Quantum hardware resource virtualization method and device, electronic equipment and storage medium

Abstract

The embodiment of the invention provides a quantum hardware resource virtualization method and device, electronic equipment and a storage medium. The method comprises the following steps: acquiring a target quantum bit unit topology for a target quantum computing task; obtaining a quantum bit unit network in the quantum hardware resource; in the quantum bit unit network, obtaining a plurality of candidate quantum bit unit sub-networks conforming to the target quantum bit unit topology; based on the self-operation fidelity of each quantum bit unit in the candidate quantum bit unit sub-network and the mutual operation fidelity between adjacent quantum bit units, determining the overall operation fidelity of the candidate quantum bit unit sub-network; and based on the overall operation fidelity, determining a target quantum bit unit sub-network as a virtualization resource for the target quantum computing task. According to the embodiment of the invention, the utilization rate of virtualized resources is improved, and relatively high operation accuracy is ensured. The embodiment of the invention can be applied to various scenes such as quantum calculation and superconducting quantum calculation.

Description

Technical Field

[0001] The present disclosure relates to the field of quantum technology, and in particular to a quantum hardware resource virtualization method, device, electronic device and storage medium. Background Art

[0002] In quantum hardware, quantum bits are stored in quantum bit units as the basic unit to complete quantum computing. When performing multiple tasks, in order to perform multiple tasks simultaneously, it is often similar to classical computing, and the quantum chip needs to be divided into multiple virtual machines or multiple processes need to be run simultaneously to perform multiple tasks. Quantum computing is different from classical computing. The operation of quantum computing itself is often inseparable from the quantum bit unit network that supports its underlying operation. The quantum bit unit network structure obtained by arbitrary virtualization may not be sufficient to support the required quantum operations, so the underlying quantum hardware resources often cannot be arbitrarily virtualized.

[0003] The quantum hardware resource virtualization of related technologies generally adopts a simple physical segmentation method. For example, the quantum hardware resources are divided into two parts, namely virtualized quantum hardware resource A and virtualized quantum hardware resource B. When executing task 1, virtualized quantum hardware resource A is started, and when executing task 2, virtualized quantum hardware resource B is started. This simple segmentation method may waste quantum hardware resources and may not guarantee that the virtualized quantum hardware resources allocated can accurately execute quantum tasks.

[0004] The disadvantages of related technologies are that the resource utilization rate of quantum hardware resources is low and the calculation accuracy is difficult to guarantee. Summary of the invention

[0005] The embodiments of the present disclosure provide a quantum hardware resource virtualization method, device, electronic device, and storage medium, which improve the utilization rate of virtualized resources and ensure high calculation accuracy.

[0006] According to one aspect of the present disclosure, a method for virtualizing quantum hardware resources is provided, comprising:

[0007] Obtaining a target quantum bit unit topology for a target quantum computing task;

[0008] Obtain the quantum bit unit network in the quantum hardware resource;

[0009] In the qubit unit network, a plurality of candidate qubit unit subnetworks that conform to the target qubit unit topology are obtained;

[0010] Determining the overall operational fidelity of the candidate qubit unit subnetwork based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operational fidelity between adjacent qubit units;

[0011] Based on the overall operational fidelity of the plurality of candidate quantum bit unit subnetworks, a target quantum bit unit subnetwork is determined as a virtualized resource for the target quantum computing task.

[0012] According to one aspect of the present disclosure, a quantum hardware resource virtualization device is provided, comprising:

[0013] A first acquisition unit, used to acquire a target quantum bit unit topology for a target quantum computing task;

[0014] A second acquisition unit, used to acquire a quantum bit unit network in a quantum hardware resource;

[0015] A third acquisition unit is used to acquire, in the quantum bit unit network, a plurality of candidate quantum bit unit sub-networks that conform to the target quantum bit unit topology;

[0016] A first determining unit, configured to determine the overall operation fidelity of the candidate quantum bit unit subnetwork based on the self-operation fidelity of each quantum bit unit in the candidate quantum bit unit subnetwork and the mutual operation fidelity between adjacent quantum bit units;

[0017] The second determination unit is used to determine a target quantum bit unit subnetwork as a virtualized resource for the target quantum computing task based on the overall operational fidelity of the plurality of candidate quantum bit unit subnetworks.

[0018] Optionally, the first determining unit is specifically configured to:

[0019] Obtaining a first weight of the self-operation fidelity and a second weight of the mutual operation fidelity;

[0020] Based on the first weight and the second weight, a weighted sum is performed on the self-operation fidelity and the mutual operation fidelity to obtain the overall operation fidelity.

[0021] Optionally, the first determining unit is further configured to:

[0022] Obtaining a task type of the target quantum computing task;

[0023] Based on the task type, a preset mapping relationship between the task type and the weight is searched to obtain the first weight and the second weight.

[0024] Optionally, the target quantum bit unit topology is a universal quantum bit unit topology; and the first acquisition unit is specifically used to:

[0025] Acquire a plurality of sample quantum computing tasks, wherein the plurality of sample quantum computing tasks include the target quantum computing task;

[0026] Acquire a plurality of sample quantum bit unit topologies for a plurality of the sample quantum computing tasks;

[0027] The union of multiple sample quantum bit unit topologies is taken to obtain the universal quantum bit unit topology.

[0028] Optionally, the second acquiring unit is specifically configured to:

[0029] Acquire original quantum bit units in a quantum hardware resource, and a first connection relationship between the original quantum bit units;

[0030] Obtaining occupied quantum bit units;

[0031] Acquire a second connection relationship between the occupied qubit units and between the occupied qubit unit and an adjacent qubit unit;

[0032] The occupied quantum bit unit is removed from the original quantum bit unit, and the second connection relationship is removed from the first connection relationship to obtain the quantum bit unit network.

[0033] Optionally, the target quantum bit unit topology includes a first number of quantum bit units; and the third acquisition unit is specifically configured to:

[0034] Traversing the qubit unit network to obtain a plurality of post-screening qubit unit sub-networks, the post-screening qubit unit sub-networks comprising the first number of connected qubit units;

[0035] The third connection relationship between the quantum bit units in the target quantum bit unit topology is compared with the fourth connection relationship between the quantum bit units in each of the screened quantum bit unit sub-networks to determine a plurality of candidate quantum bit unit sub-networks from the plurality of screened quantum bit unit sub-networks.

[0036] Optionally, the second determining unit is specifically configured to:

[0037] Determining an overall failure rate of the candidate qubit unit subnetwork based on the failure rate of each of the qubit units in the candidate qubit unit subnetwork;

[0038] A target quantum bit unit sub-network is determined based on the overall operational fidelity and the overall failure rate of the plurality of candidate quantum bit unit sub-networks.

[0039] Optionally, the second determining unit is specifically configured to:

[0040] Obtaining the importance of the target quantum computing task;

[0041] determining a fidelity level corresponding to the importance;

[0042] The candidate quantum bit unit subnetwork whose overall operation fidelity belongs to the fidelity level among the multiple candidate quantum bit unit subnetworks is determined as the target quantum bit unit subnetwork.

[0043] Optionally, the number of the target quantum computing tasks is a second number, and the number of the candidate quantum bit unit subnetworks is a third number, wherein the second number is less than the third number; and the second determining unit is specifically configured to:

[0044] sorting the third number of candidate quantum bit unit sub-networks according to the overall operational fidelity;

[0045] The first second number of the candidate quantum bit unit sub-networks in the sorting are determined as the second number of the target quantum bit unit sub-networks for the second number of the target quantum computing tasks.

[0046] Optionally, the target quantum computing task is a second number of the associated target quantum computing tasks, and the candidate quantum bit unit subnetwork is a third number of the candidate quantum bit unit subnetwork, wherein the second number is less than the third number;

[0047] Optionally, the second determining unit is specifically configured to:

[0048] Traversing the third number of the candidate quantum bit unit sub-networks to obtain a plurality of candidate sub-network combinations, wherein the candidate sub-network combinations include the second number of the candidate quantum bit unit sub-networks;

[0049] Determining the sum of the overall operational fidelity of a second number of the candidate qubit unit sub-networks in the candidate sub-network combination;

[0050] Determining the concentration of a second number of the candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0051] Based on the sum and the concentration of the plurality of candidate sub-network combinations, a target sub-network combination is determined from the plurality of candidate sub-network combinations as a second number of the target quantum bit unit sub-networks for a second number of the target quantum computing tasks.

[0052] Optionally, the second determining unit is further configured to:

[0053] Determine the center point distances between two of the second number of candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0054] The reciprocal of the average distance of the center point distance is determined as the concentration of the second number of the candidate quantum bit unit sub-networks.

[0055] According to one aspect of the present disclosure, an electronic device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor implements the above-mentioned quantum hardware resource virtualization method when executing the computer program.

