A data processing method and related apparatus

Abstract

This application discloses a data processing method and related apparatus. The method includes: obtaining a probability storage matrix and reconstructed data corresponding to a segmented circuit to be reconstructed; processing the probability storage matrix and the reconstructed data according to a reconstruction rule corresponding to the segmented circuit to be reconstructed, to obtain the output result of the original quantum circuit, wherein the reconstruction rule is determined by the relationship between the segmented circuits to be reconstructed in the original quantum circuit. Using the embodiments of this application, data reconstruction efficiency is improved.

Description

Technical Field

[0001] This application belongs to the field of data processing technology, and in particular to a data processing method and related apparatus. Background Technology

[0002] Quantum circuits (also known as quantum logic circuits) are the most commonly used general-purpose quantum computing model, representing circuits that operate on qubits under an abstract concept. They consist of qubits, circuits (timelines), and various logic gates, and the results are finally read out through quantum measurements.

[0003] Current quantum circuit decomposition techniques are used to break down large-scale quantum circuits into smaller circuits that can run on NISQ (Noisy Intermediate-Scale Quantum) computers. This allows for the simulation of large-scale quantum circuits using small-scale quantum hardware to solve large-scale problems, thereby obtaining potential computing power between quantum computing and classical computing.

[0004] When a quantum circuit is segmented, the completeness requirement of the quantum data stream must be met, ensuring that the output of the segmented quantum circuit is identical to that of the original quantum circuit. Each segmented circuit (corresponding to a module of the unsegmented quantum circuit) requires multiple sub-circuits under different measurement substrates or different input quantum states to characterize it. The probability distributions obtained by state tomography of these sub-circuits need to be stored for subsequent recovery or solution of the overall probability distribution of the complete circuit or the objective function. To meet the completeness requirement, existing methods involve sequentially multiplying and summing the probabilities of the output points of the multiple sub-circuits representing each segmented circuit. Since the number of multiplication terms increases exponentially with the number of segmentation points, this operation introduces exponential complexity, significantly increasing the data reconstruction time and thus reducing data reconstruction efficiency. Summary of the Invention

[0005] The purpose of this application is to provide a data processing method and related apparatus to address the shortcomings of the prior art. It processes the probability storage matrix and recombined data according to the recombination rules, and efficiently utilizes computing power based on matrix operations, thereby improving the data recombination efficiency.

[0006] One embodiment of this application provides a data processing method, the method comprising:

[0007] Obtain the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled. The segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point. The probability storage matrix consists of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled. The output quantum states are the quantum states evolved from different input quantum states by the corresponding segmented circuit to be reassembled. The measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases. The segmented qubits are the qubits with cutting points on the corresponding timeline.

[0008] Based on the recombination rules corresponding to the segmented circuits to be recombined, the probability storage matrix and the recombination data are processed to obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0009] Optionally, the recombined data includes:

[0010] A first matrix composed of first coefficients, wherein the first coefficients are the coefficients of the decomposition of an output quantum state of a cut qubit on each measurement basis;

[0011] A second matrix consisting of second coefficients, where the second coefficients are the coefficients of different input quantum states of a cut qubit through a corresponding output quantum state.

[0012] Optionally, the recombined data further includes:

[0013] The third matrix is ​​used to implement the first element and the second element, wherein the first element is an element in the probability storage matrix corresponding to a segmented circuit to be reassembled, and the second element is an element in the first matrix.

[0014] Optionally, the third matrix includes:

[0015]

[0016] Among them, C t Let I be the third matrix, I be the identity matrix, and t be the number of cut points on the timeline that correspond to two adjacent segments to be reassembled.

[0017] Optionally, the step of processing the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuit to be reassembled, and obtaining the output result of the original quantum circuit, includes:

[0018] Determine the relationship between the segmented circuits to be reassembled in each group of segmented circuits to be reassembled, and define the reassembly type of each group of segmented circuits to be reassembled.

[0019] Based on the correspondence between the reassembly type and the reassembly rule, determine the reassembly rule corresponding to each group of segmented circuits to be reassembled;

[0020] Based on the determined recombination rules, the corresponding probability storage matrix and recombination data are processed to obtain the output of the original quantum circuit.

[0021] Optionally, determining the reassembly rule for each group of segmented circuits to be reassembled based on the correspondence between reassembly types and reassembly rules includes:

[0022] When the recombination type is sequential recombination, the recombination rules corresponding to sequential recombination include:

[0023]

[0024] in, These are the probability storage matrices corresponding to segment A and segment B in a set of segmented circuits to be reassembled, respectively. R Let U be the first matrix. L This is the second matrix;

[0025] When the recombination type is an embedded recombination, the recombination rules corresponding to the sequential recombination include:

[0026]

[0027] Among them, the segmented circuit A to be reassembled and the segmented circuit B to be reassembled are embedded.

