1483 results about "Quantum circuit" patented technology

The invention discloses a method and a system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cathode Spectroscopy) simulation according to an electronic structure of molecules of a target material; obtaining at least one effective excitation operator based on parameters in the coefficient of each excitation operator in UCCSD simulation and by combining all the excitation operators; constructing a quantum circuit according to all the effective excitation operators; determining energy level distribution of molecules of the target material based on the quantum circuit; and determining the reaction activity of the molecules of the target material according to the energy level distribution of the molecules of the target material. According to the method, in the process of obtaining the effective excitation operator, an ADAPT-VQE algorithm does not need to be executed, so that the analysis cost of the physical and chemical properties of the material can be reduced, and the analysis efficiency of the physical and chemical properties of the material can also be improved.

The invention provides a quantum circuit optimization method, device and equipment for a ZUC algorithm subcomponent, and the method comprises the steps: encoding a signal transmitted by communication into quantum bits, and inputting the quantum bits into a ZUC algorithm structure for quantum implementation; representing a first linear subcomponent in the ZUC algorithm structure as a matrix in a binary field; after a matrix in the binary field is expressed as a block matrix, a low-dimensional matrix M in the binary field is derived from the block matrix, and quantum implementation of the M is searched by using a search algorithm designed based on a matrix decomposition principle; and according to a quantum gate parallel rule, carrying out optimized multi-layer division on the quantum of the M again, obtaining the quantum of the M, carrying out optimized layering operation, and optimizing the quantum of the first linear subcomponent. According to the method provided by the invention, the quantum circuit of the subcomponent of the ZUC algorithm is optimized, so that the resource overhead of quantum implementation of the ZUC algorithm is saved.

The invention relates to the technical field of GIS (Geographic Information System) equipment denoising, in particular to a GIS local interference source denoising method, which comprises the following steps of: constructing a hybrid architecture of a quantum convolutional neural network and a quantum recurrent neural network, extracting features by using a variable component sub-circuit as a convolution kernel in the quantum convolutional neural network, processing time sequence data by using quantum bit entanglement in the quantum recurrent neural network, and extracting a local interference source in the quantum recurrent neural network; normalization, coding and enhancement are carried out on electrical, electromagnetic and other multi-source data, a quantum stochastic gradient descent algorithm is used for training, a multi-modal fusion network based on an attention mechanism is also constructed, features of all modals are extracted through an independent convolutional layer, then splicing and weighted fusion are carried out, and finally a quantum reinforcement learning environment is constructed. An intelligent agent strategy network and a reward function are designed based on a quantum neural network, parameters are adjusted according to quantum Q learning, quantum calculation, deep learning and a multi-modal fusion technology are integrated, the GIS local interference source denoising effect is effectively improved, and stable operation of equipment is guaranteed.

The invention discloses a quantum approximate optimization method and device based on easy Hamiltonian, and belongs to the technical field of quantum computation.The quantum approximate optimization method comprises the steps that a binary constraint optimization problem in intelligent decision making and resource configuration is converted into a linear constraint equation; preparing the initial state of the quantum circuit into an initial state corresponding to the special solution of the linear constraint equation; a variable component sub-circuit composed of a target Hamiltonian and an easy-to-drive Hamiltonian is designed, so that quantum state evolution is strictly limited in a feasible sub-space; a final quantum state is simulated and measured through Hamiltonian to obtain a candidate solution, and parameters are iteratively adjusted by using a classical optimization algorithm to approach an optimal solution. According to the method, convergence is accelerated through special solution initialization, the number of iterations is reduced, the evolutionary process is guaranteed to always meet constraint conditions through peaceability, and the solving efficiency and the success rate are remarkably improved.

The invention relates to the technical field of quantum computing, and discloses a quantum circuit mapping method and system based on deep reinforcement learning, according to the method, an original logic quantum circuit is analyzed and simplified into a ZX-graph, then the ZX-graph is converted into a quantum circuit dependency graph, the computing complexity is remarkably reduced, and the quantum circuit mapping efficiency is improved. A large-scale quantum circuit mapping task can be processed within reasonable time, a Markov decision process environment is constructed through a quantum circuit dependency graph and quantum chip parameters, a deep reinforcement learning agent is trained by using the Markov decision process environment, and an optimal mapping strategy optimization model is obtained. Through the optimal mapping strategy optimization model, the corresponding optimal quantum bit mapping scheme can be output to the current to-be-mapped logic line, so that the method can be adapted to quantum chips of various topological structures, and the generalization ability and adaptability of the mapping scheme are improved.