[0056] According to one aspect of the present disclosure, a computer-readable storage medium is provided, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the method for virtualizing quantum hardware resources as described above is implemented.

[0057] According to one aspect of the present disclosure, a computer program product is provided. The computer program product includes a computer program. The computer program is read and executed by a processor of a computer device, so that the computer device executes the quantum hardware resource virtualization method as described above.

[0058] In the disclosed embodiment, when quantum hardware resources are needed to perform a quantum computing task, based on the quantum computing task, the target quantum bit topology is first determined, and then multiple candidate quantum bit unit subnetworks that conform to the target quantum bit unit topology are obtained in the quantum bit unit network in the quantum hardware resources. In this way, any candidate quantum bit unit subnetwork can be used as a network for performing quantum computing tasks, and the topological structure of the candidate quantum bit unit subnetwork is relatively reasonable, which improves the adaptability of virtualized quantum hardware resources and quantum computing tasks, thereby improving resource utilization. Then, based on the self-operation fidelity of each quantum bit unit in the candidate quantum bit unit subnetwork and the mutual operation fidelity between adjacent quantum bit units, the overall operation fidelity of the candidate quantum bit unit subnetwork is determined, and based on the overall operation fidelity of multiple candidate quantum bit unit subnetworks, the target quantum bit unit subnetwork is determined as a virtualized resource for the target quantum computing task. In this way, the target quantum bit unit subnetwork has a high overall operation fidelity, which can ensure the operation accuracy of the target quantum bit unit subnetwork in performing quantum computing tasks. In summary, the embodiments of the present disclosure can improve the adaptability of virtualized quantum hardware resources and quantum computing tasks, increase resource utilization, and ensure higher computing accuracy.

[0059] Other features and advantages of the present disclosure will be described in the following description, and partly become apparent from the description, or understood by practicing the present disclosure. The purpose and other advantages of the present disclosure can be realized and obtained by the structures particularly pointed out in the description, claims and drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] The accompanying drawings are used to provide further understanding of the technical solution of the present disclosure and constitute a part of the specification. Together with the embodiments of the present disclosure, they are used to explain the technical solution of the present disclosure and do not constitute a limitation on the technical solution of the present disclosure.

[0061] Figure 1 is an architectural diagram of a quantum computing system to which the quantum hardware resource virtualization method according to an embodiment of the present disclosure is applied;

[0062] Figure 2A-2D is a schematic diagram of an embodiment of the present disclosure applied in a quantum hardware resource virtualization scenario;

[0063] Figure 3 is a flow chart of a quantum hardware resource virtualization method according to an embodiment of the present disclosure;

[0064] Figure 4A-4D yes Figure 3 A schematic diagram of step 310 in FIG. 1 regarding a target quantum bit unit topology;

[0065] Figure 5 yes Figure 3 Step 310 in the flowchart is about the target qubit unit topology being a universal qubit unit topology;

[0066] Figure 6 It is a specific implementation diagram of inducing the universal quantum bit unit topology from multiple sample quantum computing tasks;

[0067] Figure 7 yes Figure 3 Step 320 in the flowchart for obtaining a quantum bit unit network;

[0068] Figure 8A-8C It is a schematic diagram of the specific implementation of obtaining a quantum bit unit network;

[0069] Fig. 9 yes Figure 3 Step 330 in the flowchart for obtaining multiple candidate quantum bit unit sub-networks;

[0070] Fig.10 It is a specific implementation diagram for obtaining multiple candidate quantum bit unit sub-networks;

[0071] Fig.11 yes Figure 3Step 340 in the flowchart for obtaining the overall operation fidelity;

[0072] Fig.12 It is a specific implementation diagram for obtaining overall computational fidelity;

[0073] Fig.13 yes Figure 3 Step 350 in the flowchart of determining a target qubit unit sub-network using the overall failure rate;

[0074] Fig.14 It is a schematic diagram of a specific implementation of determining a target quantum bit unit sub-network using the overall failure rate;

[0075] Fig.15 yes Figure 3 A flowchart of step 350 of determining a target qubit unit subnetwork using importance;

[0076] Fig.16 It is a schematic diagram of a specific implementation of using importance to determine the target quantum bit unit sub-network;

[0077] Fig.17 yes Figure 3 Step 350 in the flowchart is a flowchart for determining a target quantum bit unit sub-network for a second number of target quantum computing tasks;

[0078] Fig.18 is a specific implementation schematic diagram of determining a target quantum bit unit subnetwork for a second number of target quantum computing tasks;

[0079] Fig.19 yes Figure 3 Step 350 in the flowchart is a flowchart for determining a target quantum bit unit sub-network for an associated second number of target quantum computing tasks;

[0080] Figure 20A-20C is a specific implementation schematic diagram of determining a target quantum bit unit subnetwork for an associated second number of target quantum computing tasks;

[0081] Fig.21 is a detailed diagram of the implementation of the quantum hardware resource virtualization method of the disclosed embodiment;

[0082] Fig. 22 is a module diagram of a quantum hardware resource virtualization device according to an embodiment of the present disclosure;

[0083] Fig.23 According to the embodiment of the present disclosure, Figure 3 The terminal structure diagram of the typesetting processing method shown;

[0084] Fig.24 According to the embodiment of the present disclosure, Figure 3 The server structure diagram of the typesetting processing method shown. DETAILED DESCRIPTION

[0085] In order to make the purpose, technical solution and advantages of the present disclosure more clear, the present disclosure is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present disclosure and are not used to limit the present disclosure.

[0086] Before further describing the embodiments of the present disclosure in detail, the nouns and terms involved in the embodiments of the present disclosure are described. The nouns and terms involved in the embodiments of the present disclosure are subject to the following interpretations:

[0087] Quantum computing: Quantum computing is a computing method designed using the principles of quantum mechanics. The biggest difference between it and traditional computing is that it uses quantum bits (qubits) instead of traditional binary bits (bits) for calculations. Quantum bits have different characteristics from traditional binary bits, the most important of which is that they can be in multiple states at the same time. It is precisely because quantum bits can represent two states at the same time and carry more information that more data operations can be completed with the same number of quantum bit units than classical computing. Therefore, quantum computing greatly improves computer processing speed.

[0088] Quantum: The quantum in “quantum computing” refers to the smallest discrete unit a system can use to compute an output.

[0089] Quantum bit: It is the basic unit of information in quantum computing. The role played by quantum bits in quantum computing is similar to that played by bits in traditional computing, but their behavior is very different. Classical bits are binary and can only store 0 or 1, but quantum bits can store the superposition of all possible states, that is, the superposition of state |0> and state |1>, thus greatly improving computer processing speed.

[0090] Quantum bit unit: A storage unit in quantum hardware resources used to hold quantum bits that participate in calculations.

[0091] System architecture and scenario description of the application of the embodiments of the present disclosure

[0092] Figure 1 The diagram is a schematic diagram of a quantum computing system used in a quantum hardware resource virtualization method according to an embodiment of the present disclosure. The quantum computing system includes a browser, a client, a quantum application, a quantum operating system, quantum hardware resources, and the like.

[0093] Browsers and clients are executable programs used to generate quantum computing tasks. Browsers and clients generally run on terminals. Terminals include desktop computers, laptops, tablet computers, PDAs (personal digital assistants), mobile phones, car terminals, and other forms.

[0094] Quantum applications are deployed on quantum operating systems. The API in quantum applications is used to receive quantum computing tasks. The task distribution system in quantum applications is used to distribute quantum computing tasks to quantum operating systems. The quantum simulator in quantum applications can simulate the quantum computing of tasks.

[0095] The quantum operating system (Qubit Operating System, QOS) is generally deployed in the cloud. The quantum operating system is generally installed on quantum hardware resources. The quantum operating system includes an intermediate representation, a quantum just-in-time compiler, a quantum cabin, resource configuration, isolation security, and resource checking. The intermediate representation is used as a common interface between quantum applications and quantum operating systems, and can serve as an abstract representation of quantum computing tasks. The quantum just-in-time compiler (also known as quantum JIT, Just In Time) includes a task acquisition model and a topology compilation model. The task scheduling model is used to perform task scheduling. The topology compilation model is used to compile the scheduled tasks to obtain the quantum bit unit topology. The quantum cabin includes a checker and a database. The checker is used to check quantum computing tasks. The database is used to store data of quantum computing tasks, such as the quantum bit unit topology corresponding to the quantum computing task. Resource configuration is used to allocate virtualized resources for quantum computing tasks. Isolation security is used for data isolation and data security between the quantum operating system and quantum hardware resources. Resource checking is used to check quantum hardware resources for quantum computing tasks.

[0096] Quantum hardware resources are the physical space where quantum computing is located. Quantum hardware resources are generally deployed in the cloud. Figure 1 As shown, the quantum hardware resource includes a quantum processing unit 1 (QPU1) and a quantum processing unit 2 (QPU2). A quantum processing unit is a relatively physically independent hardware block in the quantum hardware resource. It should be understood by those skilled in the art that quantum processing unit 1 (QPU1) and quantum processing unit 2 (QPU2) are only examples, and the number of quantum processing units may also be other numbers.