[0028] Optionally, the method further includes:

[0029] When there is a segmented circuit in a set of circuits to be reassembled where the number of input points is not equal to the number of output points, in addition to cutting the qubits, a new cutting qubit is determined in the segmented circuit to be reassembled, and a new cutting point is set on the new cutting qubit.

[0030] Another embodiment of this application provides a data processing apparatus, the apparatus comprising:

[0031] The acquisition module is used to acquire the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled. The segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point. The probability storage matrix consists of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled. The output quantum states are the quantum states evolved from different input quantum states through the corresponding segmented circuit to be reassembled. The measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases. The segmented qubits are the qubits with cutting points on the corresponding timeline.

[0032] The processing module is used to process the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuits to be recombined, and obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0033] Another embodiment of this application provides a super-cooperative operating system, which processes data according to the method described in any of the preceding claims.

[0034] Another embodiment of this application provides a storage medium storing a computer program, wherein the computer program is configured to implement the method described in any of the above-described embodiments when running.

[0035] Another embodiment of this application provides an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to implement the method described in any of the above embodiments.

[0036] Compared with existing technologies, this application first obtains the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, and then processes the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuit to be reassembled to obtain the output result of the original quantum circuit. The probability storage matrix can contain all probabilities corresponding to the segmentation of qubits. Based on the operation of the probability storage matrix and the recombination data, the recombination result can be obtained. Compared with calculating one by one, this application uses matrix operations to realize the overall operation on the data corresponding to the segmented circuit to be reassembled, which efficiently utilizes computing power and thus improves the efficiency of data recombination. Attached Figure Description

[0037] Figure 1 This is a network block diagram of a data processing system provided in an embodiment of this application;

[0038] Figure 2 A flowchart illustrating a data processing method provided in an embodiment of this application;

[0039] Figure 3 A schematic diagram of quantum circuit cutting provided for an embodiment of this application;

[0040] Figure 4 A schematic diagram of a segmented circuit to be reassembled, consisting of multiple sub-circuits, provided for an embodiment of this application;

[0041] Figure 5 A schematic diagram of a segmented circuit to be reassembled with an embedded relationship, provided for an embodiment of this application;

[0042] Figure 6A schematic diagram of a recombined segmentation circuit with added new cutting points provided in an embodiment of this application;

[0043] Figure 7 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application. Detailed Implementation

[0044] The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain this application, and should not be construed as limiting this application.

[0045] Figure 1 This is a network block diagram of a data processing system provided in an embodiment of this application. The data processing system may include a network 110, a server 120, a wireless device 130, a client 140, a storage unit 150, a classical processing system 160, a quantum processing system 170, and may also include additional memory, a classical processor, a quantum processor, and other devices not shown.

[0046] Network 110 is a medium used to provide communication links between various devices and computers connected together within a data processing system, including but not limited to the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof. The connection method can be wired, wireless communication links, or fiber optic cables.

[0047] Server 120 and client 140 are conventional data processing systems that may contain data and applications or software tools that perform conventional computational processes. Client 140 may be a personal computer or a network computer, so the data may also be provided by server 120. Wireless device 130 may be a smartphone, tablet, laptop, smart wearable device, etc. Storage unit 150 may include database 151, which can be configured to store data such as qubit parameters, quantum logic gate parameters, quantum circuits, and quantum programs.

[0048] The classical processing system 160 (quantum processing system 170) may include a classical processor 161 (quantum processor 171) for processing classical data (quantum data) and a memory 163 (memory 172) for storing classical data (quantum data). The classical data (quantum data) may be a boot file, an operating system image, and an application program 162 (application program 173). The application program 162 (application program 173) may be used to implement a quantum algorithm compiled according to the data processing method provided in the embodiments of this application.

[0049] Any data or information stored or generated in the classical processing system 160 (quantum processing system 170) can also be configured to be stored or generated in another classical (quantum) processing system in a similar manner, and any application executed therein can also be configured to be executed in another classical (quantum) processing system in a similar manner.

[0050] It should be noted that a true quantum computer has a hybrid structure, which includes at least... Figure 1 The system consists of two main parts: the classical processing system 160, which is responsible for performing classical calculations and control; and the quantum processing system 170, which is responsible for running quantum programs and thus realizing quantum computing.

[0051] The aforementioned classical processing system 160 and quantum processing system 170 can be integrated into a single device or distributed across two different devices. For example, the first device, including the classical processing system 160, runs a classical computer operating system that provides quantum application development tools and services, as well as the storage and network services required for quantum applications. Users develop quantum applications using the quantum application development tools and services on the second device and send the quantum program to the second device, including the quantum processing system 170, via the network services. The second device runs a quantum computer operating system, which parses the code of the quantum program and compiles it into instructions that can be recognized and executed by the quantum computer control system. The quantum processor 170 then implements the quantum algorithm corresponding to the quantum program based on these instructions.

