683 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 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 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.

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.

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.

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.

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.

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.

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 a secondary quantization molecular Hamiltonian based on a target material molecular structure; traversing non-zero coefficient excitation terms in the molecular Hamiltonian, and screening an excitation operator conforming to the symmetry of a molecular point group as a target excitation operator; generating symmetric unitary coupling cluster single-double excitation simulation according to the target excitation operator; constructing a quantum circuit based on the configuration; and determining the reaction activity of the target material molecule by using the quantum circuit. According to the method, traditional manual symmetry analysis is avoided, professional knowledge is not needed, and the operation process is simplified. The method is systematized, easy to program and implement, high in universality and capable of being automatically expanded to any molecule, the design cost is remarkably reduced, and the molecular energy level solving efficiency is improved.

The invention provides a resource scheduling method, electronic equipment, a storage medium and a computer program product. The method comprises: obtaining global information of a target computing power network, the target computing power network comprising a plurality of nodes, the plurality of nodes comprising a plurality of user nodes, a plurality of network nodes and a plurality of computing nodes, the global information at least comprising state information of the plurality of nodes and state information of a plurality of transmission paths, each transmission path comprises a user node and a computing node; constructing a resource scheduling model of the target computing power network based on the global information of the target computing power network; converting the resource scheduling model into a quantum computing model; constructing a quantum circuit based on the quantum calculation model; and determining a resource scheduling result of the target computing power network according to the measurement result of the quantum circuit. Through the scheme provided by the invention, the global resource scheduling strategy can be quickly obtained.

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 provides a method for executing a dynamic quantum circuit on a superconducting quantum computing device, a superconducting quantum computing system and a computer readable storage medium, and the method comprises the following steps: dividing the dynamic quantum circuit into at least one main circuit and at least one control sub-circuit, the main circuit is a circuit which is not influenced by a measurement result in the dynamic quantum circuit during execution, and the control sub-circuit is a circuit which is controlled by depending on the measurement result in the dynamic quantum circuit during execution; and respectively carrying out routing compiling on the at least one main line and the at least one control sub-line so as to sequentially execute the at least one main line after routing compiling and the control sub-line which is determined to be required to be executed after routing compiling on the superconducting quantum computing equipment according to the execution time sequence of the dynamic quantum line.

The invention provides a surface code-based quantum circuit fault-tolerant compiling method and a surface code-based quantum circuit fault-tolerant compiling device. The method comprises the following steps: acquiring an input set and a quantum circuit; aiming at each initial parameter combination, according to the corresponding bit block number parameter and the corresponding factory number parameter, estimating execution time required for executing the quantum circuit; for each initial parameter combination, generating line space-time cost information of the quantum line according to the corresponding bit block number parameter, the corresponding factory number parameter and the corresponding execution time; determining a target parameter combination from the plurality of initial parameter combinations based on the respective line space-time cost information of the plurality of initial parameter combinations; and according to the target parameter combination, mapping the logic bit of the quantum circuit to the physical space of the chip, and scheduling the quantum operation in the mapped physical space to obtain a physical execution sequence.

The invention provides a distributed quantum circuit intelligent cutting method based on a large model. The method comprises the steps that an initial quantum circuit corresponding to a target quantum calculation task is acquired; constructing a cutting loss estimation model, performing multi-group cutting scheme simulation on the initial quantum circuit, and generating multiple groups of candidate cutting quantum circuits; a target cutting quantum circuit set meeting a preset optimal condition is screened out; training a preset large model by using the target cutting quantum circuit in the training set and the corresponding cutting scheme; verifying the generation precision of the trained large model by using the test set to obtain a target large model; and obtaining a to-be-cut quantum circuit of a new to-be-processed quantum calculation task, inputting the input features into the target large model, and directly outputting a cutting scheme and the cut quantum circuit by the target large model. According to the method, the quantum circuit structure and the von Noiemann entropy loss rule are learned through a large model, automatic low-loss cutting of the circuit is achieved, the generalization ability is high, and the method can adapt to diversified hardware environments.

The disclosure provides an image classification method, system, electronic device, and storage medium, including: acquiring a sample image and using a convolutional neural network module to convert the sample image into one-dimensional feature data; splitting one-dimensional feature data into multiple data segments, and using multiple quantum circuits in the quantum layer module to process all data segments in parallel; concatenating the output results of all quantum circuits to acquire a concatenated vector, and using the classification layer module to output the category prediction results corresponding to the concatenated vector; calculating the loss function value based on the category prediction results and the category labels of sample images, and train an image classification model; an unknown image corresponding to the image recognition task is determined, and the trained image classification model is used to output the image category of the unknown image.