[0097] When a browser or client generates a task that requires quantum computing, the task is first sent to the task scheduling model of the quantum operating system through the task distribution system in the quantum application. The quantum simulator in the quantum application can simulate the quantum computing of the task. In the quantum operating system, the task is scheduled by the task scheduling model, and the task is compiled by the topology compilation model to compile the quantum bit unit topology suitable for executing the task. A large number of quantum bit units are distributed in the quantum hardware resources. Adjacent quantum bit units are connected through the action of radio frequency beams to form an overall quantum bit unit network. The quantum hardware resources are virtualized to obtain virtualized resources for quantum computing tasks.

[0098] The embodiments of the present disclosure can be applied in various scenarios, such as Figure 2A-2D The quantum hardware resource virtualization scenario shown.

[0099] like Figure 2A As shown, quantum computing tasks A and B require virtualized resources, so the quantum hardware resources are virtualized. The quantum hardware resources include 12 qubit units. There is a connection relationship between qubit unit 1 and qubit unit 2. There is a connection relationship between qubit unit 2 and qubit unit 3. There is a connection relationship between qubit unit 3 and qubit unit 4. There is a connection relationship between qubit unit 4 and qubit unit 5. There is a connection relationship between qubit unit 5 and qubit unit 6. There is a connection relationship between qubit unit 6 and qubit unit 7. There is a connection relationship between qubit unit 7 and qubit unit 8. There is a connection relationship between qubit unit 8 and qubit unit 9. There is a connection relationship between qubit unit 9 and qubit unit 10. There is a connection relationship between qubit unit 10 and qubit unit 11. There is a connection relationship between qubit unit 11 and qubit unit 12. There is a connection relationship between qubit unit 1 and qubit unit 12. There is a connection relationship between qubit unit 2 and qubit unit 11. There is a connection relationship between qubit unit 3 and qubit unit 10. There is a connection relationship between qubit unit 4 and qubit unit 9. There is a connection relationship between qubit unit 5 and qubit unit 8.

[0100] The quantum bit unit topology of quantum computing task A is 4 quantum bit units connected end to end, and the quantum bit unit topology of quantum computing task B is 3 quantum bit units connected in a single chain. The quantum hardware resources are divided based on the quantum bit unit topology of these two tasks. Figure 2A The two dotted lines in the figure divide the overall quantum hardware resources into virtualized resources z1, virtualized resources z2, and virtualized resources z3. Figure 2B shown.

[0101] exist Figure 2B In the example, virtualized resource z1 includes qubit unit 1, qubit unit 2, qubit unit 11, and qubit unit 12, for a total of 4 qubit units. Virtualized resource z2 includes qubit unit 3, qubit unit 4, qubit unit 9, and qubit unit 10, for a total of 4 qubit units. Virtualized resource z3 includes qubit unit 5, qubit unit 6, qubit unit 7, and qubit unit 8, for a total of 4 qubit units.

[0102] Figure 2B and Figure 2A The difference is that there is no connection between qubit unit 2 and qubit unit 3. There is no connection between qubit unit 4 and qubit unit 5. There is no connection between qubit unit 8 and qubit unit 9. There is no connection between qubit unit 10 and qubit unit 11.

[0103] Assuming that the computational fidelity of virtualized resource z1 is 0.9, the computational fidelity of virtualized resource z2 is 0.8, and the computational fidelity of virtualized resource z3 is 0.5, it is determined that virtualized resource z1 processes quantum computing task A, and it is determined that virtualized resource z2 processes quantum computing task B. In this way, the computational fidelity of virtualized resources processing quantum computing tasks can be ensured.

[0104] Running quantum computing task A on virtualized resource z1 Figure 2C As shown, the quantum computing task B is run on the virtualized resource z2 as follows Figure 2D It should be noted that the virtualized resource z3 can be used for other quantum computing tasks.

[0105] exist Figure 2C In FIG. 1 , when the virtualized resource z1 processes the quantum computing task A, the quantum computing task A occupies the quantum bit unit 1, the quantum bit unit 2, the quantum bit unit 11, and the quantum bit unit 12. It can be seen that the virtualized resource z1 is fully occupied, and the resource utilization rate is high.

[0106] exist Figure 2D In the example, when virtualized resource z2 processes quantum computing task B, quantum computing task B occupies qubit unit 4, qubit unit 5, and qubit unit 9, leaving qubit unit 8. In this case, only one qubit unit is idle, which shows that the resource utilization rate is also high.

[0107] In summary, when virtualizing quantum hardware resources, the quantum bit unit topology of quantum computing tasks is fully considered, and the adaptability of virtualized quantum hardware resources to quantum computing tasks is improved, thereby improving resource utilization. In addition, the computational fidelity of each segmented virtualized resource is also considered, so that the virtualized resources used for quantum computing tasks have higher computational accuracy.

[0108] General description of the disclosed embodiments

[0109] According to an embodiment of the present disclosure, a quantum hardware resource virtualization method is provided.

[0110] The quantum hardware resource virtualization method of the disclosed embodiment may be executed on a server, or may be executed partially on a server and partially on a terminal.

[0111] like Figure 3 As shown, according to one embodiment of the present disclosure, quantum hardware resource virtualization includes:

[0112] Step 310: Obtain a target quantum bit unit topology for a target quantum computing task;

[0113] Step 320: Obtain a quantum bit unit network in quantum hardware resources;

[0114] Step 330: In the quantum bit unit network, obtain multiple candidate quantum bit unit sub-networks that meet the target quantum bit unit topology;

[0115] Step 340: Determine the overall computational fidelity of the candidate qubit unit subnetwork based on the self-computational fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual computational fidelity between adjacent qubit units;

[0116] Step 350: Based on the overall operational fidelity of multiple candidate quantum bit unit subnetworks, determine a target quantum bit unit subnetwork as a virtualized resource for a target quantum computing task.

[0117] The following is a detailed description of steps 310-330.

[0118] Detailed description of step 310

[0119] In step 310, a target quantum bit unit topology for a target quantum computing task is obtained. The target quantum computing task refers to a task that can trigger a quantum hardware resource virtualization service. The target quantum computing task includes multiple quantum operations. The target quantum bit unit topology refers to a network structure composed of multiple quantum bit units.

[0120] Since multiple quantum computations in the target quantum computing task can be converted into gate operations of each qubit unit and gate operations between adjacent qubit units, the target qubit unit topology is obtained based on the network structure formed by each qubit unit and adjacent qubit units. The target qubit unit topology includes multiple qubit units and the connection relationship between the qubit units.

[0121] It should be noted that quantum bits can represent two states at the same time, such as the "dead" and "alive" of "Schrödinger's cat", but before the box is opened, "Schrödinger's cat" is in a superposition of the two states of "dead" and "alive". Since quantum bits can represent two states at the same time and carry more information, more data operations can be completed with the same number of quantum bit units than classical computing. The state of a quantum bit is a superposition of two states |0> and |1>, with probabilities of α and β respectively. Before the quantum bit is observed, α and β are uncertain values ​​that change randomly, but both satisfy "α 2 +β 2 =1"; when the quantum bit is observed, the values ​​of α and β are determined. Each quantum bit can use a variety of different gate operations.

[0122] Gate operation is also called quantum gate operation or quantum logic gate operation. The more typical gate operations are I, X, Y, and H. The gate operation here is not completed through the gate devices in classical computing, but by applying different RF modulation signals to the quantum bit unit. The RF modulation signal has signals with different components, and each component signal has three variables: amplitude, frequency, and phase. By adjusting the three variables of different components, various gate operations can be completed. For example, the X gate operation is to interchange the probabilities of states |0> and |1>, that is, the probability of state |0> in the quantum bit unit is changed from α to β by adjusting the three variables of different components of the RF signal; the probability of state |1> in the quantum bit unit is changed from β to α by adjusting the three variables of different components of the RF signal. The H gate operation is to change the probability of state |0> from α to β, the probability of state |1> changes from β to

[0123] In one embodiment, step 310 includes:

[0124] Obtain quantum computing tasks for task distribution systems in quantum applications;

[0125] Calling the task scheduling model in the quantum operating system to schedule the target quantum computing task, and obtaining the scheduled target quantum computing task;

[0126] The topology compilation model is called to perform topology compilation on the scheduled target quantum computing task to obtain the target quantum bit unit topology.

[0127] Since quantum applications and quantum operating systems have been described in the system architecture above, they will not be repeated here.

[0128] The benefit of this embodiment is that it fully utilizes the cooperation between quantum applications and quantum operating systems to improve the flexibility and accuracy of obtaining the target quantum bit unit topology.

[0129] Combine the following Figure 4A-4B The target quantum bit unit topology is described in detail.