[0052] In the classic silicon-based processing system 160, the units of the classic processor 161 are CMOS transistors. These computing units are not limited by time or coherence; that is, they are available at any time without time constraints. Furthermore, the number of these computing units in a silicon chip is sufficient; currently, a classic processor contains tens of thousands of computing units. The sufficient number of computing units and the fixed selectable computing logic of the CMOS transistors, such as AND logic, allow for computational efficiency through a combination of numerous CMOS transistors and limited logic functions.

[0053] Unlike the logic units in the classical processing system 160, the basic computational unit of the quantum processor 171 in the quantum processing system 170 is the qubit. The input of a qubit is limited by coherence and coherence time; that is, a qubit is limited by its usage time and is not always available. Making full use of qubits within their available time is a key challenge in quantum computing. Furthermore, the number of qubits in a quantum computer is one of the representative indicators of its performance. Each qubit performs computational functions through on-demand configured logic functions. Given the limited number of qubits and the diverse logic functions available in quantum computing, such as Hadamard gates (H gates), Pauli-X gates (X gates), Pauli-Y gates (Y gates), Pauli-Z gates (Z gates), X gates, RY gates, RZ gates, CNOT gates, CR gates, iSWAP gates, Tofoli gates, etc., quantum computing requires combining a limited number of qubits with diverse logic function combinations to achieve the desired computational effect.

[0054] Based on these differences, the design of logical functions applied to qubits (including the design of whether qubits are used and the design of the efficiency of each qubit's use) is crucial to improving the computational performance of quantum computers and requires specialized design. The aforementioned design considerations for qubits are technical problems that ordinary computing devices do not need to address. Therefore, this application proposes a data processing method and related apparatus to improve data recombination efficiency in order to achieve high-efficiency data processing.

[0055] See Figure 2 , Figure 2 A flowchart illustrating a data processing method provided in this application embodiment may include the following steps:

[0056] S201: Obtain the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, wherein the segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point, the probability storage matrix is ​​composed of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled, the output quantum states are the quantum states after different input quantum states have evolved through the corresponding segmented circuit to be reassembled, the measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases, and the segmented qubits are the qubits with cutting points on the corresponding timeline.

[0057] The preset cutting point can be selected based on actual conditions or according to preset cutting rules, thereby determining the cutting position in the original quantum circuit. The segmented circuit to be reassembled can be obtained by directly cutting at the cutting point, or it can be obtained by reassembling the segmented circuits obtained from the cutting. The segmented circuit to be reassembled contains at least one multi-qubit quantum logic gate, and the segmented circuits are distinguished by the corresponding quantum logic gates in the circuit. Figure 3 As shown, a segmented circuit to be reassembled corresponds to quantum logic gate A, and this segmented circuit can be called reassembled segmented circuit A. Quantum logic gates A and B each represent an operator block (or unitary matrix). The operator block and the qubits acting on it constitute the segmented circuit to be reassembled. The operator block can be a basic module constituting the original quantum circuit. The operator block includes a multi-qubit quantum logic gate, which can be obtained by combining multiple single-qubit quantum logic gates and / or multi-qubit quantum logic gates. Figure 3 In the diagram, the positions marked by paired triangles are the cutting points, and the qubits located at the cutting points are the cut qubits. The left triangle represents the output point (also known as the measurement point), and the right triangle represents the input point. After the original quantum circuit is cut at this position, the eigenvalues ​​measured on the left under the measurement basis need to be input to the right to correspond to the operation of the original quantum circuit.

[0058] It should be noted that the division of qubits into cut and uncut qubits is determined based on the existence of a cutting point on the corresponding timeline. This corresponding timeline is the timeline between the circuit to be reassembled that executes later, and the execution sequence is determined based on the original quantum circuit. The division of qubits into cut and uncut qubits is determined by executing two adjacent circuits to be reassembled, with the circuit to be reassembled earlier executing first. Figure 3 For example, in segmented quantum circuit A, the number of cut qubits is q4, and the number of uncut qubits is q3; in segmented quantum circuit B, the number of cut qubits is q5, and the number of uncut qubits is q4.

[0059] The probability distribution of the uncut qubits in the segmented circuit to be reassembled is omitted, and the probability storage matrix U is used. p It can be represented by the following matrix:

[0060]

[0061] Each row corresponds to the probability statistics of the output of the |0> and |1> states obtained by measuring the qubits when the input quantum states are |0>, |1>, |+>, and |i>, respectively. Each column corresponds to the probability of obtaining the |0> and |1> states under different measurement bases I, X, and Y. Since the eigenvectors of measurement bases I and Z are the same, the corresponding probabilities are the same. Therefore, measurement base I is used as the representative in the probability storage matrix. The probability storage matrix can be a 4×6 matrix, which can be converted into a higher-order tensor. Here, 4 represents the four input quantum states, and since the probability of measuring the |0> and |1> states under the measurement bases is 2×3=6. A probability storage matrix can store one of the probability distributions of all actual output qubit segments. For multiple actual outputs, the same number of storage matrices are needed, i.e., third-order tensors. The number of eigenstates of the output of a segmented circuit to be reassembled is m*n*a, where m is the number of input quantum states, n is twice the number of measurement bases, and a is the number of output quantum states of the uncut qubits in the segmented circuit to be reassembled.