The invention relates to the technical field of quantum computing, and provides a polariton quantum computing simulation method and related device.The method comprises the steps that parameterized quantum circuits are generated based on micromodels used for describing polaritons for all to-be-computed excitation states respectively, and the parameterized quantum circuits are generated based on initial Hamiltonian of polaritons in a ground state; the target Hamiltonian amount of the polariton in the current excitation state is obtained, then the value of each parameter is adjusted at least once, and the target energy of the corresponding excitation state is obtained. In the primary adjustment process, parameter updating is carried out on the quantum circuit, a reference quantum state of the corresponding excitation state is obtained by utilizing the updated quantum circuit, reference energy of the corresponding excitation state is obtained based on the reference quantum state and in combination with the target Hamiltonian, and then when a set convergence condition is met, the target Hamiltonian is obtained. And taking the reference energy as target energy of the corresponding excited state. The polaritons are simulated through the quantum computer, and the simulation efficiency is improved.

A quantum computing service provides a quantum algorithm development kit that enables a customer to define a quantum task, a quantum algorithm, or a quantum circuit using an intermediate representation. The quantum computing service is then configured to automatically translate the quantum task, quantum algorithm, or quantum circuit into a specific representation specific to a particular quantum computing technology selected by the customer to be used to execute the customer's quantum task, quantum algorithm, or quantum circuit.

The invention provides a nonlinear data generation and processing method based on light quantum and a light quantum computer, and the method comprises the steps: obtaining a nonlinear function and attribute information of a nonlinear layer; according to the frequency spectrum number and the attribute information of the nonlinear function, constructing an initial light quantum circuit; measuring the initial light quantum circuit, and determining a target function corresponding to the initial light quantum circuit according to a measurement result; loss information of the target function is determined, whether the initial light quantum circuit is applied or not is determined according to the loss information, and if yes, the initial light quantum circuit serves as a target light quantum circuit; and performing operation on input data of the nonlinear layer based on the target light quantum circuit. According to the method, the low-energy-consumption characteristic of photon calculation, the nonlinear characteristic of light quantum calculation and the general programmable capability of electronic calculation can be fused, and high-energy-efficiency calculation can be carried out on input data of a nonlinear layer. In addition, the method also has the advantages that the complexity of a quantum circuit is smaller, and the participation of a nonlinear optical device is not needed.

The invention relates to the technical field of quantum compilation, and discloses an error suppression compilation optimization method for a quantum computer, which comprises the following steps of: capturing a physical quantum gate operation error rate and a hardware topological structure of a quantum processor for executing a mapping task, and constructing a hardware feature matrix; capturing gate interaction attributes of a to-be-compiled quantum logic circuit, and constructing a circuit characteristic matrix; according to the constructed hardware feature matrix and circuit feature matrix, establishing a mapping scheme representation model and a corresponding overhead function; solving the overhead function by using a genetic algorithm, and searching a mapping scheme which minimizes the overhead function value under the condition of meeting the resource constraint of the quantum processor; applying the optimized mapping scheme to the quantum logic circuit to be compiled, and compiling and optimizing the quantum logic circuit to be compiled; according to the method, the problems of poor adaptability, insufficient error rate optimization and the like of a quantum bit allocation scheme in the prior art are solved, and low-error and reliable quantum circuit mapping processing is realized.

One or more systems, devices, methods of use and / or methods of fabrication provided herein relate to a device that can facilitate qubit measurement with isolation imposed between a quantum processor and a respective qubit measurement circuit and / or which respective qubit measurement circuit can have a small footprint, such as within a respective cryogenic chamber of a quantum system. According to one embodiment, a device comprises an isolator circuit having a bandpass filter configuration coupled between a pair of ports and the bandpass filter configuration comprising two or more poles. Two or more shunt resonators can be realized as the two or more poles, wherein the two or more shunt resonators can comprise DC SQUIDs and can be coupled together with one or more admittance inverters. A non-reciprocal signal transmission can be generated between the two ports by RF pumping the DC SQUIDs.

A device comprises a superconducting quantum circuit comprising a coupler which is coupled to a first quantum bit and a second quantum bit. The coupler comprises a tunable coupler and a fixed coupler. The coupler is configured to operate in a first mode to suppress coupling between the first quantum bit and the second quantum bit, when the tunable coupler is tuned to have a first frequency which corresponds to a fixed frequency of the fixed coupler. The coupler is configured to operate in a second mode to enable coupling between the first quantum bit and the second quantum bit, when the tunable coupler is tuned to have a second frequency which is different from the fixed frequency of the fixed coupler.