[0130] In one example, if Figure 4A As shown, the target quantum bit unit topology M1 of the target quantum computing task R1 includes 4 quantum bit units. Specifically, the target quantum computing task R1 includes 7 quantum calculations. These 7 quantum calculations can be converted into gate operations of quantum bit unit 1, gate operations of quantum bit unit 2, gate operations of quantum bit unit 3, gate operations of quantum bit unit 2, gate operations between quantum bit unit 1 and quantum bit unit 2, gate operations between quantum bit unit 2 and quantum bit unit 3, and gate operations between quantum bit unit 4 and quantum bit unit 4. Then, in the target quantum bit unit topology M1, there is a connection relationship between quantum bit unit 1 and quantum bit unit 2, a connection relationship between quantum bit unit 2 and quantum bit unit 3, and a connection relationship between quantum bit unit 3 and quantum bit unit 4.

[0131] In another example, if Figure 4B As shown, the target quantum bit unit topology M2 of the target quantum computing task R2 includes three quantum bit units. In the target quantum bit unit topology M2, there is a connection relationship between quantum bit unit 1 and quantum bit unit 2, and there is a connection relationship between quantum bit unit 1 and quantum bit unit 3.

[0132] In another example, if Figure 4C As shown, the target quantum bit unit topology M3 of the target quantum computing task R3 includes two quantum bit units. In the target quantum bit unit topology M3, there is a connection relationship between the quantum bit unit 1 and the quantum bit unit 2.

[0133] In another example, if Figure 4DAs shown, the target quantum bit unit topology M4 of the target quantum computing task R4 includes 4 quantum bit units. In the target quantum bit unit topology M4, there is a connection relationship between quantum bit unit 1 and quantum bit unit 2, there is a connection relationship between quantum bit unit 2 and quantum bit unit 3, there is a connection relationship between quantum bit unit 3 and quantum bit unit 4, and there is a connection relationship between quantum bit unit 1 and quantum bit unit 4.

[0134] It should be noted that from Figure 4A-4D From the target quantum bit unit topology shown, it can be seen that the number of quantum bit units and the connection relationship between quantum bit units required for different target quantum computing tasks are generally different. It can be seen that the target quantum bit unit topology of a single target quantum computing task is non-universal and cannot be universally applied to other target quantum computing tasks. In view of this, in one embodiment, it is proposed to determine a universal quantum bit unit network structure topology that is basically applicable to most tasks based on the form of the quantum bit unit network structure that is usually occupied by quantum computing tasks.

[0135] Reference Figure 5 In the specific implementation of this embodiment, the target quantum bit unit topology is a universal quantum bit unit topology, and step 310 includes:

[0136] Step 510: Acquire multiple sample quantum computing tasks, wherein the multiple sample quantum computing tasks include a target quantum computing task;

[0137] Step 520: Obtain multiple sample quantum bit unit topologies for multiple sample quantum computing tasks;

[0138] Step 530: Take the union of multiple sample quantum bit unit topologies to obtain a universal quantum bit unit topology.

[0139] The following is a detailed description of steps 510-530.

[0140] In step 510, the sample quantum computing task is similar to the target quantum computing task, and also includes multiple quantum computing, and the sample quantum computing task also has a corresponding quantum bit unit topology. However, the target quantum computing task is used for the practical application of quantum hardware resource virtualization, while the sample quantum computing task is used to summarize the universal quantum bit unit topology. Figure 6 As shown, there are four sample quantum computing tasks, namely, sample quantum computing task Y1, sample quantum computing task Y2, sample quantum computing task Y3, and sample quantum computing task Y4. Among them, sample quantum computing task Y1 is the target quantum computing task.

[0141] In step 520, the sample quantum bit unit topology of the sample quantum computing task can be obtained by calling the topology compilation model. Step 520 is similar to the process of obtaining the target quantum bit unit topology of the target quantum computing task in the above text, and will not be repeated here.

[0142] In step 530, the multiple sample qubit unit topologies are not the same, which actually means that the number of qubit units and the connection relationships between qubit units are different. Therefore, the union of these sample qubit unit topologies is taken, and the obtained universal qubit unit topology includes all qubit units and all connection relationships.

[0143] In one example, if Figure 6 As shown, based on the sample qubit unit topologies of the four sample quantum computing tasks, after taking the union, a universal qubit unit topology is obtained. Specifically, from the sample qubit unit topologies of the sample quantum computing task Y1, the sample quantum computing task Y2, the sample quantum computing task Y3, and the sample quantum computing task Y4, it can be known that the sample qubit units involved include sample qubit unit 1, sample qubit unit 2, sample qubit unit 3, and sample qubit unit 4, a total of four sample qubit units. It can also be known that there is a connection relationship between sample qubit unit 1 and sample qubit unit 2, a connection relationship between sample qubit unit 2 and sample qubit unit 3, and a connection relationship between sample qubit unit 3 and sample qubit unit 4. Finally, we get Figure 6 The universal qubit unit topology is shown on the right. Then, in actual use, if the qubit unit topology of a target quantum computing task is the same as any of the sample quantum computing tasks Y1, Y2, Y3, and Y4, then the universal qubit unit topology is applicable.

[0144] The benefit of this embodiment is that a universal quantum bit unit topology can be summarized based on multiple sample quantum computing tasks, and the universal quantum bit unit topology is applicable to different target quantum computing tasks, thereby improving applicability.

[0145] Detailed description of step 320

[0146] In step 320, a quantum bit unit network in the quantum hardware resources is obtained. A quantum bit unit network refers to a network composed of multiple quantum bit units that can be used as a virtualized resource for quantum computing tasks. In the quantum bit unit network, there are original quantum bit units and a first connection relationship between the original quantum bit units. In fact, the original quantum bit units in the quantum bit unit network may be occupied by other quantum computing tasks, and the occupied original quantum bit units cannot participate in the processing of the target quantum computing task. Therefore, in one embodiment, the occupied quantum bit units should be deleted from the quantum bit unit network.

[0147] Reference Figure 7 In the specific implementation of this embodiment, step 320 includes:

[0148] Step 710: obtaining original quantum bit units in quantum hardware resources and a first connection relationship between the original quantum bit units;

[0149] Step 720, obtaining occupied quantum bit units;

[0150] Step 730: Obtain a second connection relationship between occupied qubit units and between an occupied qubit unit and an adjacent qubit unit;

[0151] Step 740: remove occupied quantum bit units from the original quantum bit units, remove the second connection relationship from the first connection relationship, and obtain a quantum bit unit network.

[0152] In step 710, if Fig. 8A As shown, the original quantum bit units in the quantum hardware resource include {quantum bit unit 1, quantum bit unit 2, quantum bit unit 3, quantum bit unit 4, quantum bit unit 5, quantum bit unit 6, quantum bit unit 7, quantum bit unit 8, quantum bit unit 9, quantum bit unit 10, quantum bit unit 11, quantum bit unit 12}, a total of 12 original quantum bit units. The first connection relationship between the original quantum bit units includes {first connection relationship L 1，2 , the first connection relationship L 2，3 , the first connection relationship L 3，4 , the first connection relationship L 4，5 , the first connection relationship L 5，6 , the first connection relationship L 6，7 , the first connection relationship L 7，8 , the first connection relationship L 8，9 , the first connection relationship L 9，10 , the first connection relationship L 10,11 , the first connection relationship L 11,12 , the first connection relationship L 1，12, the first connection relationship L 2，11 , the first connection relationship L 3,10 , the first connection relationship L 4,9 , the first connection relationship L 5,8}, a total of 16 first connection relationships.

[0153] Continue as Fig. 8A As shown, the first connection relationship corresponding to the quantum bit unit 1 includes the first connection relationship L 1，2 , the first connection relationship L 1，12 The first connection relationship corresponding to the quantum bit unit 2 includes the first connection relationship L 1，2 , the first connection relationship L 2，3 , the first connection relationship L 2，11 The first connection relationship corresponding to the quantum bit unit 3 includes the first connection relationship L 2，3 , the first connection relationship L 3，4 , the first connection relationship L 3，10 The first connection relationship corresponding to the quantum bit unit 4 includes the first connection relationship L 3，4 , the first connection relationship L 4，5 , the first connection relationship L 4，9 The first connection relationship corresponding to the quantum bit unit 5 includes the first connection relationship L 4，5 , the first connection relationship L 5，6 , the first connection relationship L 5，8 The first connection relationship corresponding to the quantum bit unit 6 includes the first connection relationship L 5，6 , the first connection relationship L 6，7 The first connection relationship corresponding to the quantum bit unit 7 includes the first connection relationship L 6，7 , the first connection relationship L 7，8 The first connection relationship corresponding to the quantum bit unit 8 includes the first connection relationship L 5，8 , the first connection relationship L 7，8 , the first connection relationship L 8，9 The first connection relationship corresponding to the quantum bit unit 9 includes the first connection relationship L 4，9 , the first connection relationship L 8，9 , the first connection relationship L 9，10 The first connection relationship corresponding to the quantum bit unit 10 includes the first connection relationship L 3，10 , the first connection relationship L 9，10 , the first connection relationship L 10，11 The first connection relationship corresponding to the quantum bit unit 11 includes the first connection relationship L 2，11 , the first connection relationship L 10，11 , the first connection relationship L 11，12 The first connection relationship corresponding to the quantum bit unit 12 includes the first connection relationship L1，12 , the first connection relationship L 11，12 .