[0062] A segmented circuit to be reassembled can be composed of multiple sub-circuits, for example, such as... Figure 4 As shown, the entangled quantum information flow is decomposed into a linear combination of non-entangled information flows through sub-circuits. The quantum processing system 170 runs each sub-circuit, obtains the measurement results of each sub-circuit, and sends the measurement results to the classical processing system 160. The classical processing system 160 uses the measurement results to generate a probability storage matrix.

[0063] The recombined data refers to the data required for data reconstruction, excluding the probability storage matrix. The recombined data is the same for different segments of the circuit to be recombined; that is, the recombined data does not change with the segment to be recombined, but is determined by the unique properties of quantum computing.

[0064] S202: Based on the recombination rules corresponding to the segmented circuits to be recombined, process the probability storage matrix and the recombination data to obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0065] To obtain the output of the original quantum circuit, the data corresponding to the segments to be reassembled must be reassembled. Therefore, reassembly cannot be arbitrary. To obtain the correct output, the reassembly rules must be determined by the relationships between the circuits to be reassembled. Different relationships between the circuits may lead to different processing methods for the probability storage matrix and the reassembled data. The reassembly rules determine the data processing method. The relationships between the segments to be reassembled determine how the quantum state evolves. Setting reassembly rules according to a consistent evolutionary pattern can satisfy the completeness requirement of the quantum data stream.

[0066] As can be seen, this embodiment first obtains the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, and then processes the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuit to be reassembled to obtain the output result of the original quantum circuit. The probability storage matrix can contain all probabilities corresponding to the segmentation of qubits. Based on the operation of the probability storage matrix and the recombination data, the recombination result can be obtained. Compared with calculating one by one, this application uses matrix operation to realize the overall operation on the data corresponding to the segmented circuit to be reassembled, which efficiently utilizes computing power and thus improves the efficiency of data recombination.

[0067] In some possible implementations of this application, the reconstructed data may include:

[0068] A first matrix composed of first coefficients, wherein the first coefficients are the coefficients of the decomposition of an output quantum state of a cut qubit on each measurement basis;

[0069] A second matrix consisting of second coefficients, where the second coefficients are the coefficients of different input quantum states of a cut qubit through a corresponding output quantum state.

[0070] The output quantum state of a diced qubit is the quantum state obtained by measuring the measurement point of the diced qubit on different measurement bases. For example, considering a segmented circuit to be reassembled with one diced qubit and two uncooked qubits, where the output quantum state of the two uncooked qubits is the |01> state, the decomposition of the segmented circuit to be reassembled on different measurement bases can be as follows:

[0071] p 1，1 =p(|010>|I)+p(|011>|I)+p(|010>|Z)-p(|011>|Z)

[0072] p 1，2 =p(|010>|I)+p(|011>|I)-p(|010>|Z)+p(|011)|Z)

[0073] p 1，3 =p(|010>|X)-p(|011>|X)

[0074] p 1，4 =p(|010>|Y)-p(|011>|Y)

[0075] Since measurement basis I and measurement basis Z have the same eigenvectors, the coefficients of the decomposition quantities corresponding to these two measurement bases can be combined to obtain a first matrix U with a dimension of 6×4. R It can be as follows:

[0076]

[0077] The second matrix consists of the coefficients of the output quantum states obtained by the evolution of different input quantum states (|0> state, |1> state, |+> state, |i> state) through the corresponding recombined segmentation circuits. For example, taking an output quantum state of the recombined segmentation circuit as |010>, the coefficients of this output quantum state can be:

[0078] p 2，1 =p(|010>||0>)

[0079] p 2，2 =p(|010>||1>)

[0080] p 2，3 =2p(|010>||+>)-p(|010>||0>)-p(|010>||1>)

[0081] p 2，4 =2p(|010>||i>)-p(|010>||0>)-p(|010>||1>)

[0082] Based on the coefficients above, we can obtain a second matrix U with a dimension of 4×4. L As shown below:

[0083]

[0084] It should be noted that the coefficients of the decomposed quantities of the output quantum state obtained on the measurement basis are constant. For different input quantum states, the coefficients of the output quantum state are also constant. The corresponding probabilities will change with different input quantum states and different measurement basis. Therefore, the first matrix and the second matrix are the same for different output quantum states.

[0085] In this embodiment of the application, the recombined data may further include:

[0086] The third matrix is ​​used to implement the first element and the second element, wherein the first element is an element in the probability storage matrix corresponding to a segmented circuit to be reassembled, and the second element is an element in the first matrix.