Disclosed is a method for sharing information between a sender node and a receiver node in accordance with a quantum communication protocol. The method comprises: determining an attack configuration for access by a third party to the quantum channel, the attack configuration being defined by at least a quantum circuit system having specific parameters and an attack success bound, the quantum circuit system being configured to intercept a qubit on the quantum channel, determine the state of the intercepted qubit; using the quantum circuit system to measure first and second metrics by at least intercepting qubits on the quantum channel; determining whether the second metric fulfils an error tolerance bound and whether the first metric fulfills the attack success bound; aborting the communication protocol if the second metric fulfils the error tolerance bound and the first metric fulfills the attack success bound.

The present disclosure relates to the field of artificial intelligence (AI) and quantum technologies, and provides a quantum error correction hardware decoder and a chip. The quantum error correction hardware decoder includes: a memory storing instructions, a neural network processing unit, and a processor in communication with the memory and the neural network processing unit; and wherein, when the processor executes the instructions, the processor is configured to cause the quantum error correction decoder to: obtain error syndrome information for an error syndrome measured due to an error occurring in a quantum circuit, decode, by the neural network processing unit, the error syndrome information based on a neural network model to obtain an output result of the neural network model, and determine error information based on the output result, the error information indicating a qubit in which an error occurs in the quantum circuit and a corresponding error type.

A method, system, and computer program product for learning noise models to perform quantum error mitigation. Each target layer of a quantum circuit is divided into a set of sub-layers. Each of the sub-layers for each target layer of the quantum circuit is grouped into a reduced set of learning layers, which enables each sub-layer's noise model to be learned from fewer layers (learning layers). A learning layer refers to a layer that is used in combination with other learning layers to form the minimally complete layer set for learning all the layer components used in the quantum circuit. The noise models for each of the sub-layers are then learned on the reduced set of learning layers. Such learned noise models are combined to form a complete set of noise models for the target layers of the quantum circuit and used to perform quantum error mitigation on the quantum circuit.

Systems, methods, and apparatus for multiplexed control and readout of quantum computing systems that can include qubits, couplers, and other related quantum computing circuit devices. Numerous examples of superconducting quantum computing systems are described that include some, or all, of these quantum computing circuit devices integrated into a superconducting quantum circuit that can be interfaced by a classical control system. In one example, a superconducting circuit is described. The superconducting circuit includes: a superconducting device including a superconducting loop interrupted by one or more Josephson junctions; a first microwave resonator inductively coupled to the superconducting loop of the superconducting device; a second microwave resonator capacitively coupled to the superconducting device, where the first and second microwave resonators each have a different fundamental frequency; and a microwave transmission line evanescently coupled to each of the first and second microwave resonators.

Methods and systems determine a solution for an optimization problem using a quantum computer and a classical computer. The method comprises: receiving or determining, by the classical computer, a description of the problem; receiving or determining, by the classical computer, one or more quantum circuits defining gate operations to be executed by the quantum computer; determining, by the classical computer, an optimized first parametric quantum circuit comprising execution, by the quantum computer, of the gate operations; determining, using the quantum computer, an optimized input value in the input space; and determining, by the classical computer, the solution to the optimization problem based on the optimized input value and / or an output value corresponding to that optimized input value.

A method of estimating noise for individual gates of a quantum circuit uses averaged circuit eigenvalue sampling to determine an overall eigenvalue for the circuit. The circuit is sampled a sufficient number of times to fill a design matrix, wherein the design matrix allows for solving of a system of equations to determine eigenvalues for the individual gates using the averaged eigenvalue for the overall quantum circuit, the samples, and the sample results. Applying a logarithm to these relationships enables solving the system of equations using linear estimation or linear regression, in some embodiments.

The invention discloses a quantum bit mapping optimization method for hardware guidance and fidelity perception and a related device, and belongs to the field of quantum computing, and the method comprises the steps: defining each node in a hardware coupling graph of a target quantum processor as an initial community; evaluating all adjacent community pairs according to a reward function defined based on modularity and fidelity of candidate communities, selecting an optimal community pair for fusion, and taking the community with the largest current scale as an optimal candidate area; iteratively executing a community fusion step until a converged single community is obtained; and selecting an optimal candidate region with the physical quantum bit number greater than or equal to the logic quantum bit number of the quantum circuit to be mapped and the minimum scale, and outputting a mapping sub-graph. According to the method, through a recursive community fusion strategy, the operation range of the solver is restrained in a subspace with the scale greatly reduced and the quality better, the problem of combinatorial explosion caused by global search is fundamentally avoided, and the calculation overhead is greatly reduced.