[0154] In step 720, the occupied qubit unit refers to the original qubit unit that is occupied by other tasks or damaged. Figure 8B As shown, among the 12 original quantum bit units of the quantum hardware resource, quantum bit unit 2 and quantum bit unit 10 are occupied quantum bit units.

[0155] In step 730, if an original qubit unit of the quantum hardware resource is an occupied qubit unit, it not only indicates that the original qubit unit is unavailable, but also the connection relationship connected to the original qubit unit is unavailable. Therefore, it is necessary to obtain the second connection relationship between the occupied qubit units and between the occupied qubit units and the adjacent qubit units. For example, continue as Figure 8B As shown, the second connection relationship corresponding to the quantum bit unit 2 includes the second connection relationship L 1，2 , the second connection relationship L 2，3 , the second connection relationship L 2，11 The second connection relationship corresponding to the quantum bit unit 10 includes the second connection relationship L 3，10 , the second connection relationship L 9，10 , the second connection relationship L 10，11 .

[0156] In step 740, the occupied qubit units are removed from the original qubit units, and the second connection relationship is removed from the first connection relationship to obtain a qubit unit network. Figure 8C As shown, qubit unit 2 and qubit unit 10 are removed from the 12 original qubit units, and the original qubit units include {qubit unit 1, qubit unit 3, qubit unit 4, qubit unit 5, qubit unit 6, qubit unit 7, qubit unit 8, qubit unit 9, qubit unit 11, qubit unit 12}, a total of 10 original qubit units. Then L is removed from the 16 first connection relationships. 1，2 , L 2，3 , L 2，11 , L 3，10 , L 9，10 , L 10，11 , the first connection relationship includes {the first connection relationship L 3，4 , the first connection relationship L 4，5 , the first connection relationship L 5，6 , the first connection relationship L 6，7 , the first connection relationship L 7，8 , the first connection relationship L 8，9 , the first connection relationship L11,12 , the first connection relationship L 1，12 , the first connection relationship L 4,9 , the first connection relationship L 5,8}, a total of 10 first connection relationships.

[0157] The benefit of the embodiment of steps 710-740 is that by removing occupied qubit units and connection relationships associated with occupied qubit units, the possibility of unavailable qubit units in the qubit unit network is reduced, thereby improving the availability of the qubit unit network.

[0158] Detailed description of step 330

[0159] In step 330, in the qubit unit network, a plurality of candidate qubit unit subnetworks that conform to the target qubit unit topology are obtained. The candidate qubit unit subnetwork is a subset of the qubit unit network. In fact, if a candidate qubit unit subnetwork includes the qubit units in the target qubit unit topology and the connection relationship between the qubit units, it indicates that the candidate qubit unit conforms to the target qubit unit topology. Therefore, in one embodiment, assuming that the target qubit unit topology contains a first number of qubit units, the qubit unit network is screened based on the first number of qubit units, and then a network whose connection relationship is also consistent with the target qubit unit topology is found from the screened qubit unit subnetwork.

[0160] Reference Fig. 9 In a specific implementation of this embodiment, the target qubit unit topology includes a first number of qubit units, and step 330 includes:

[0161] Step 910: traverse the quantum bit unit network to obtain multiple post-screening quantum bit unit sub-networks, where the post-screening quantum bit unit sub-networks include a first number of connected quantum bit units;

[0162] Step 920: compare the third connection relationship between the qubit units in the target qubit unit topology with the fourth connection relationship between the qubit units in each screened qubit unit subnetwork, so as to determine multiple candidate qubit unit subnetworks from the multiple screened qubit unit subnetworks.

[0163] In step 910, the qubit unit sub-network is a subset of the qubit unit network and includes a first number of qubit units. Fig.10As shown, assuming that the target qubit unit topology includes 4 qubit units, the qubit unit network includes 12 qubit units. After traversal, the obtained screened qubit unit subnetwork includes 4 connected qubit units. Fig.10 The five post-screening qubit unit subnetworks are shown in Fig.10 The part circled by the dotted line in the matrix in the figure), but in fact there are other post-selection qubit unit sub-networks. For example, qubit unit 1, qubit unit 2, qubit unit 3, and qubit unit 4 in the qubit unit network can also form a post-selection qubit unit sub-network.

[0164] In step 920, the number of qubit units in the screened qubit unit subnetwork is the same as the target qubit unit topology, but the connection relationship is not necessarily the same. Therefore, it is necessary to compare the third connection relationship with the fourth connection relationship, and the screened qubit unit subnetwork with the same connection relationship as the comparison result is used as a candidate qubit unit subnetwork.

[0165] For example, continue as Fig.10 As shown, five candidate qubit unit subnetworks can be determined from multiple screened qubit unit subnetworks. The five candidate qubit unit subnetworks include candidate qubit unit subnetwork W1, candidate qubit unit subnetwork W2, candidate qubit unit subnetwork W3, candidate qubit unit subnetwork W4, and candidate qubit unit subnetwork W5. Among them, candidate qubit unit subnetwork W1 includes qubit unit 1, qubit unit 2, qubit unit 11, and qubit unit 12. Candidate qubit unit subnetwork W2 includes qubit unit 2, qubit unit 3, qubit unit 10, and qubit unit 11. Candidate qubit unit subnetwork W3 includes qubit unit 3, qubit unit 4, qubit unit 9, and qubit unit 10. Candidate qubit unit subnetwork W4 includes qubit unit 4, qubit unit 5, qubit unit 8, and qubit unit 9. Candidate qubit unit subnetwork W5 includes qubit unit 5, qubit unit 6, qubit unit 7, and qubit unit 8.

[0166] It should be noted that multiple candidate qubit unit subnetworks are different from each other, but there may be overlaps. For example, the overlapping part of W1 and W2 includes qubit unit 2 and qubit unit 11. The overlapping part of W2 and W3 includes qubit unit 3 and qubit unit 10. The overlapping part of W3 and W4 includes qubit unit 4 and qubit unit 9. The overlapping part of W4 and W5 includes qubit unit 5 and qubit unit 8.

[0167] The benefit of the embodiment of steps 910-920 is that since the number of quantum bit units in the screened quantum bit unit sub-network is smaller than that of the quantum bit unit network, it is more efficient to find the quantum bit unit sub-network with the same connection relationship as the candidate quantum bit unit sub-network from the obtained screened quantum bit unit sub-network.

[0168] Detailed description of step 340

[0169] In step 340, the overall operation fidelity of the candidate qubit unit subnetwork is determined based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operation fidelity between adjacent qubit units.

[0170] It should be noted that when a quantum bit unit performs a quantum computing task, it is generally expected that the gate operation will achieve the expected result. However, due to various reasons, the results will generally deviate. The degree of closeness between the actual gate operation result (i.e., the observed result of the state of the quantum bit after the gate operation) and the expected gate operation result is the fidelity. The fidelity of the gate operation represents the fidelity of the execution task. The fidelity of the gate operation is manifested in the embodiments of the present disclosure as self-operation fidelity and mutual operation fidelity.

[0171] Self-operation fidelity refers to the degree of closeness between the first actual operation result and the first expected operation result after the qubit unit performs gate operation alone. The higher the degree of closeness, the higher the self-operation fidelity. For example, if the first actual operation result is 0.9 and the first expected operation result is 0.8, the self-operation fidelity is (0.8-|0.8-0.9|) / 0.8=7 / 8.

[0172] The mutual operation fidelity refers to the degree of closeness between the second actual operation result and the second expected operation result after the gate operation between the quantum bit units. The higher the degree of closeness, the higher the mutual operation fidelity. For example, if the second actual operation result is 0.7 and the second expected operation result is 0.9, the mutual operation fidelity is (0.9-|0.9-0.7|) / 0.9=7 / 9.

[0173] In one embodiment, the overall operational fidelity can be determined by calculating the sum of the self-operation fidelity and the mutual operation fidelity. For example, the candidate quantum bit unit subnetwork includes 4 quantum bit units. The self-operation fidelity of each quantum bit unit includes {0.9, 0.8, 0.7, 0.8}, and the mutual operation fidelity between adjacent quantum bit units includes {0.6, 0.4, 0.7, 0.6}. Then the overall operational fidelity is (0.9+0.8+0.7+0.8+0.6+0.4+0.7+0.6)=5.5. The advantage of using and calculating the overall operational fidelity is that the influence of the self-operation fidelity and the mutual operation fidelity on the determination of the overall operational fidelity can be equally reflected.