[0087] As can be seen from the form of the probability storage matrix, its rows and columns correspond to the input and measurement, respectively. However, when extending its storage format to multi-segment qubits, it cannot be accomplished through a direct product (Kronecker algorithm). This is because the computational order of the probability storage matrix and the first matrix cannot be directly correlated through a simple direct product, although the correspondence with the second matrix can be extended through a direct product. Therefore, before multiplying the probability storage matrix with the first matrix, it is necessary to correlate their elements. Specifically, this can be achieved by first shifting the columns of the probability storage matrix using a third matrix, and then multiplying it with the first matrix, thus realizing the extension to multi-segment qubits.

[0088] In some possible embodiments of this application, the third matrix may include:

[0089]

[0090] Among them, C t Let I be the third matrix, I be the identity matrix, and t be the number of cut points on the timeline that correspond to two adjacent segments to be reassembled.

[0091] In quantum circuits, one timeline corresponds to one qubit, and t represents the number of cut points on the timeline between two adjacent segments of the circuit to be reassembled, where t represents the combined action of the qubits. Figure 3 For example, the number of cutting points is 1. The cutting points are the cutting points corresponding to the paired triangles between the recombined segmented circuit A and the recombined segmented circuit B. The cutting points corresponding to the triangle on the left side of the recombined segmented circuit A and the triangle on the right side of the recombined segmented circuit B cannot be included in t because they are not cutting points between the recombined segmented circuit A and the recombined segmented circuit B.

[0092] Third matrix C t It has recursive properties, as shown below:

[0093] C1 = I6

[0094]

[0095]

[0096]

[0097]

[0098]

[0099] The following explanation uses the matrix form corresponding to Swap6 as an example. Swap means shifting the odd-numbered columns to the front and the even-numbered columns to the back of the corresponding dimension of the square matrix:

[0100]

[0101] In some possible embodiments of this application, the step of processing the probability storage matrix and the recombination data according to the recombination rule corresponding to the segmented circuit to be reassembled, and obtaining the output result of the original quantum circuit, may include:

[0102] Determine the relationship between the segmented circuits to be reassembled in each group of segmented circuits to be reassembled, and define the reassembly type of each group of segmented circuits to be reassembled.

[0103] Based on the correspondence between the reassembly type and the reassembly rule, determine the reassembly rule corresponding to each group of segmented circuits to be reassembled;

[0104] Based on the determined recombination rules, the corresponding probability storage matrix and recombination data are processed to obtain the output of the original quantum circuit.

[0105] The number of recombined segments in each group can be the same or different. Generally, a group of recombined segments contains at least two adjacent segments. The output of the quantum circuit is related to the evolution sequence of the quantum state within the quantum circuit. Recombining adjacent segments ensures the correct output. The grouping method can be pre-set or generated based on the number of segments to be recombined. For example, the original quantum circuit is cut into A, B, C, D, E, and F. One grouping method is (A, B), (C, D), and (E, F). After A and B recombine to obtain G, C and D recombine to obtain H, and E and F recombine to obtain J, G, H, and J can be used as a group of recombined segments. Recombining G, H, and J yields the output of the original quantum circuit. Another grouping method is to first group A and B together to obtain G, then group G and C together to obtain L, and so on, to obtain the output of the original quantum circuit.

[0106] The relationship between the segments to be reassembled can be obtained by traversing the original quantum circuit marked with cutting point information, or it can be determined by the identification information generated by cutting the original quantum circuit according to the cutting point. The identification information can be the identification information for a segment to be reassembled, which indicates the relationship between the segment to be reassembled and other segment to be reassembled; or the identification information can be the identification information for a cutting point, which indicates the relationship between the two segments to be reassembled corresponding to the cutting point.

[0107] In some possible embodiments of this application, determining the reassembly rule corresponding to each group of segmented circuits to be reassembled based on the correspondence between reassembly type and reassembly rule includes:

[0108] When the recombination type is sequential recombination, the recombination rules corresponding to sequential recombination include:

[0109]

[0110] in, These are the probability storage matrices corresponding to segment A and segment B in a set of segmented circuits to be reassembled, respectively. R Let U be the first matrix. L This is the second matrix;

[0111] When the recombination type is an embedded recombination, the recombination rules corresponding to the sequential recombination include:

[0112]

[0113] Among them, the segmented circuit A to be reassembled and the segmented circuit B to be reassembled are embedded.

[0114] In the embodiments of this application, matrixing the reassembly operation can reduce the number of multiplication / addition operations between data corresponding to a large number of segments to be reassembled, thereby reducing a large amount of data processing complexity and greatly improving the efficiency of data reassembly.

[0115] Taking a set of two segmented circuits to be reassembled as an example, such as... Figure 3 As shown, the segments to be reassembled are sequentially related, therefore the reassembly type is sequential reassembly. t It is used for normalization in sequential recombination. Using the sequential recombination rules, the probability storage matrix, the first matrix, the second matrix, and the third matrix are recombined to obtain a matrix that conforms to the probability storage matrix structure, that is, to obtain the probability storage matrix of the new segmented circuit.

