1016 results about "Quantum circuit" patented technology

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.

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.

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.

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.

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 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.

The invention discloses a quantum algorithm code generation method and device, equipment and a storage medium. The method comprises the steps that first prompt information is obtained; at least inputting the first prompt information into a generation model, and generating quantum algorithm text description information by the generation model; the quantum algorithm text description information is used for describing candidate quantum circuits for realizing a target task; and inputting second prompt information obtained based on the quantum algorithm text description information into the generation model, and generating an executable quantum algorithm code by the generation model.

The invention provides a quantum system data processing method based on light quantum and a light quantum computer, and the method comprises the steps: obtaining an ordinary differential equation and the attribute information of the ordinary differential equation; according to the frequency spectrum number of the ordinary differential equation and the attribute information of the ordinary differential equation, constructing an initial light quantum circuit corresponding to the ordinary differential equation; 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 quantum system based on the target light quantum line. According to the method, the light quantum circuit expression capability can be greatly improved, and high-precision solving of the ordinary differential equation is realized.

The invention discloses a quantum circuit conversion method and system, electronic equipment and a storage medium, and relates to the technical field of quantum circuit conversion, and the method comprises the steps: extracting a feature vector of a logic quantum circuit based on initial quantum bit mapping; the feature vector is input into a pre-trained decision tree, recommendation parameters of a line conversion algorithm are obtained, the decision tree is constructed by a training set, and the feature vector of each sample corresponds to the optimal parameter of the decision tree, namely the parameter with the minimum number of physical line gates; and configuring a line conversion algorithm by using recommended parameters, converting a logic line into a physical line, and ensuring that all two quantum bit gates meet quantum computer connected graph constraints and are equivalent in function. According to the method, adaptive parameter configuration can be achieved through the feature vectors and the decision tree, the line conversion quality is effectively improved, the number of physical line gates is remarkably reduced, and the quantum program execution efficiency is improved on the premise that function equivalence and connectivity are guaranteed.

Cutting quantum circuits is disclosed. A graph representation of a quantum circuit includes layers. Vector layers, each of which represents a subgraph of the graph, are generated from the layers. The vector layers are sequentially input to a model that is configured to generate a probability for the vector layer and the corresponding graph layer. The probability represents whether the layer is a good cutting point for cutting the quantum circuit. A cutting operation may be performed to cut the quantum circuit at the cutting points.

A computing system including one or more classical binary computers coupled to one or more quantum computers. The computing system is configured to process the one or more computing tasks including at least one combinatorial optimization task using a Filtering Variational Quantum Eigensolver (F-VQE) algorithm implemented by using one or more Ansätze circuits and a cost function arrangement to generate one or more quantum circuits in the quantum computer. The computing system iteratively applies a filtering operator to a cost function arrangement to generate a corresponding filtered cost function arrangement that excludes energy states that exceed an energy threshold and uses the filtered cost function arrangement in the one or more quantum circuits to generate output results.

The invention discloses a robot environment identification method based on multi-modal fusion, and the method comprises the following steps: collecting image data, point cloud data and acoustic data in a robot operation environment, and carrying out the preprocessing; inputting the structured multi-modal input sample into a modal perception type quantum encoder of a multi-modal quantum graph neural network; constructing a modal coupling quantum diagram based on the modal quantum state representation set; inputting the modal coupling quantum diagram into an entangled modal propagation unit, and performing cross-modal information propagation of nodes of the modal coupling quantum diagram through a parameterized quantum circuit; quantum measurement operation is executed on the fusion quantum graph embedded representation, and an environment recognition result is output; and inputting an environment identification result into a robot control module, and driving the robot to execute path adjustment, obstacle avoidance or action response. According to the method, the multi-mode quantum graph neural network is adopted, and autonomous recognition of the robot in a complex environment is achieved.

Methods, systems and apparatus for measuring quantum state purity. In one aspect, a method for determining an average purity of multiple output quantum states, wherein the multiple output quantum states correspond to applications of respective random quantum circuits of a same circuit depth to a same initial quantum state, the method including: obtaining a plurality of data items, wherein each data item corresponds to a respective random quantum circuit of the same circuit depth and represents a probability that application of the respective random quantum circuit to the initial quantum state produces a respective measurement result; calculating a variance of a plurality of data items; determining a Porter-Thomas distribution having a dimension equal to a dimension of each output quantum state; and dividing the calculated variance by a variance of the Porter-Thomas distribution to determine the average purity.