[0174] In one embodiment, the overall operation fidelity may be determined by calculating a weighted sum of the self-operation fidelity and the mutual operation fidelity.

[0175] Reference Fig.11 In the specific implementation of this embodiment, step 340 includes:

[0176] Step 1110, obtaining a first weight of the self-operation fidelity and a second weight of the mutual operation fidelity;

[0177] Step 1120: Based on the first weight and the second weight, perform a weighted sum of the self-operation fidelity and the mutual operation fidelity to obtain the overall operation fidelity.

[0178] In step 1110, the first weight and the second weight may be set in advance, for example, the first weight is set to 0.9 and the second weight is set to 1.1. That is, no matter what quantum computing task is targeted, the fixed first weight and second weight may be used to participate in the calculation of the overall computing fidelity.

[0179] In one embodiment, step 1110 includes:

[0180] Obtain the task type of the target quantum computing task;

[0181] Based on the task type, a preset mapping relationship between the task type and the weight is searched to obtain a first weight and a second weight.

[0182] Specifically, the task type refers to the type to which the target quantum computing task belongs in the preset type set. For example, the type set includes a first type, a second type, and a third type. In one embodiment, the task type of the target quantum computing task can be obtained by a classification model or other type determination method. The mapping relationship between the task type and the weight is shown in Table 1. Assuming that the task type is the first type, the first weight is 0.6 and the second weight is 1.4. Assuming that the task type is the second type, the first weight is 0.8 and the second weight is 1.2. Assuming that the task type is the third type, the first weight is 0.9 and the second weight is 1.1.

[0183] Task Type Weight Type I The first weight is 0.6, the second weight is 1.4 Type II The first weight is 0.8, the second weight is 1.2 The third type The first weight is 0.9, the second weight is 1.1

[0184] Table 1

[0185] After the first weight and the second weight are obtained in step 1110 , in step 1120 , a weighted sum is performed on the self-operation fidelity and the mutual operation fidelity based on the first weight and the second weight to obtain the overall operation fidelity.

[0186] The benefit of the embodiment of steps 1110 - 1120 is that different weights can be set for self-operation fidelity and mutual operation fidelity, thereby increasing the flexibility of determining the overall operation fidelity.

[0187] In one example, if Fig.12 As shown, the quantum hardware resource includes 12 qubit units. The self-operation fidelity of qubit unit 1 is 0.9. The self-operation fidelity of qubit unit 2 is 0.8. The self-operation fidelity of qubit unit 3 is 0.4. The self-operation fidelity of qubit unit 4 is 0.7. The self-operation fidelity of qubit unit 5 is 0.5. The self-operation fidelity of qubit unit 6 is 0.6. The self-operation fidelity of qubit unit 7 is 0.8. The self-operation fidelity of qubit unit 8 is 0.5. The self-operation fidelity of qubit unit 9 is 0.6. The self-operation fidelity of qubit unit 10 is 0.8. The self-operation fidelity of qubit unit 11 is 0.4. The self-operation fidelity of qubit unit 12 is 0.8.

[0188] Continue as Fig.12 As shown, the mutual operation fidelity between qubit units 1 and 2 is 0.6. The mutual operation fidelity between qubit units 2 and 3 is 0.7. The mutual operation fidelity between qubit units 3 and 4 is 0.9. The mutual operation fidelity between qubit units 4 and 5 is 0.4. The mutual operation fidelity between qubit units 5 and 6 is 0.4. The mutual operation fidelity between qubit units 6 and 7 is 0.8. The mutual operation fidelity between qubit units 7 and 8 is 0.9. The mutual operation fidelity between qubit units 8 and 9 is 0.8. The mutual operation fidelity between qubit units 9 and 10 is 0.7. The mutual operation fidelity between qubit units 10 and 11 is 0.4. The mutual operation fidelity between qubit units 11 and 12 is 0.7. The mutual operation fidelity between qubit units 1 and 12 is 0.4. The mutual operation fidelity between qubit units 2 and 11 is 0.5. The mutual operation fidelity between qubit units 3 and 10 is 0.3. The mutual operation fidelity between qubit units 4 and 9 is 0.9. The mutual operation fidelity between qubit units 5 and 8 is 0.7.

[0189] Assume that the first weight is 0.8 and the second weight is 1.2. Fig.12As shown, the overall operational fidelity of candidate qubit unit subnetwork W1 is 0.8*(0.9+0.8+0.4+0.8)+1.2*(0.6+0.5+0.7+0.4)=4.96. The overall operational fidelity of candidate qubit unit subnetwork W2 is 0.8*(0.8+0.4+0.8+0.4)+1.2*(0.7+0.3+0.4+0.5)=4.2. The overall operational fidelity of candidate qubit unit subnetwork W3 is 0.8*(0.4+0.7+0.6+0.8)+1.2*(0.9+0.9+0.7+0.3)=5.39. The overall operational fidelity of candidate qubit unit subnetwork W4 is 0.8*(0.7+0.5+0.5+0.6)+1.2*(0.4+0.7+0.8+0.9)=5.2. The overall operational fidelity of candidate qubit unit subnetwork W5 is 0.8*(0.5+0.6+0.8+0.5)+1.2*(0.4+0.8+0.9+0.7)=5.28.

[0190] Detailed description of step 350

[0191] In step 350, a target qubit unit subnetwork is determined based on the overall operational fidelity of the plurality of candidate qubit unit subnetworks as a virtualized resource for the target quantum computing task.

[0192] In one embodiment, multiple overall operation fidelities may be sorted by size, and the candidate qubit unit subnetwork corresponding to the largest overall operation fidelity from the sorting result is used as the target qubit unit subnetwork. Alternatively, multiple overall operation fidelities are compared with a fidelity threshold, and the candidate qubit unit subnetwork whose overall operation fidelity is greater than the fidelity threshold is used as the target qubit subnetwork.

[0193] The benefit of this embodiment is that the target quantum bit unit sub-network is determined only based on the overall operational fidelity, and the determination efficiency is high.

[0194] It should be noted that the overall operational fidelity actually refers to the operational accuracy when the candidate quantum bit unit subnetwork does not fail. However, to a certain extent, some candidate quantum bit unit subnetworks are prone to failure. If the failure rate of a candidate quantum bit unit subnetwork is relatively high, then even if its overall operational fidelity is high, it should not be used as a target quantum bit unit subnetwork.

[0195] Reference Fig.13 In the specific implementation of this embodiment, step 350 includes:

[0196] Step 1310: determining the overall failure rate of the candidate qubit unit subnetwork based on the failure rate of each qubit unit in the candidate qubit unit subnetwork;

[0197] Step 1320: Determine a target quantum bit unit subnetwork based on the overall operational fidelity and overall failure rate of multiple candidate quantum bit unit subnetworks.

[0198] In step 1310, the candidate qubit unit subnetwork includes multiple qubit units. Each qubit unit has a corresponding failure rate. The failure rates of each qubit unit are counted to obtain the overall failure rate. For example, the candidate qubit unit subnetwork includes 4 qubit units, and the failure rates are 0.01, 0.03, 0.02, and 0.01, respectively. The overall failure rate is (0.1+0.3+0.2+0.1) / 4=0.0175.

[0199] After determining the overall failure rate at step 1310 , at step 1320 , a target qubit unit subnetwork is determined based on the overall operational fidelity and the overall failure rate.

[0200] For example, Fig.14 As shown, there are a total of 5 candidate quantum bit unit subnetworks. Among them, the overall operational fidelity of candidate quantum bit unit subnetwork W1 is 4.96, and the overall failure rate is 0.02. The overall operational fidelity of candidate quantum bit unit subnetwork W2 is 4.2, and the overall failure rate is 0.05. The overall operational fidelity of candidate quantum bit unit subnetwork W3 is 5.39, and the overall failure rate is 0.09. The overall operational fidelity of candidate quantum bit unit subnetwork W4 is 5.2, and the overall failure rate is 0.03. The overall operational fidelity of candidate quantum bit unit subnetwork W5 is 5.28, and the overall failure rate is 0.01. In this example, W3 has the highest overall operational fidelity, but the overall failure rate of W3 is 0.09, which is a high overall failure rate and is not suitable as a target quantum bit unit subnetwork. Although the overall operational fidelity of W5 is lower than that of W3, the overall failure rate of W5 is 0.01. After comprehensively considering the overall operational fidelity and overall failure rate, W5 was selected as the target quantum bit unit sub-network.

[0201] In one embodiment, step 1320 includes:

[0202] determining a first score based on the overall operational fidelity of the candidate qubit unit subnetwork;

[0203] determining a second score based on the overall failure rate of the candidate qubit unit subnetwork;

[0204] Determining a total score of the candidate qubit unit subnetwork based on the first score and the second score;

[0205] Based on the total scores of the multiple candidate qubit unit subnetworks, a target qubit unit subnetwork is determined.