[0116] Figure 5 This is a schematic diagram of the segmented circuits to be reassembled with an embedded relationship. Because segmented circuits A (divided into A1 and A2) and B are embedded, a trace operation is required. The first cut point can be reassembled according to the sequential reassembly rules, or the second cut point can be reassembled sequentially first. Then, a new matrix is ​​obtained through the first, second, and third matrices. For both reassembly methods, the order of segmented circuits A and B in the reassembly rules changes.

[0117] In some possible embodiments of this application, the method may further include:

[0118] When there is a segmented circuit in a set of circuits to be reassembled where the number of input points is not equal to the number of output points, in addition to cutting the qubits, a new cutting qubit is determined in the segmented circuit to be reassembled, and a new cutting point is set on the new cutting qubit.

[0119] For a segmented circuit to be reassembled where the number of output points and input points differs, to adapt to the probabilistic storage matrix format, new cutting points need to be added to the circuit where the number of input points is not equal to the number of output points. These new cutting qubits are those that do not operate on quantum logic gates or act as unit operators in subsequent execution sequences; that is, the timeline corresponding to this qubit in the subsequent execution sequence corresponds to the I-channel. For example... Figure 6 As shown, before adding new cut points, the number of input points in the segmented circuit A to be reassembled is 2, which are two triangles pointing left from the left vertex. The number of output points is 1, which is a triangle pointing right from the right vertex between the segmented circuit A and the segmented circuit B to be reassembled. The dashed box shows the newly added cut points in the segmented circuit A to be reassembled. The subsequent additional cut points and the segmented circuit B to be reassembled are made to correspond to the above sequential reassembly rules. The timeline obtained by the cut corresponds to an I channel, and its probability matrix is ​​very simple. By performing a direct product with the probability matrix of the segmented circuit B to be reassembled, the decomposition of the segmented circuit B to be reassembled into a higher dimension can be obtained.

[0120] See Figure 7 , Figure 7 This is a schematic diagram of the structure of a data processing device provided in an embodiment of this application, and... Figure 2 Corresponding to the process shown, the apparatus includes:

[0121] The module 701 is used to obtain the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled. The segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point. The probability storage matrix consists of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled. The output quantum states are the quantum states evolved from different input quantum states by the corresponding segmented circuit to be reassembled. The measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases. The segmented qubits are the qubits with cutting points on the corresponding timeline.

[0122] The processing module 702 is used to process the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuits to be recombined, and obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0123] In some possible implementations of this application, the reconstructed data may include:

[0124] A first matrix composed of first coefficients, wherein the first coefficients are the coefficients of the decomposition of an output quantum state of a cut qubit on each measurement basis;

[0125] A second matrix consisting of second coefficients, where the second coefficients are the coefficients of different input quantum states of a cut qubit through a corresponding output quantum state.

[0126] In some possible embodiments of this application, the recombined data may further include:

[0127] The third matrix is ​​used to implement the first element and the second element, wherein the first element is an element in the probability storage matrix corresponding to a segmented circuit to be reassembled, and the second element is an element in the first matrix.

[0128] In some possible embodiments of this application, the third matrix may include:

[0129]

[0130] Among them, C t Let I be the third matrix, I be the identity matrix, and t be the number of cut points on the timeline that correspond to two adjacent segments to be reassembled.

[0131] In some possible embodiments of this application, the processing module 702 may include:

[0132] The first determining unit is used to determine the relationship between the segmented circuits to be reassembled in each group of segmented circuits to be reassembled, and to determine the reassembly type of each group of segmented circuits to be reassembled.

[0133] The second determining unit is used to determine the reorganization rule corresponding to each group of segmented circuits to be reorganized based on the correspondence between reorganization type and reorganization rule.

[0134] The processing unit is used to process the corresponding probability storage matrix and recombination data according to the determined recombination rules to obtain the output of the original quantum circuit.

[0135] In some possible embodiments of this application, the processing unit may be specifically used for:

[0136] When the recombination type is sequential recombination, the recombination rules corresponding to sequential recombination include:

[0137]

[0138] in, These are the probability storage matrices corresponding to segment A and segment B in a set of segmented circuits to be reassembled, respectively.R Let U be the first matrix. L This is the second matrix;

[0139] When the recombination type is an embedded recombination, the recombination rules corresponding to the sequential recombination include:

[0140]

[0141] Among them, the segmented circuit A to be reassembled and the segmented circuit B to be reassembled are embedded.

[0142] In some possible embodiments of this application, the apparatus may further include:

[0143] The determination module is used to determine new cutting qubits in a group of segmented circuits to be reassembled, in addition to cutting qubits, and to set new cutting points on the new cutting qubits when there are segmented circuits to be reassembled with the number of input points not equal to the number of output points.