A quantum method, receives by a quantum circuit, quantum information from a first block within a blockchain. The quantum method performs quantum voting in each node in the quantum blockchains. The quantum method uses entanglement capabilities for achieving consensus voting.

The invention discloses a variable component sub-line compilation optimization method and a related device, and belongs to the technical field of quantum computing, and the method comprises the following steps: if a variable component sub-line is not compiled for the first time and a mapping relation is unchanged, calling quantum hardware resources to execute the compiled variable component sub-line so as to update logic gate parameters in the variable component sub-line, the mapping relation is used for representing the corresponding relation between the logic bits in the variable component sub-lines and the physical bits in the quantum hardware resources. According to the method, the mapping relation result is stored during the first compiling, and a mechanism for judging whether the compiling is the first compiling is introduced into the compiling process, so that the tedious remapping operation is avoided, the time and computing resources required by the compiling process are remarkably reduced, the parameter updating can be quickly responded, and the execution efficiency of the variable component sub-line is improved.

The invention discloses a quantum circuit compiling method and system, a terminal and a computer readable storage medium. The quantum circuit compiling method comprises the steps of obtaining target unitary transformation and hardware constraints; converting a unitary transformation space parameter corresponding to the target unitary transformation into a Riemannian manifold; calculating a geodesic path using a Lagrange action amount based on the Riemannian manifold and the hardware constraint; synthesizing a gate sequence of the geodesic line path; a compiling circuit with authenticated minimum depth and maximum fidelity is output based on the synthesized gate sequence. The compilation circuit obtained by the invention has circuit optimality mathematical guarantee.

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. A described computer-implemented method enables computing Hamiltonian dynamics of observables on a quantum computer to provide information about the physical system represented by the Hamiltonian. A described computer-implemented method prepares low energy electronic structure states of a physical system using adiabatic evolution. The method determines the energy of an equilibrium quantum state of a physical system using a time evolution operator that enables adiabatic evolution of a prepared electronic structure state on a quantum computing system. A described method involves indirectly determining the energy of an eigenstate of a physical system by evaluating the expectation values of a time-evolution operator averaged across multiple shots for randomly-generated quantum circuits.

The embodiment of the invention provides an artificial intelligence model training method and device, electronic equipment and a storage medium, and aims to reduce the cost of applying a quantum technology to AI model training and improve the training efficiency of an AI model. The method comprises the following steps: a central processing unit performs data preprocessing on original training data acquired from a memory; the original training data comprises a training set; executing the following iterative training steps on a to-be-trained artificial intelligence AI model until a preset iterative stop condition is met: inputting the training set into the to-be-trained AI model by the graphics processor, and obtaining a loss function corresponding to a current parameter of the to-be-trained AI model; the quantum processor encodes the loss function into a quantum state; the quantum processor constructs a quantum circuit based on the loss function of the quantum state, and measures the quantum gradient of the loss function through the quantum circuit; the quantum processor updates the current parameter based on the quantum gradient and a preset regularization gradient.

Aspects of the present disclosure relate generally to systems and methods for detecting change in images using a quantum information processing (QIP) system. The method includes implementing a quantum circuit in the QIP system, the quantum circuit comprising at least an ancilla qubit denoted as |a> and qubits denoted as image qubit conditions on a |0> state and a |1> state of the ancilla qubit |a>. The method also includes loading a reference image and a test image onto image qubits controlled on the |0> state and the |1> state of the ancilla qubit |a> in the quantum circuit. The method further includes determining a state of the image qubits after measuring |1> on the ancilla qubit for a predetermined number of times, wherein the reference image is detected to be different from the test image when the state of the ancilla qubit measures |1>.

Aspects of the present disclosure relate generally to systems and methods for optimizing an implementation of a quantum chemistry task in a quantum circuit. The method includes obtaining a chemistry task presented as a Hamilton to implement in a Variational Quantum Eigensolver (VQE) circuit. The method also includes mapping the chemistry task to a qubit space of the VQE circuit with Unitary Coupled Cluster with Single and Double excitations (UCCSD) ansatz. The method also includes decomposing the fermionic excitations to Givens rotations and controlled-Z (CZ) gates by passing exponentiated Pauli forms in the VQE circuit to a cloud compiler. The method further includes after commuting the CZ gates through Givens rotations, cancelling the commuted CZ gates. The method further includes dropping CZ gates at the beginning and the end of the quantum circuit.