[0206] Specifically, based on the overall operational fidelity of the candidate quantum bit unit sub-network, the first score is determined by looking up a comparison table between the overall operational fidelity range and the first score, or by using a formula method, etc.

[0207] (1) The overall operation fidelity range and the first score comparison table lists the corresponding relationship between the overall operation fidelity range and the first score. First, the overall operation fidelity range is obtained according to the overall operation fidelity, and then the overall operation fidelity range and the first score comparison table are searched to obtain the first score. The following is an example of the overall operation fidelity range and the first score comparison table:

[0208] Overall operational fidelity range First Score 0.9 or more 100 0.7-0.9 90 0.5-0.7 80 0.3-0.5 70 0.1-0.3 60 …… ……

[0209] Table 2

[0210] For example, if the overall operation fidelity is 0.8, then the overall operation fidelity range is 0.7-0.9. By looking up Table 2, the corresponding first score is 90.

[0211] The above method of searching the comparison table between the overall operation fidelity range and the first score has the advantages of being simple and easy to implement with low processing overhead.

[0212] (2) When the formula method is used, the first score can be set to be proportional to the overall operation fidelity, for example:

[0213] F1=K1*G1 Formula 1

[0214] Among them, F1 represents the first score, G1 represents the overall operation fidelity, and K1 is a preset constant that can be set according to actual needs. For example, K1=112.5, after substituting G1=0.8, the first score F1=90.

[0215] The advantages of the above method of determining the first score by means of a formula are high accuracy, and the formula can be adjusted as required, which is highly flexible.

[0216] Based on the overall failure rate of the candidate quantum bit unit sub-network, the second score can be determined by looking up a comparison table between the overall failure rate range and the second score, or by using a formula method, etc.

[0217] (1) The overall failure rate range and the second score comparison table lists the corresponding relationship between the overall failure rate range and the second score. First, the overall failure rate range is obtained according to the overall failure rate, and then the overall failure rate range and the second score comparison table are searched to obtain the second score. The following is an example of the overall failure rate range and the second score comparison table:

[0218] Overall failure rate range Second score 0-0.01 100 0.01-0.03 90 0.03-0.05 80 0.05-0.07 70 0.07-0.09 60 …… ……

[0219] Table 3

[0220] For example, if the overall failure rate is 0.02, then the overall failure rate range is 0.01-0.03. By looking up Table 3, the corresponding second score is 90.

[0221] The above method of searching the comparison table of the overall failure rate range and the second score has the advantages of being simple and easy to implement with low processing overhead.

[0222] (2) When the formula method is used, the second score can be set to be inversely proportional to the overall failure rate, for example:

[0223] F2=K2*G2+b Formula 2

[0224] Wherein, F2 represents the second score, G2 represents the overall failure rate, K2 and b are preset constants, which can be set according to actual needs. For example, K2 = -100, b = 92, after substituting G2 = 0.02, the second score F2 = 90.

[0225] The advantages of the above method of determining the second score by means of a formula are high accuracy, and the formula can be adjusted as required, thus having high flexibility.

[0226] Based on the first score and the second score, the total score of the candidate quantum bit unit subnetwork is determined by calculating the average or weighted average of the first score and the second score.

[0227] When the average of the first score and the second score is calculated as the total score, for example, if the first score is 90 and the second score is 80, the total score is (90+80) / 2=85. The advantage of using the average to calculate the total score is that the influence of the overall operation fidelity and the overall failure rate on determining the total score can be equally reflected.

[0228] When calculating the weighted average of the first score and the second score as the total score, for example, the weights of the overall operational fidelity and the overall failure rate are set to 0.6 and 0.4 respectively, the first score is 90, and the second score is 80, then the total score is 90×0.6+80×0.4=86. The advantage of using the weighted average to calculate the total score is that different weights can be set for the overall operational fidelity and the overall failure rate, which increases the flexibility of determining the total score.

[0229] Based on the total scores of multiple candidate qubit unit subnetworks, a target qubit unit subnetwork is determined. The multiple total scores can be sorted by size, and the candidate qubit unit subnetwork corresponding to the largest total score in the sorting result is used as the target qubit unit subnetwork. Alternatively, the multiple total scores are compared with a first threshold, and one of the multiple candidate qubit unit subnetworks whose total scores are greater than the first threshold is selected as the target qubit subnetwork.

[0230] The benefit of this embodiment is that the total score is determined based on the first score of the overall operational fidelity and the second score of the overall failure rate, so that the target quantum bit unit network is determined based on the total score, thereby improving the determination accuracy.

[0231] It should be noted that the above embodiment determines the target quantum bit unit network based on the overall computational fidelity and the overall failure rate, and is more inclined to ensure the stability of the target quantum bit unit network. In one embodiment, in order to ensure that the target quantum bit unit network can meet the computational accuracy requirements of the target quantum computing task, it is necessary to determine the target quantum bit unit subnetwork based on the importance of the target quantum computing task.

[0232] Reference Fig.15 In the specific implementation of this embodiment, step 350 includes:

[0233] Step 1510: Obtain the importance of the target quantum computing task;

[0234] Step 1520, determining the fidelity level corresponding to the importance;

[0235] Step 1530: Determine the candidate quantum bit unit subnetwork whose overall computational fidelity belongs to the fidelity level among the multiple candidate quantum bit unit subnetworks as the target quantum bit unit subnetwork.

[0236] In step 1510, the importance indicates the importance of the target quantum computing task. For example, if a target quantum computing task contains more mutual operations, the importance of the target quantum computing task is higher. When the target quantum computing task is generated, the importance can be automatically marked for it, so that the importance of the target quantum computing task can be obtained. Alternatively, when determining the target quantum bit unit subnetwork for the target quantum computing task, the target quantum computing task is parsed, and the importance is determined based on the parsed quantum computing. This embodiment does not specifically limit the method for obtaining the importance.

[0237] In step 1520, the fidelity level corresponding to the importance is determined, and the fidelity level can be obtained by searching for a preset importance-level mapping relationship. The importance-level mapping relationship is shown in Table 4. Assuming the importance is 0.9-1, the fidelity level is 5-10, assuming the importance is 0.7-0.9, the fidelity level is 4-5, and assuming the importance is 0.5-0.7, the fidelity level is 1-4.

[0238] Importance Fidelity Level 0.9-1 5-10 0.7-0.9 4-5 0.5-0.7 1-4 …… ……

[0239] Table 4

[0240] In step 1530, a candidate qubit unit subnetwork whose overall computation fidelity belongs to the fidelity level among the plurality of candidate qubit unit subnetworks is determined as a target qubit unit subnetwork. Fig.16 As shown, the overall operational fidelity of candidate qubit unit subnetwork W1 is 4.96. The overall operational fidelity of candidate qubit unit subnetwork W2 is 4.2. The overall operational fidelity of candidate qubit unit subnetwork W3 is 5.39. The overall operational fidelity of candidate qubit unit subnetwork W4 is 5.2. The overall operational fidelity of candidate qubit unit subnetwork W5 is 5.28. Assuming that the importance of the target quantum computing task is 0.9, look up Table 4 and get the fidelity level of 5-10. The overall operational fidelity belonging to the fidelity level 5-10 is 5.39, 5.2, and 5.28, so any one of candidate qubit unit subnetwork W3, candidate qubit unit subnetwork W4, and candidate qubit unit subnetwork W5 can be used as the target qubit unit subnetwork.

[0241] The benefit of the embodiment of steps 1510-1530 is that the target quantum bit unit network is determined by utilizing the task type of the target quantum computing task, so that the overall operational fidelity of the target quantum bit unit is linked to the task type, thereby improving the correlation between the target quantum computing task and the target quantum bit unit network.

[0242] It should be noted that both embodiments of step 350 above are for determining a target quantum bit unit subnetwork for a target quantum computing task. However, in one embodiment, there are multiple target quantum computing tasks, and multiple target quantum bit unit subnetworks need to be determined simultaneously.

[0243] Reference Fig.17 , when this embodiment is specifically implemented, the number of target quantum computing tasks is the second number, the number of candidate quantum bit unit subnetworks is the third number, and the second number is less than the third number, then step 350 includes:

[0244] Step 1710, sorting the third number of candidate quantum bit unit sub-networks according to overall computational fidelity;

[0245] Step 1720: Determine the first second number of candidate quantum bit unit sub-networks in the sort as the second number of target quantum bit unit sub-networks for the second number of target quantum computing tasks.