[0144] As can be seen, this embodiment first obtains the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, and then processes the probability storage matrix and the recombination data according to the recombination rules corresponding to the segmented circuit to be reassembled to obtain the output result of the original quantum circuit. The probability storage matrix can contain all probabilities corresponding to the segmentation of qubits. Based on the operation of the probability storage matrix and the recombination data, the recombination result can be obtained. Compared with calculating one by one, this application uses matrix operation to realize the overall operation on the data corresponding to the segmented circuit to be reassembled, which efficiently utilizes computing power and thus improves the efficiency of data recombination.

[0145] This application also provides a quantum-supercomputer collaborative operating system, which runs on a quantum computer including a quantum processor and / or a supercomputer including a classical processor, for processing data according to the method described in the method-side embodiment of this application.

[0146] This application also provides a storage medium storing a computer program, wherein the computer program is configured to implement the steps in any of the above method embodiments when running.

[0147] Specifically, in this embodiment, the storage medium can be configured to store a computer program for implementing the following steps:

[0148] S201: Obtain the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, wherein the segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point, the probability storage matrix is ​​composed of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled, the output quantum states are the quantum states after different input quantum states have evolved through the corresponding segmented circuit to be reassembled, the measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases, and the segmented qubits are the qubits with cutting points on the corresponding timeline;

[0149] S202: Based on the recombination rules corresponding to the segmented circuits to be recombined, process the probability storage matrix and the recombination data to obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0150] This application also provides an electronic device, including a memory and a processor, wherein the memory stores a computer program, and the processor is configured to run the computer program to implement the steps in any of the above method embodiments.

[0151] Specifically, the aforementioned electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the aforementioned processor, and the input / output device is connected to the aforementioned processor.

[0152] Specifically, in this embodiment, the processor described above can be configured to implement the following steps via a computer program:

[0153] S201: Obtain the probability storage matrix and recombination data corresponding to the segmented circuit to be reassembled, wherein the segmented circuit to be reassembled is obtained by cutting the original quantum circuit according to a preset cutting point, the probability storage matrix is ​​composed of the measurement probabilities corresponding to the output quantum states of the segmented circuit to be reassembled, the output quantum states are the quantum states after different input quantum states have evolved through the corresponding segmented circuit to be reassembled, the measurement probabilities are the probabilities obtained by measuring the evolved segmented qubits on different measurement bases, and the segmented qubits are the qubits with cutting points on the corresponding timeline;

[0154] S202: Based on the recombination rules corresponding to the segmented circuits to be recombined, process the probability storage matrix and the recombination data to obtain the output result of the original quantum circuit, wherein the recombination rules are determined by the relationship between the segmented circuits to be recombined in the original quantum circuit.

[0155] This specification also provides a computer program product containing instructions that, when executed by a computer, cause the computer to perform the data processing method described in any of the above embodiments.

[0156] It is understood that the specific examples in this specification are only intended to help those skilled in the art better understand the implementation methods described herein, and are not intended to limit the scope of the invention.

[0157] It is understood that in the various embodiments of this specification, the sequence number of each process does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not limit the implementation process of the embodiments of this specification in any way.

[0158] It is understood that the various implementation methods described in this specification can be implemented individually or in combination, and the implementation methods in this specification are not limited in this respect.

[0159] Unless otherwise stated, all technical and scientific terms used in the embodiments of this specification have the same meaning as commonly understood by one of ordinary skill in the art. The terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the scope of this specification. The term "and / or" as used in this specification includes any and all combinations of one or more of the associated listed items. The singular forms "a," "the," and "the" as used in the embodiments of this specification and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0160] It is understood that the processor in the embodiments of this specification can be an integrated circuit chip with signal processing capabilities. In implementation, each step of the above method embodiments can be completed by integrated logic circuits in the processor's hardware or by instructions in software form. The processor can be a general-purpose processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It can implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of this specification. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of this specification can be directly implemented by a hardware decoding processor, or by a combination of hardware and software modules in the decoding processor. The software modules can reside in random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or other mature storage media in the art. This storage medium is located in memory; the processor reads information from the memory and, in conjunction with its hardware, completes the steps of the above methods.

[0161] It is understood that the memory in the embodiments of this specification may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. Non-volatile memory may be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may be random access memory (RAM). It should be noted that the memory in the systems and methods described herein is intended to include, but is not limited to, these and any other suitable types of memory.

[0162] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this specification.

[0163] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes of the systems, devices, and units described above can be referred to the corresponding processes in the aforementioned method implementations, and will not be repeated here.

[0164] In the several embodiments provided in this specification, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be electrical, mechanical, or other forms.

[0165] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment, depending on actual needs.

[0166] In addition, the functional units in the various embodiments of this specification can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0167] If the aforementioned functions are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solutions of this specification, in essence, or the parts that contribute to the prior art, or parts of the technical solutions, can be embodied in the form of software products. These computer software products are stored in a storage medium and include several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this specification. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0168] The above description is merely a specific embodiment of this specification, but the scope of protection of this invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this specification should be included within the scope of protection of this specification. Therefore, the scope of protection of this invention should be determined by the scope of the claims.

