both single qubit and dual qubit measurements on a plurality regions of the ancillary portion to generate topological features such as a twists, domain walls, and defects within a bulk region of the encoded S gate.

The invention discloses a quantum circuit calculation method. The method comprises the steps that an original quantum circuit is decomposed, a target quantum circuit is generated, and the target quantum circuit only comprises a single-bit gate and a double-bit gate. Then, based on the quantum gate dependency relationship of the target quantum circuit, splitting the target quantum circuit to generate a first sub-circuit and a second sub-circuit; then, based on the quantum simulation machine, the first sub-line is executed, and a first density matrix is determined. Then, based on the quantum processor, the second sub-line is executed, and a second density matrix is determined. And finally, according to the first density matrix and the second density matrix, determining a target execution result corresponding to the original quantum circuit. Thus, through decomposition processing and splitting processing, the circuit structure of the original quantum circuit is simplified, and high resource consumption of a traditional full-circuit single processing mode is avoided.

The invention relates to the technical field of quantum reinforcement learning, in particular to a reinforcement learning method and system for quantum gate regulation, and the method sequentially comprises the steps: carrying out the normalization of an offline sample, carrying out the principal component analysis, and then preparing a prior quantum state; performing wavelet scattering and persistent coherence on the quantum pulses to extract topological features, and mapping the topological features into a non-Abell geometric gate rotation angle to generate an action probability; constructing a sparse high-dimensional vector, selecting a target super vector through Grover amplification, writing the target super vector into the silicon carbide memristor array, and retrieving an action vector according to a conduction function determined by the topological feature vector; the motion vector drives the Heisenberg cellular automaton to predict the environment, the local error triggers the fine tuning of the rotation angle and the conduction value, and the global distance triggers the topology recompilation and the quantum natural gradient. According to the method, decision making within 250 microseconds, low-energy-consumption retrieval and steady-state self-healing are achieved.

Methods, systems and apparatus for quantum error correction. A layered representation of error propagation through quantum error detection circuits is constructed. The layered representation includes multiple line circuit layers that each represent a probability of local detection events in a quantum computing system associated with potential error processes in an execution of a quantum algorithm. To construct the layered representation, potential detection events associated with each potential error process occurring at quantum gates in the quantum circuit are determined. Lines are associated with each potential error process, the lines each connecting a potential detection event associated with the potential error process to another potential detection event associated with the same potential error process or a boundary of the quantum circuit. Similar lines are merged and used to construct unique line circuit layers. The layered representation is transmitted to the quantum computing system prior to execution of the quantum algorithm.

The invention relates to the field of medical image classification, and provides a medical image classification method and device based on a coherent Isin machine, equipment and a medium, and the method comprises the steps: constructing an SVM model for medical image binary classification; constructing a QUBO model of the SVM model; solving the QUBO model by using a coherent Isin machine to obtain optimal parameters of the SVM model; and determining the type of the medical image to be classified by using the SVM model adopting the optimal parameters. According to the method and the device, the SVM of the medical image binary classification problem is modeled into the QUBO problem in the quantum solvable form, and the SVM problem in the QUBO form is processed and converted by using the coherent Isin machine, so that the optimization process is accelerated by using quantum hardware, the medical image binary classification problem can be effectively and quickly solved, and in addition, the method and the device can be applied to the field of medical image processing. And the SVM model is solved by using coherent Isin machine evolution, so that accurate quantum gate operation is avoided, the control difficulty of the quantum system is reduced, and the realizability is higher.

The disclosure relates to machine learning, more particular to training a machine learning model comprising a classical sub-model and a quantum sub-model. A classical processor, receives, from a classical device, an intermediate classical output from a classical sub-model of the machine learning model and configures quantum gates of a quantum circuit based on the intermediate classical output. A quantum processor executes the quantum circuit using the quantum gates to determine a quantum circuit output, the quantum circuit being configured to represent a quantum sub-model of the machine learning model. The classical processor adapts the quantum circuit output to determine a further classical output; updates the quantum sub-model based on minimising a loss involving the further classical output; and transmits a loss propagation value to the classical device, to cause the classical device to update the classical sub-model based on the loss propagation value, thereby training the machine learning model.

