335 results about "Quantum gate" patented technology

The invention discloses an AI-based signaling network vulnerability attack simulation and prevention system, which comprises a signaling sensing layer, which is deployed in a core network element to carry out hardware-level decoding of an SS7 / Diameter / SIP / 5G-NR protocol, dynamically extracts protocol field-level metadata through a YARA rule base and generates a standardized signaling log; the threat modeling layer is used for receiving a signaling log output by the signaling sensing layer, generating mixed traffic after injecting a simulation attack, outputting the mixed traffic to the anomaly detection layer, constructing a multi-dimensional feature encoder by using a parameterized quantum gate based on a quantum generative adversarial network and a GFlowNet stream generation engine, generating a compliance attack vector in combination with the constraint of a 3GPP protocol state machine, and outputting the compliance attack vector to the anomaly detection layer; meanwhile, attack trajectory diversity sampling is completed through a Diameter protocol AVP nested state tree and a two-factor award function; the anomaly detection layer is used for receiving the mixed flow of the threat modeling layer and outputting a threat evaluation result to the response processing layer; and the response processing layer is used for receiving the threat assessment result of the anomaly detection layer and issuing a defense instruction to the signaling sensing layer.

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.

A method of time-dependent quantum Hamiltonian simulation that is capable of efficiently achieving a target error is described. The time evolution of a time-dependent Hamiltonian describing a physical system is modeled using a Magnus operator that has one or more nested commutators and integrals. The Magnus operator is approximated with a commutator-free operator up to an order n. An error between the commutator-free operator and the Magnus operator as result of the approximation is estimated based at least in part on a simulation step size h. The commutator-free operators may be simulated on a quantum computer via one or more quantum gates for a total simulation time in temporal increments of h, where the step size h has a value such that a simulation error of the simulation is less than or equal to a target error.

The invention discloses a path planning method, device and equipment and a storage medium, and the method comprises the steps: carrying out the quantum state coding of a path state in GIS spatial data, and obtaining a quantum superposition state and an entanglement state of the path state based on a quantum gate; the path planning problem is converted into a quantum Hamiltonian minimization problem, and the Hamiltonian of the annealing process is constructed based on the quantum tunneling effect; an initial quantum superposition state of a path state is constructed for the quantum Hamiltonian, and a target path is searched based on a Grover search algorithm; and coding the dynamic constraint condition into a quantum constraint Hamiltonian, and solving the minimum value of the total sub-Hamiltonian. According to the technical scheme provided by the embodiment of the invention, the path planning task can be efficiently completed.

Techniques facilitating error mitigation for quantum computing devices. In one example, a system can comprise a process that executes computer executable components stored in memory. The computer executable components comprise: an approximation component; a budget component; and an optimization component. The approximation component can generate an approximate decomposition of a quantum gate. The budget component can set a budget value (Cbudget) for a C-factor that is a metric for increase in variance of quasi-probability sampling. The optimization component can determine an optimal decomposition for the quantum gate as a function of Cbudget.

Systems and methods for performing iFRB benchmarking are disclosed. Exemplary systems can include a quantum component and a classical component. The classical component can include at least one processor and at least one non-transitory computer-readable medium. The non-transitory computer-readable medium can contain instructions that, when executed by the at least one processor, cause the classical component to perform operations. The operations can include generating a gate sequence including test gates interleaved with gate subsequences equivalent to Haar random two-qubit gates. Each gate subsequence can include at least one SQiSW gate. The operations can further include generating a recovery gate based on the gate sequence. The operations can further include providing commands applying the gate sequence and the recovery gate to the quantum component and obtaining an output from the quantum component.

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.

An information processing apparatus sets, for a rotation gate that is a quantum gate executed on an encoded logical qubit, a target rotation angle set in the rotation gate to a designated rotation angle, generates a first logical qubit having a predetermined ancilla state based on the designated rotation angle, executes a stochastic rotation operation that results in a forward rotation with the designated rotation angle or in an inverse rotation whose sign is opposite to a sign of the designated rotation angle by using, as input, the first logical qubit and a second logical qubit on which the rotation gate is executed, and repeats a process for generating the first logical qubit and a process for executing the rotation operation while updating the designated rotation angle based on the target rotation angle until the rotation operation results in the forward rotation.

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.

A method, system, and product for performance analysis of quantum programs. A quantum program comprises plurality of code artifacts and is compilable into a quantum circuit. A representation of the quantum circuit that implements the quantum program is obtained. The quantum circuit manipulates a plurality of qubits over a plurality of cycles using a plurality of quantum gates. The representation of the quantum circuit includes circuit components. A performance measurement of a code artifact of the quantum program is automatically computed based on one or more circuit components that are mapped to the code artifact by a component to code mapping. The component to code mapping maps circuit components of the representation to the quantum circuit to respective code artifacts of the quantum program.