Claims

1. A data processing method, characterized by, The method comprises: obtaining a probability storage matrix corresponding to a to-be-recombined segmented circuit and recombination data, wherein the to-be-recombined segmented circuit is obtained by cutting an original quantum circuit according to a preset cutting point, the probability storage matrix is composed of measurement probabilities corresponding to output quantum states of the to-be-recombined segmented circuit, the output quantum states are quantum states evolved from different input quantum states by the corresponding to-be-recombined segmented circuit, and the measurement probabilities are probabilities obtained by measuring the evolved cutting quantum bits on different measurement bases, the cutting quantum bits are quantum bits with the cutting point on the corresponding time line; wherein the recombination data comprises a first matrix composed of first coefficients, a second matrix composed of second coefficients, and a third matrix for implementing first elements and second elements; the first coefficient is a coefficient of a decomposition amount of one output quantum state of one cutting quantum bit on each measurement base; the second coefficient is a coefficient of one output quantum state of one cutting quantum bit corresponding to different input quantum states; the first element is an element in the probability storage matrix corresponding to one to-be-recombined segmented circuit, and the second element is an element in the first matrix; According to a reorganization rule corresponding to the to-be-reorganized segmented circuit, processing the probability storage matrix and the reorganization data to obtain an output result of the original quantum circuit, wherein when a relationship between to-be-reorganized segmented circuits in a group of to-be-reorganized segmented circuits is sequential reorganization, the reorganization rule corresponding to the sequential reorganization includes: ; wherein, , are probability storage matrices corresponding to to-be-reorganized segmented circuit A and to-be-reorganized segmented circuit B in a group of to-be-reorganized segmented circuits, is a first matrix, is a second matrix, is a third matrix, is a number of cutting points on a timeline commonly corresponding to two adjacent to-be-reorganized segmented circuits.

2. The method of claim 1, wherein, the third matrix comprises wherein is the identity matrix.

3. The method of claim 1, wherein, when the relationship between the to-be-recombined segmented circuits in a group of to-be-recombined segmented circuits is an embedded recombination, the recombination rule corresponding to the embedded recombination comprises: wherein the to-be-recombined segmented circuit A and the to-be-recombined segmented circuit B are in an embedded relationship.

4. The method of claim 1, wherein, The method further comprises: when there is a to-be-recombined segmented circuit with an unequal number of input points and output points in a group of to-be-recombined segmented circuits, determining a new cutting quantum bit in the to-be-recombined segmented circuit except the cutting quantum bit, and setting a new cutting point on the new cutting quantum bit.

5. A data processing apparatus, characterized by, The device comprises: an obtaining module, configured to obtain a probability storage matrix corresponding to a to-be-recombined segmented circuit and recombination data, wherein the to-be-recombined segmented circuit is obtained by cutting an original quantum circuit according to a preset cutting point, the probability storage matrix is composed of measurement probabilities corresponding to output quantum states of the to-be-recombined segmented circuit, the output quantum states are quantum states evolved from different input quantum states by the corresponding to-be-recombined segmented circuit, and the measurement probabilities are probabilities obtained by measuring the evolved cutting quantum bits on different measurement bases, the cutting quantum bits are quantum bits with the cutting point on the corresponding time line; wherein the recombination data comprises a first matrix composed of first coefficients, a second matrix composed of second coefficients, and a third matrix for implementing first elements and second elements; the first coefficient is a coefficient of a decomposition amount of one output quantum state of one cutting quantum bit on each measurement base; the second coefficient is a coefficient of one output quantum state of one cutting quantum bit corresponding to different input quantum states; the first element is an element in the probability storage matrix corresponding to one to-be-recombined segmented circuit, and the second element is an element in the first matrix; The processing module is configured to process the probability storage matrix and the reorganization data according to a reorganization rule corresponding to the to-be-reorganized segmented circuit, and obtain an output result of the original quantum circuit, wherein when a relationship between to-be-reorganized segmented circuits in a group of to-be-reorganized segmented circuits is sequential reorganization, the reorganization rule corresponding to the sequential reorganization includes: ; wherein, , are probability storage matrices corresponding to to-be-reorganized segmented circuit A and to-be-reorganized segmented circuit B in a group of to-be-reorganized segmented circuits, is a first matrix, is a second matrix, is a third matrix, is the number of cutting points on a timeline commonly corresponding to two adjacent to-be-reorganized segmented circuits.

6. A quantity super-synergetic operating system, characterized in that, The super-collaborative operating system realizes data processing according to the method in any one of claims 1 to 4.

7. A storage medium, characterized by The storage medium stores a computer program, and the computer program is configured to implement the method in any one of claims 1 to 4 when executed. 8.An electronic device comprising a memory and a processor, the electronic device comprising: The memory stores a computer program, and the processor is configured to execute the computer program to implement the method in any one of claims 1 to 4.

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