Provided are computer-implemented methods and quantum computing systems for preparing computational states representing quantum states of a physical system, including performing a computational evolution of the state and then determining physical properties of the system using the time-evolved computational state. Hamiltonian dynamics of observables are computed on a quantum computer to provide information about the physical system represented by the Hamiltonian. Low energy electronic structure states of a physical system are prepared using adiabatic evolution. The energy of an equilibrium quantum state of a physical system is determined using a time-evolution operator. The energy of an eigenstate of a physical system is indirectly determined by evaluating expectation values of a time-evolution operator averaged across multiple shots for randomly-generated quantum circuits. Example methods enable calculation of the energy of an evolved computational state with chemical accuracy, due to avoiding discretization errors, with a smaller circuit depth than known alternatives.

The invention discloses a semiconductor data detection system and method based on artificial intelligence, and relates to the technical field of semiconductor detection.The method comprises the steps that parameterized revolving door operation is executed through a quantum circuit, a reformed group equation is constructed to generate a physical loss item, and meanwhile a generative adversarial network is constructed through a quantum discriminator and a quantum generator; generating an enhanced data set; constructing a physical topology adjacency matrix according to the enhanced data set, loading a source domain convolutional neural network model and carrying out feature transformation, and generating a physical constraint embedded analysis engine through a dynamic physical graph attention mechanism and lattice differential homeomorphic mapping; deploying a physical constraint embedded analysis engine, processing real-time wafer data, generating a lattice defect tensor and a time-space confidence field, obtaining a confidence score, triggering a process adjustment instruction when the confidence score meets a high confidence condition, and otherwise, storing data which does not meet the condition into a feedback queue; according to the invention, deep coupling of a quantum generation process and a semiconductor lattice physical rule is realized.

The invention discloses a method and system for determining the reaction activity of material molecules based on quantum computing, and relates to the technical field of material performance analysis based on quantum computing, and the method comprises the following steps: generating UCCSD (Unified Conduction Cancellation Standard Description) simulation containing a plurality of excitation operators according to the electronic structure of a target material molecule; constructing a quantum circuit based on all the excitation operators; when the ground state energy is calculated by using the VQE algorithm, initially setting each parameter as zero in the first calculation, calculating the current gradient of each parameter, updating the parameter value according to the gradient, and iterating until all gradients are zero to obtain the ground state energy; and finally determining the reaction activity of the molecules according to the ground state energy. According to the method, the initial parameter is set to be zero, the gradient calculation complexity is reduced by using the excitation operator ease relation, and measurement of a large number of expected values is avoided. And the line is directly constructed based on UCCSD, and bubble-string conversion and graph coloring preprocessing are not needed, so that the calculation overhead is reduced.

An assistive processing method and apparatus for quantum machine learning, a device, and a system, relating to the technical field of quanta. The method comprises: obtaining a unitary result generated in an execution process of a quantum machine learning task, wherein the unitary result is obtained by measuring a first quantum bit in a first parameterized quantum circuit used in the quantum machine learning task, and the first parameterized quantum circuit is used for executing a unitary operation on an initial quantum state of the first quantum bit; executing nonlinear processing on the unitary result to obtain a nonlinear processing result; and on the basis of the nonlinear processing result, indicating an initial quantum state of a second quantum bit to a second parameterized quantum circuit used in the quantum machine learning task, wherein the initial quantum state of the second quantum bit is determined by encoding the nonlinear processing result. Classical nonlinear processing is introduced in an intermediate execution stage of the quantum machine learning task, and nonlinear perception is carried out on the unitary result, thereby improving the expression precision of quantum machine learning.

The invention relates to the technical field of distributed quantum computing, in particular to a distributed quantum circuit state transfer evaluation method based on state transfer group scoring. According to the method, the problems that the existing method depends on a simplified scheduling model and channel contention possibly caused by parallel communication operation is not restrained are solved, and meanwhile, the defect that a scheduling feasibility verification mechanism is lacked is overcome. According to the technical scheme, the method comprises the following steps that S1, a quantum circuit partition structure is analyzed; s2, calculating potential scores of two bits in the global gate as state transmission bits; s3, expanding a state transmission group: moving the interference gate based on a gate exchange rule to expand the state transmission group; s4, performing scheduling feasibility verification on the state transfer group; S5, performing final state transfer frequency statistics; and calculating the total communication cost according to whether the state transfer group needs to return the cost. The method has the beneficial effects that the state transfer times are accurately evaluated; identification and optimization of the combined transmission opportunity are supported; and an evaluation strategy with adjustable parameters is supported.