The invention discloses an anti-quantum computing attack data encryption method based on a deep quantum neural network, which is applied to the technical field of data processing, and comprises the following steps: obtaining quantum associated data and security constraint parameters in the fields of government affairs and finance, and completing classical data quantum bit coding, high-dimensional feature extraction and noise filtering through quantization preprocessing; generating high-dimensional quantum state data adaptive to the quantum neural network; a deep quantum neural network encryption architecture is constructed, a dynamic key pool is generated based on quantum superposition-entanglement characteristics, and a layered encryption scheme is formed in combination with a weight sub-update mechanism; encryption parameters are optimized through a quantum neural network reinforcement learning framework, robustness is improved, and a self-learning optimization strategy is generated; an evolution trajectory is monitored by means of a quantum neural network to construct an encryption execution closed loop, and finally comprehensive evaluation information containing indexes such as a training convergence rate and key efficiency is generated through a quantum gate inverse operation learning model and a Hash verification neural network, so that the quantum attack resistance is enhanced.

The invention provides a quantum circuit simulation calculation method. The method comprises the following steps: acquiring an ideal quantum circuit; a first noise quantum circuit is obtained according to a noise model and the ideal quantum circuit, the first noise quantum circuit comprises a first quantum gate sequence, the first quantum gate sequence comprises R first diagonal gates acting on a first quantum bit and M first Follici X gates acting on the first quantum bit, the first diagonal gates act on the multiple quantum bits, and the M first Follici X gates act on the multiple quantum bits; m is greater than 1; the first noise quantum circuit is transformed to obtain a fused quantum circuit, the first quantum gate sequence is transformed into a second quantum gate sequence in the fused quantum circuit, and the second quantum gate sequence comprises R second diagonal gates acting on the first quantum bit and F second Fouli X gates acting on the first quantum bit, the second diagonal gate acts on a plurality of quantum bits, and F is a remainder obtained by dividing M by 2; and running the fusion quantum circuit to obtain quantum data output by the fusion quantum circuit.

The invention discloses a logistics network feature extraction method based on a quantum graph convolutional neural network, and the method comprises the steps: building a quantum graph convolutional neural network, and training the quantum graph convolutional neural network; and carrying out logistics network feature extraction by using the trained quantum graph convolutional neural network. Dynamic adaptation (quantum dynamic feature coding including feature coding module, CNOT gate adjustment, classical feedback and loss function design) is introduced, quantum gate parameters are updated in real time through a quantum gradient descent method, and the quantum state is adjusted in combination with a logistics optimization target (such as minimum transportation time), so that the quantum gate parameters are updated in real time. On-line learning and real-time updating of logistics network features are realized through quantum-classical hybrid optimization circulation (the quantum part extracts features and the classical part feeds back updated parameters), and robustness of the model in a dynamic scene is ensured.

A computer-implemented method for improving the computational efficiency and performance of large language models (LLMs) within at least one hybrid classical-quantum computation system with involving quantum circuits and tensor networks; and the classical computing device applies disentanglers to decompose the weight matrices of self-attention layers and multilayer perceptron (MLP) layers of a pre-selected large language model (LLM) into an unitary quantum circuits and a non-unitary tensor network for allowing transformation into quantum circuits into quantum gates; and sends this information to at least one quantum computing device within a quantum circuits; and processes non-unitary tensor network with at least one classical computing device and combines both results to reconstruct the large language model; and enlarges the bond dimension of the non-unitary tensor network and the number of layers of the quantum circuits; and optimizes the new parameters variationally in order to improve the accuracy beyond that of the original LLM.

This invention provides a real-time radio signal identification and classification system and method based on artificial intelligence, relating to the field of radio signal identification technology. The system includes: a signal preprocessing module for filtering, denoising, and normalizing received radio signals to generate a standardized signal dataset; a Hilbert space mapping module for mapping each signal sample in the standardized signal dataset to a complex vector in Hilbert space; a quantum gate operation module for performing quantum state evolution on the complex vector using single-qubit and two-qubit gates to generate superposition and entangled states containing signal characteristics; an amplitude compression module for compressing the signal dataset into a quantum state of n qubits using an exponential compression strategy; and an artificial intelligence classification module for real-time classification of signals using deep neural networks or support vector machines based on quantum state measurement results, outputting classification labels.

The application discloses a kind of based on ensemble rare earth ions double quantum bit controlled gate construction method, it is related to quantum control technical field, it includes to double quantum bit frequency site selection, and respectively as control bit, target bit;Utilize the blocking effect generated by the dipole-dipole interaction between double quantum bits to construct controlled gate, including: to control bit apply light pulse driving control bit is from ground state transition to excited state;To target bit apply single quantum gate to drive its evolution, and apply compensation pulse;To control bit apply light pulse driving control bit from excited state de-excitation to ground state.The application utilizes the interaction of the light pulse and quantum system medium that can be optimized to produce arbitrary geometric quantum logic gate on target quantum bit, and simultaneously by using the blocking effect caused by dipole-dipole interaction, the evolution of target bit quantum bit can be constrained by control bit.