A computer-implemented method for training a machine learning model (27) using a training dataset (28) having a set of distributional parameters θ is disclosed. The method comprises selecting (S205) stochastically a subset (28a) from the training dataset (28), calculating a gradient of the subset (28a) by encoding (S210) a cost function representative of the gradient into a quantum circuit, amplifying (S220) the amplitude of the quantum circuit, constructing a likelihood function (S230), and minimising the cost function in a variational quantum circuit to optimise the distributional parameters, extracting the optimised distributional parameters, and entering the optimised distributional parameters into the machine learning model (27).

A quantum device includes a quantum chip including a superconducting quantum circuit; an interposer including mounting the quantum chip on a first surface thereof; a housing having openings penetrating from a first surface of the housing opposing a second surface of the interposer to a second surface of the housing with probe pins housed in the opening, a board with a first surface facing the second surface of the housing; and one or more spacers between the first surface of the housing and the second surface of the interposer to ensure a clearance between the first surface of the housing and the second surface of the interposer facing the first surface of the housing.

The invention provides a transaction risk identification method and device, electronic equipment, a medium and a program product, and can be applied to the technical field of quantum and the technical field of artificial intelligence. The method comprises the following steps: acquiring a high-dimensional feature vector related to a to-be-detected transaction; the high-dimensional feature vector is input into a quantum auto-encoder model constructed based on a parameterized quantum circuit for quantum feature compression, low-dimensional compression features are output, and the quantum auto-encoder model is obtained based on pre-training of a loss function weighted by abnormal risk samples; inputting the low-dimensional compression features into a classification model, and outputting a transaction risk probability value; and performing transaction risk identification on the to-be-detected transaction based on the risk probability value.

The invention provides a quantum circuit system based on an AES cryptosystem and an encryption method. The quantum circuit system based on the AES cryptosystem comprises a byte replacement module which adopts a pre-optimized S-box query circuit to realize non-linear byte replacement; the row shift module completes in-row byte cyclic shift through quantum bit exchange operation; the column confusion module realizes a matrix multiplication circuit based on finite field operation, and a quantum circuit of the column confusion module is generated by a depth-first matrix decomposition algorithm; and the round key adding module realizes XOR operation of a round key and a state by using a CNOT gate array, and a key required by the round key adding module is dynamically generated through a key expansion circuit. And a compact Z-shaped architecture is adopted to optimize time sequence scheduling and resource allocation of each module. On the premise of keeping the quantum bit resource usage amount equivalent to that of an original Z-shaped architecture, the quantum circuit depth is remarkably reduced, and higher fidelity and shorter execution time can be realized on NISQ equipment.

The invention discloses a high polymer material performance prediction method and system based on deep learning, and the method comprises the steps: constructing an automatic encoder, and carrying out the dimension reduction of various data of a high polymer material through unsupervised learning; optimizing a multi-mode encoder structure by adopting an automatic design mechanism; extracting a fusion characteristic value of the high polymer material by using a multi-modal data encoder; dynamic attention fusion: introducing a dynamic gating weight to adaptively distribute modal weights to input data; introducing physical constraint, and embedding molecular dynamics into back propagation; performing quantum circuit acceleration graph convolution; and predicting and outputting, mapping the fusion characteristic value to the tensile strength and elastic modulus performance indexes of the high polymer material, and realizing nonlinear regression through a multi-layer perceptron. According to the method, a material molecular dynamics equation is converted into a forward propagation kernel from a posterior constraint, the dynamic behaviors of molecules can be simulated and predicted more accurately, and the calculation efficiency is improved while the precision is ensured.

The invention provides a digital quantum simulation method, which comprises the following steps of: performing symmetry analysis and subspace decomposition on a target Hamiltonian to obtain an effective Hamiltonian and a symmetry constraint condition; constructing a target unitary operator according to the effective Hamiltonian, and initializing a quantum circuit population of the target unitary operator; calculating entanglement characteristics of each quantum line in the quantum line population, performing structure variation on the quantum line population based on the entanglement characteristics, and performing line fragment crossing in combination with a symmetry constraint condition to obtain a candidate line set; performing line parameter optimization on the candidate line set based on the fidelity gradient to obtain an optimized line set, and extracting gate distribution structure features of the optimized line set; and non-uniform sampling is carried out on the optimized line set based on gate distribution structure characteristics to obtain a sampling line subset, an optimal quantum line is screened out from the sampling line subset based on the deviation between an experimental observation value and a theoretical expected value, and quantum simulation is carried out based on the optimal quantum line.