The invention relates to the technical field of quantum computing, and provides a linear complexity quantum state preparation method based on tensor decomposition and a quantum circuit construction system.The high-dimensional tensor is decomposed into a series of low-rank core tensors through continuous singular value decomposition, each core tensor in a core tensor sequence is expanded into a unitary matrix, and the unitary matrix is used as a quantum circuit; the unitary matrix sequence is mapped to quantum lines coupled using adjacent qubits, and the quantum lines are run to prepare a target quantum state. Based on this, the line generated by the method can approximately or accurately prepare a target quantum state only by coupling adjacent quantum bits, and is perfectly adaptive to quantum chips of linear or grid topologies such as superconducting and semiconductor quantum dots and the like.

The embodiment of the invention discloses a quantum computer, a method and a related device for solving a combinatorial optimization problem, and the quantum computer comprises a measurement and control all-in-one machine which is configured to generate a control signal based on a constraint condition, the constraint condition is used for representing the constraint when a plurality of elements are combined; the quantum chip comprises at least one group of quantum bits, and the number of the quantum bits is the same as that of the elements; and the interface is connected with the measurement and control all-in-one machine and the quantum chip and is configured to control the quantum chip based on the control signal so as to generate an optimal combination of elements represented by the ground state of the group of quantum bits. By adopting the embodiment of the invention, the requirement of quantum bits can be effectively reduced, the method is suitable for a real quantum computer, and a practical and feasible quantum circuit can be operated to solve a combinatorial optimization problem.

The quantum state preparation method, device, medium and equipment for any real vector disclosed by the present invention relate to the technical field of quantum computing. Among them, the quantum state preparation method for any real vector includes: normalizing the first real vector to be encoded; determining whether there exists a positive integer n such that 2n=N; if it is determined that there is no positive integer n satisfying 2n=N, then determining the value of the positive integer n such that the positive integer n satisfies the condition 2n-1<N<2n; based on the values of the positive integer n and N, expanding the first real vector to obtain a second real vector; constructing a quantum circuit based on the second real vector; executing the quantum circuit to perform quantum state encoding on the second real vector to obtain an initial quantum state encoding result; and obtaining the quantum state encoding result of the first real vector based on the initial quantum state encoding result, thereby improving the efficiency and accuracy.

Systems, apparatuses, methods, and computer program products are disclosed for selecting a quantum circuit. An example method includes identifying, by communications hardware, a set of input attributes. The example method also includes determining, by quantum circuit selection circuitry, a set of quantum circuit selection criteria based on the set of input attributes. The example method also includes choosing, by the quantum circuit selection circuitry, a quantum circuit design from a collection of pre-determined quantum circuit designs and based on the set of quantum circuit selection criteria. The example method also includes generating, by quantum circuit generation circuitry, a quantum circuit for the chosen quantum circuit design. The example method also includes outputting, by the communications hardware, the generated quantum circuit.

A method, system, and computer program product for mapping a quantum circuit to a quantum processor. A light cone analysis is performed on the quantum circuit. A light cone refers to a map of the effects that the circuit operations have on the final observable value. Circuit operations that fall outside or within one or more light cones of non-identity operators in an observable based on the light cone analysis on the quantum circuit are then determined. The greater the number of overlapping or individual light cones that such circuit operations lie within, the greater the impact that such circuit operations have on the final observable value. A circuit mapping of the quantum circuit on the quantum processor is then determined based on the determination of which circuit operations fall outside or within the one or more light cones of non-identity operators in the observable.

The invention discloses a quantum optimization-oriented design method for realizing an S box circuit, which comprises the following steps of: S1, analyzing linear operation and nonlinear operation in classical implementation of an S box, and dividing a classical implementation structure of the S box; s2, designing quantum implementation of different modules in the classical implementation structure of the S box step by step; and S3, analyzing the combinability of a linear module implementation circuit in the quantum implementation of the S box to optimize the quantum implementation of the S box. The quantum implementation efficiency of the S box in the cryptographic algorithm is effectively improved, and the implementation cost of a related quantum circuit is reduced.

The invention relates to a quantum feature fusion method for improving a quantum convolutional neural network. The method comprises the following steps: firstly, performing data enhancement on input data and expanding training samples; then, inputting the enhanced data into a classic convolutional layer, and extracting local features; thirdly, performing quantum feature mapping on features extracted by the classical convolutional layer by using a quantum convolutional layer, and mapping the features to a high-dimensional Hilbert space; in a quantum feature fusion module, quantum features extracted by different quantum convolutional layers are fused through quantum circuit design, and efficient fusion of the features is realized. And finally, inputting the fused quantum features into a full connection layer to realize a classification or regression task. According to the method, the advantages of quantum calculation are fully utilized, and the feature extraction and fusion capability of the convolutional neural network is effectively improved through quantum feature fusion. The effectiveness of the method is verified through specific experiments.