A method for performing a ZZ-rotation quantum gate acting on two qubits having an XX coupling and corresponding resonance frequencies. The method includes applying twice the following pulses: rotation pulses, and echo pulses. In each application of pulses, to each of the two qubits, a corresponding rotation pulse is applied. The rotation pulse has a corresponding phase, has a corresponding amplitude, and has a driving frequency ω{circumflex over ( )}((i)) distinct from each of the resonance frequencies, so that each of the two qubits is having a corresponding detuning Δ_0,1{circumflex over ( )}(i)). The echo pulse is commuting with a Pauli-ZZ operator associated with the two qubits. The echo pulse is applied so as to control a magnitude of any one of: XX+θ(Δ_0{circumflex over ( )}((i)) Δ_1{circumflex over ( )}((i)))·YY rotation, and XY-θ(Δ_0{circumflex over ( )}((i)) Δ_1{circumflex over ( )}((i)))·YX rotation. In each application of pulses, the echo pulse is applied after the rotation pulse.

A qubit allocation program of an embodiment causes a computer to execute a process of converting, a process of creating a second graph, a process of specifying, and a process of creating circuit information. The process of converting converts a quantum circuit serving as an operation target into a first graph indicating a connection relation of each gate included in the quantum circuit. The process of creating a second graph creates a second graph from which a gate other than a two-quantum gate included in the first graph is removed, based on the first graph. The process of specifying specifies a graph isomorphic to the second graph from a third graph created based on each of a plurality of the quantum circuits. The process of creating circuit information creates circuit information corresponding to the quantum circuit serving as the operation target, to which a qubit is allocated based on the quantum circuits corresponding to the specified third graph.

Disclosed herein is a new system and method for loading quantum processor programs. Pulse processors are programmed, in real-time, according to a low-level instruction set to produce microwave pulses that manipulate the states in a quantum processor. The nature of qubits in the quantum processor causes quantum hardware characteristics to drift over time. These qubits undergo small physical changes that may damage the accuracy of the quantum gates, typically due to variation of temperature, or energy in the quantum hardware. This new system and method for loading quantum processor programs enables qubit calibration and the adjustment of the quantum hardware in real-time according to immediate feedback from one program to another.

Systems and methods involving quantum machines, hybrid quantum machines, aspects of quantum information technology and / or other features are disclosed. In one exemplary implementation, a system is provided comprising a quantum register that stores quantum information using qubits, wherein the qubits are configured to store the quantum information using particles or objects arranged in a lattice of quantum gates, a clock that provides a clock cycle to the quantum register, and a qubit-tie computing component coupled to the quantum register, wherein the qubit-tie computing component is configured to shift the quantum information between the qubits, wherein the system stores the qubits in different states using physical qualities, which may define qubits that are configured to be entangled and superposed at a same time. Further, the quantum register may comprise an entanglement component, and / or the qubit-tie computing component may comprise a superposition component.

A device includes a grouping of N qubits, where N is equal to two or more, and a coherent light source configured to, given selected values for a set of parameters of at least a first and a second laser pulse, the parameters selected from a relative phase shift, a laser frequency, a laser intensity, and a pulse duration: apply at least the first and second laser pulses to all qubits within the grouping of N qubits, thereby coupling a non-interacting quantum state |1 to an interacting excited state |r, such that each qubit that begins in quantum state |1 returns to the state |1 upon completion of the at least first and second laser pulses, and such that qubits in the grouping are mutually blockaded.

Provided herein are methods for generating, from a quantum algorithm, a quantum circuit that is error robust. The methods determine a characteristic of a quantum hardware that is used to implement the quantum algorithm and informs the deterministic dynamic error suppression routine to be implemented. The methods also consider the compiled quantum circuit because that provides the information about the context of the operations performed on the qubits, which is an important factor in the fidelity of the quantum gates and ultimately the success of the algorithm. The methods then use the characteristic and the context to apply deterministic error correction.

A method may include obtaining a configuration of a quantum circuit comprising n qubits and k quantum gates. The k quantum gates include at least a single-qubit gate or a two-qubit control gate. The method may include constructing a neural network representing the quantum circuit, wherein the neural network includes k+1 layers that include k pairs of adjacent layers, with each pair of the adjacent layers corresponding to one of the k quantum gates. The method may include connecting one or more nodes in each pair of the adjacent layers based on a representation of a corresponding quantum gate of the k quantum gates. The method may include training the neural network using machine learning techniques to obtain an output. The method may include applying the output to the quantum circuit.