A quantum circuit design support apparatus determines the number of control qubits for each of one or more third quantum gates corresponding respectively to one or more third qubits that have a predetermined value before the gate operation of a first quantum gate that flips the value of the target qubit when all control qubits are 1, and the number of control qubits for a second quantum gate so that a predetermined relationship is satisfied. The quantum circuit design support apparatus generates a second quantum circuit including the third quantum gates, each using first qubits equal in number to the determined number of control qubits as the control qubits and a third qubit as the target qubit, and the second quantum gate using a first qubit not used in the third quantum gates and the third qubits as the control qubits and the second qubit as the target qubit.

The invention discloses a power distribution network fault data preprocessing method and system based on multi-source information fusion, and relates to the technical field of power systems, and the method comprises the steps: constructing a dynamic topology manifold based on the physical connection relation of power distribution network equipment and multi-source data; manifold deformation caused by line switching or sudden load change is responded, and abnormal data are recognized in combination with the manifold curvature and the equipment connection path distance; encoding the abnormal data, the meteorological data and the equipment state data into quantum states, and generating entanglement feature vectors through quantum gate operation; performing chaos sequence modulation on the basic features to generate modulation features; performing quantum fusion transformation on the modulation feature and the entanglement feature vector to generate an enhanced feature; calculating topological space correlation, chaos behavior similarity and quantum correlation based on the enhanced features, and constructing a multi-dimensional fusion weight; and performing weighted fusion on the enhanced features according to the multi-dimensional fusion weight, and outputting a preprocessed fault feature vector.

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.

An improved non-adjacent bit quantum gate efficient analog calculation method comprises the steps that S1, dimension information of each tensor in a tensor network is obtained, the dimension information comprises the physical dimension and the auxiliary dimension of the current quantum state tensor, and the auxiliary dimension of the quantum state tensor after the quantum gate is acted is judged for subsequent contraction judgment and resource evaluation; s2, selecting a corresponding strategy for execution based on the target bit spacing and the tensor dimension; s3, judging whether the dimension of the contracted intermediate tensor exceeds a preset resource limit or not under the condition that the overall contraction mode is adopted; if the target bit exceeds the limit, inserting an SWAP gate through an overall contraction and decomposition strategy to rearrange the target bit to the maximum distance under the memory limit, and circulating to S3 for judgment; and if the limit is not exceeded, executing normally. Experiments show that in a highly entangled quantum circuit, the method of the invention can realize about 50% of simulation time optimization at most, and can limit the maximum intermediate tensor scale at the same time.

A method of determining a noise characterization of a quantum processing unit configurable to execute at least a part of a quantum circuit comprising at least two consecutive layers of quantum gates, wherein the noise characterization is based on a predetermined number of parameters, the method comprising the steps of: performing a first process based on a single layer of the part of the quantum circuit for obtaining a first set of fidelities and / or products of fidelities, performing a second process based on at least two consecutive layers of the part of the quantum circuit for obtaining a second set of fidelities and / or products of fidelities, and determining the predetermined number of parameters based on at least the first set and the second set.

The invention discloses a quantum computing gate circuit expression and compression method and a medium, and relates to the technical field of quantum computing, and the method comprises the steps: setting a conversion expression character between a user side and a quantum computing cloud platform, or setting the conversion expression character between the quantum computing cloud platform and a terminal quantum computer for unifying quantum languages; the conversion expression character is divided into three segments which are an operation code, a bit code and a parameter code in sequence, the operation code refers to quantum gate operation, the bit code refers to a quantum bit number, and the parameter code refers to a floating-point number related to the operation code; the core of the method is that the file volume is compressed and the quantum language is unified, so that the problem of transmission efficiency of existing codes among different terminals is solved.

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.

1. An apparatus comprising a two-dimensional array of quantum gates, wherein a controller is configured to control the two-dimensional array of quantum gates, wherein the controller is configured to control the apparatus to operate as a single machine state to perform a gate operation sequence for all of the quantum gates, the gate operation sequence being selected from a plurality of gate operation sequences, each of the gate operation sequences having a different maximum duration.

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.

To shorten the computation time for an expected value of a ground state energy of a molecule.SOLUTION: An information processing device 10 creates multiple quantum bit pairs, each of which is formed by combining a first quantum bit and a second quantum bit. The first quantum bit corresponds to a first orbital in which an electron is present in the initial configuration. The second quantum bit corresponds to a second orbital in which an electron is not present in the initial configuration. The information processing device 10 generates a quantum circuit 3 which applies two-qubit gates 4a to 4j to at least a part of the multiple quantum bit pairs. The two-qubit gates 4a to 4j are quantum gates which generate a superposition state according to a parameter value between a first state in which the states of the first and second quantum bits are not swapped and a second state in which the states are swapped. An expected value of a ground state energy of a molecule is acquired by causing a quantum computer 1 to repeatedly execute the quantum circuit 3.SELECTED DRAWING: Figure 1

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.