The invention discloses a task processing method and device based on quantum computing, equipment and a storage medium. The method comprises the steps of determining a maximum cut problem corresponding to a target task and a weighted undirected graph of the maximum cut problem; performing community detection division on the weighted undirected graph to obtain a plurality of community sub-graphs; mapping the community sub-graph into a sub Hamiltonian and constructing a parameterized quantum circuit; updating parameters of the parameterized quantum circuit by adopting a gradient descent algorithm to minimize a global Hamiltonian expected value, and outputting a binary string of a quantum state corresponding to the global Hamiltonian expected value as an initial solution; generating a plurality of candidate solutions for the initial solution based on a neighborhood search algorithm, calculating cut values of the initial solution and the candidate solutions, and selecting a better feasible solution based on the optimal cut value; and applying a preset disturbance operator in the parameterized quantum circuit to construct a disturbance quantum circuit, updating parameters of the disturbance quantum circuit by adopting a gradient descent algorithm, and outputting a binary string of a quantum state corresponding to the global Hamiltonian expected value as a final solution of the target task by minimizing the global Hamiltonian expected value after disturbance.

An information processing apparatus generates, based on a first dynamic quantum circuit, a plurality of candidate assignments. The information processing apparatus generates, based on the plurality of candidate assignments, second dynamic quantum circuits that satisfy a constraint condition. The information processing apparatus acquires measurement results at a measurement point in a plurality of quantum computations executed in accordance with second dynamic quantum circuits corresponding to a part of the plurality of candidate assignments. The information processing apparatus calculates, based on the measurement results, an index value affecting fidelity for each of the plurality of candidate assignments, the index value representing fidelity when quantum computation is executed in accordance with the corresponding second dynamic quantum circuit. The information processing apparatus determines an assignment based on the index value.

A non-transitory computer-readable recording medium stores a quantum computation support program for causing a computer to execute a process including: training a regression model in which parameter values are explanatory variables and computation results of quantum computation are objective variables, based on a correspondence relationship between the computation results for each of a plurality of times of quantum computation for each of the parameter values according to a quantum circuit that includes parameters and the parameter values set in the quantum computation; and specifying a solution of the quantum computation by using the regression model.

The invention relates to a multi-modal sentiment analysis method based on a large language model and quantum computing, and belongs to the technical field of multi-modal feature alignment and fusion. The multi-modal sentiment analysis method comprises the steps of constructing a multi-modal sentiment analysis data set, extracting text features and multi-granularity image sentiment description features by using the large language model and a target detection technology, carrying out multi-level fusion on the image emotion description and the original text to obtain cross-modal potential emotion association information; designing a cross-modal feature fusion mechanism based on a parameterized quantum circuit, and performing efficient fusion on multi-modal features by using quantum superposition and quantum entanglement features to generate unified emotion feature representation; performing sentiment classification based on the sentiment feature representation, and outputting a sentiment analysis result; according to the method, cross-modal potential emotion association can be effectively captured, the fusion efficiency and expression ability of multi-modal features are improved, the method is remarkably superior to the prior art in emotion analysis tasks, and the robustness and accuracy are high.

The invention discloses a quantum circuit compiling method based on neutral atom hardware topology and a related device, and belongs to the technical field of quantum computing, and the method comprises the following steps: obtaining characteristic parameters of a quantum circuit to be compiled; forming a feature vector by the obtained feature parameters of the quantum circuit, and inputting the feature vector into a pre-trained classical neural network to determine a neutral atom hardware topological structure to be subjected to mapping operation; wherein the pre-trained classical neural network is used for determining a neutral atom hardware topological structure of the quantum circuit to be compiled based on the characteristic parameters of the quantum circuit; executing mapping operation on the quantum circuit based on the neutral atom hardware topological structure; according to the quantum circuit compiling method of the neutral atom hardware topological structure, the diversified requirements of different application fields are met, the new method can provide more technical adaptation routes for a future multi-back-end quantum computing framework, and the robustness and flexibility of a quantum computing system are improved.