A computer-implemented method for training a machine learning model for approximating a labeling function comprising a variational quantum circuit, said method comprising establishing the variational quantum circuit, the variational quantum circuit comprising a plurality of variational quantum gates, and a plurality of encoding gates; executing the variational quantum circuit for a plurality of sample inputs; determining a candidate output for each sample input; determining a quality measure of the candidate outputs for the plurality of sample inputs in view of the labeling function to be approximated by the machine learning model; determining an entropy measure of the candidate outputs determined for each of the sample inputs; and updating the variational parameters based on an update function, the update function including a quality-based loss term based on the quality measure and an entropy-based loss term penalizing excess information on the input data encoded in the candidate output through the entropy measure.

Embodiments of the present application provide a method for determining quantum interference and related equipment. The method comprises: inputting a control signal on a first quantum bit, measuring the second quantum bit and the first quantum bit respectively according to the measurement operator of the second quantum bit and the measurement operator of the first quantum bit, and obtaining a set of measurement expectation values; and determining interference information of the signal acting on the first quantum bit on the second quantum bit according to a Hamiltonian model of a quantum chip and the set of measurement expectation values, the interference information being related to time. The method can determine the interference information of the signal acting on the first quantum bit on the second quantum bit, i.e., the dynamic process of the interference, according to the Hamiltonian of the first quantum bit and the second quantum bit and the measurement expectation values of the first quantum bit and the second quantum bit, thereby providing a reference for how to correct the interference signal, reducing the influence of the interference on quantum gate operation, and improving the accuracy of quantum gate operation.

To solve the above-mentioned problem, an actuator is provided. The actuator includes a control unit having a control quantity correction unit that takes a signal based on a target state indicated by a command and a measured state as input, and corrects a control quantity for driving a first member, computed by a quantum gate operation. A second member operates in response to the first member being driven based on the corrected control quantity.

A recording medium storing a program for causing a computer to execute: acquiring a first quantum circuit expressing an action of a time evolution operator regarding a target problem, a second quantum circuit having parameters and a smaller number of quantum gates than the first quantum circuit, and a third quantum circuit defining one or more quantum states being a part of quantum states regarding the target problem, in which each of the first, second, and third quantum circuits has a first size; creating first, second, and third local circuits each having a second size, by respectively reducing sizes of the first, second, and third quantum circuits to the second size smaller than the first size; calculating solutions of the parameters, so as to minimize a value of a cost function for each quantum state; and setting a quantum circuit expressing the action of the time evolution operator.

The invention relates to the technical field of quantum computing, and provides a quantum state preparation method and system based on any real vector. Abnormal value detection is carried out on an input original vector, and abnormal value calibration processing is carried out on an identified abnormal value; and expanding the vector length to an integer power of 2 through dynamic zero padding and an internal sorting strategy, and carrying out optimized sorting to obtain a final processed vector. And the quantum construction system calculates a required quantum revolving door angle by adopting a layered amplitude coding mode from top to bottom based on the vector, optimizes a control bit sequence through heuristic search, determines a quantum gate execution sequence, constructs a quantum circuit according to the sequence, constructs the optimized quantum circuit according to the sequence, and operates the circuit to obtain a quantum state. Through a multiple optimization technology, the coding precision of quantum state preparation is remarkably improved, the complexity of a quantum circuit is reduced, hardware characteristics are better adapted, and the result extraction efficiency is improved.

The application discloses a quantum neural network hybrid system based on a memristor Hopfield and a training method thereof, and aims to solve the problems of low storage precision of complex quantum weights, poor quantum-classical collaboration and high energy consumption of the quantum neural network. The system comprises a quantum computing layer, a classical interface layer and a memristor Hopfield layer, and constitutes a closed loop through error feedback. The quantum computing layer extracts quantum entanglement features by using a quantum bit and a quantum convolution layer, and outputs complex quantum weights; the classical interface layer converts the complex quantum weights into memristor conductance values through polar coordinate mapping; and the memristor Hopfield core layer adopts a double-end complex memristor array to complete storage and associative memory operation. The training method optimizes quantum gate parameters and memristor conductance values through closed loop feedback collaboration. The application can reduce precision loss, realize stable and low-energy consumption storage, and is suitable for quantum key storage, medical image diagnosis and other scenes.

Disclosed herein is a new system and method for loading quantum processor programs. Pulse processors are programmed, in real-time, according to a low-level instruction set to produce microwave pulses that manipulate the states in a quantum processor. The nature of qubits in the quantum processor causes quantum hardware characteristics to drift over time. These qubits undergo small physical changes that may damage the accuracy of the quantum gates, typically due to variation of temperature, or energy in the quantum hardware. This new system and method for loading quantum processor programs enables qubit calibration and the adjustment of the quantum hardware in real-time according to immediate feedback from one program to another.