[0246] In one example, if Fig.18 As shown, the second number is 3, specifically including the target quantum computing task R1, the target quantum computing task R2, and the target quantum computing task R3. The third number is 5, specifically including the candidate quantum bit unit subnetwork W1, the candidate quantum bit unit subnetwork W2, the candidate quantum bit unit subnetwork W3, the candidate quantum bit unit subnetwork W4, and the candidate quantum bit unit subnetwork W5. After sorting according to the overall operation fidelity, the sorting is {W3, W5, W4, W1, W2}. The first three candidate quantum bit unit subnetworks in the sorting, that is, W3, W5 and W4, are determined as the three target quantum bit unit subnetworks for the target quantum computing task R1, the target quantum computing task R2, and the target quantum computing task R3. For example, the candidate quantum bit unit subnetwork W3 is used for the target quantum computing task R1, the candidate quantum bit unit subnetwork W5 is used for the target quantum computing task R2, and the candidate quantum bit unit subnetwork W4 is used for the target quantum computing task R3.

[0247] The benefit of the embodiment of steps 1710-1720 is that a second number of target quantum bit unit sub-networks can be determined for a second number of target quantum computing tasks at the same time, thereby improving the determination efficiency.

[0248] It should be noted that the second number of target quantum bit unit subnetworks may be relatively dispersed in the quantum hardware resources. In this case, if the second number of target quantum computing tasks are not related to each other, it can be applied, but if the second number of target quantum computing tasks are related to each other, it is difficult for the dispersed target quantum bit unit subnetwork to greatly improve the processing efficiency. Therefore, in one embodiment, it is necessary to combine the candidate quantum bit unit subnetworks, and determine the second number of target quantum bit unit subnetworks by means of the concentration of the combination.

[0249] Reference Fig.19 In a specific implementation of this embodiment, the target quantum computing task is the associated second number of target quantum computing tasks, the candidate quantum bit unit subnetwork is the third number of candidate quantum bit unit subnetworks, the second number is less than the third number, and step 350 includes:

[0250] Step 1910, traversing the third number of candidate quantum bit unit sub-networks to obtain a plurality of candidate sub-network combinations, where the candidate sub-network combinations include the second number of candidate quantum bit unit sub-networks;

[0251] Step 1920, determining the sum of the overall operational fidelity of a second number of candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0252] Step 1930, determining the concentration of a second number of candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0253] Step 1940: Based on the sum and concentration of multiple candidate sub-network combinations, determine a target sub-network combination from multiple candidate sub-network combinations as a second number of target quantum bit unit sub-networks for a second number of target quantum computing tasks.

[0254] In step 1910, if Fig. 20A As shown, the second number is 3 and the third number is 5. From the 5 candidate quantum bit unit subnetworks W1, W2, W3, W4 and W5, 10 candidate subnetwork combinations can be obtained, each of which contains 3 candidate quantum bit unit subnetworks. The candidate subnetwork combinations are {(W1, W2, W3), (W1, W2, W4,), (W1, W2, W5), (W1, W3, W4), (W1, W3, W5), (W1, W4, W5), (W2, W3, W4), (W2, W3, W5), (W2, W4, W5), (W3, W4, W5)}.

[0255] In step 1920, if Fig. 20BAs shown, the sum of the overall computational fidelity of (W1, W2, W3): 4.96 + 4.2 + 5.39 = 15.55. The sum of the overall computational fidelity of (W1, W2, W4): 4.96 + 4.2 + 5.2 = 14.36. The sum of the overall computational fidelity of (W1, W2, W5): 4.96 + 4.2 + 5.28 = 14.44. The sum of the overall computational fidelity of (W1, W3, W4): 4.96 + 5.39 + 5.2 = 15.55. The sum of the overall computational fidelity of (W1, W3, W5): 4.96 + 5.39 + 5.28 = 15.63. The sum of the overall computational fidelity of (W1, W4, W5): 4.96 + 5.2 + 5.28 = 15.44. The sum of the overall computational fidelity of (W2, W3, W4): 4.2 + 5.39 + 5.2 = 14.79. The sum of the overall computational fidelity of (W2, W3, W5): 4.2 + 4.39 + 5.28 = 13.87. The sum of the overall computational fidelity of (W2, W4, W5): 4.2 + 5.2 + 5.28 = 14.68. The sum of the overall computational fidelity of (W3, W4, W5): 5.39 + 5.2 + 5.28 = 15.87.

[0256] At step 1930, the concentration of the second number of candidate qubit unit sub-networks in the candidate sub-network combination is determined. The concentration indicates the degree of concentration of the distances between each candidate qubit unit sub-network in the candidate sub-network combination.

[0257] In one embodiment, step 1930 includes:

[0258] Determine the center point distances between two of the second number of candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0259] The reciprocal of the average distance of the center point distance is determined as the concentration of the second number of candidate quantum bit unit sub-networks.

[0260] For example, Fig. 20CAs shown, a horizontal rectangular coordinate system is established, and the center point distances between the three candidate quantum bit unit subnetworks in the candidate subnetwork combination are obtained from the horizontal rectangular coordinate system. Specifically, for the candidate subnetwork combination (W1, W2, W3), the center point distance between W1 and W2 = 2, the center point distance between W1 and W3 = 4, and the center point distance between W2 and W3 = 2. For the candidate subnetwork combination (W1, W2, W4), the center point distance between W1 and W2 = 2, the center point distance between W1 and W4 = 6, and the center point distance between W2 and W4 = 4. For the candidate subnetwork combination (W1, W2, W5), the center point distance between W1 and W2 = 2, the center point distance between W1 and W5 = 8, and the center point distance between W2 and W5 = 6. For the candidate subnetwork combination (W1, W3, W4), the center point distance between W1 and W3 = 4, the center point distance between W1 and W4 = 6, and the center point distance between W3 and W4 = 2. For the candidate sub-network combination (W1, W3, W5), the center point distance between W1 and W3 = 4, the center point distance between W1 and W5 = 8, and the center point distance between W3 and W5 = 4. For the candidate sub-network combination (W1, W4, W5), the center point distance between W1 and W4 = 6, the center point distance between W1 and W5 = 8, and the center point distance between W4 and W5 = 2. For the candidate sub-network combination (W2, W3, W4), the center point distance between W2 and W3 = 2, the center point distance between W2 and W4 = 4, and the center point distance between W3 and W4 = 2. For the candidate sub-network combination (W2, W3, W5), the center point distance between W2 and W3 = 2, the center point distance between W2 and W5 = 6, and the center point distance between W3 and W5 = 4. For the candidate sub-network combination (W2, W4, W5), the center point distance between W2 and W4 = 4, the center point distance between W2 and W5 = 6, and the center point distance between W4 and W5 = 2. For the candidate sub-network combination (W3, W4, W5), the center point distance between W3 and W4 = 2, the center point distance between W3 and W5 = 4, and the center point distance between W4 and W5 = 2.

[0261] Continue as Fig. 20CAs shown, the concentration of (W1, W2, W3): 1 / (2+4+2) = 1 / 8. The concentration of (W1, W2, W4): 1 / (2+6+4) = 1 / 12. The concentration of (W1, W2, W5): 1 / (2+8+6) = 1 / 16. The concentration of (W1, W3, W4): 1 / (4+6+2) = 1 / 12. The concentration of (W1, W3, W5): 1 / (4+8+4) = 1 / 16. The concentration of (W1, W4, W5): 1 / (6+8+2) = 1 / 16. The concentration of (W2, W3, W4): 1 / (2+4+2) = 1 / 8. The concentration of (W2, W3, W5): 1 / (2+6+4) = 1 / 12. The concentration of (W2, W4, W5): 1 / (4+6+2) = 1 / 12. The concentration of (W3, W4, W5): 1 / (2+4+2) = 1 / 8.

[0262] After determining the sum and concentration of multiple candidate sub-network combinations, in step 1940, based on the sum and concentration of the multiple candidate sub-network combinations, a target sub-network combination is determined from the multiple candidate sub-network combinations as a second number of target quantum bit unit sub-networks for a second number of target quantum computing tasks.

[0263] In one embodiment, step 1940 includes:

[0264] Determining a third score based on the sum of the candidate sub-network combinations;

[0265] Based on the concentration, a fourth score is determined;

[0266] Determine a total score of the candidate sub-network combination based on the third score and the fourth score;

[0267] Based on the total scores of the candidate sub-network combinations, the target sub-network combination is determined.

[0268] In this embodiment, the higher the sum of the candidate subnetwork combinations, the higher the third score. The higher the concentration, the higher the fourth score. The total score can be determined by calculating the average or weighted average of the third score and the fourth score. Based on the total scores of multiple candidate subnetwork combinations, the target quantum bit unit subnetwork is determined. The total scores of multiple candidate subnetwork combinations can be sorted by size, and the candidate subnetwork combination corresponding to the largest total score from the sorting results is used as the target quantum bit unit subnetwork. Alternatively, multiple total scores are compared with the second threshold, and one of the multiple candidate subnetwork combinations whose total scores are greater than the second threshold is selected as the target subnetwork combination.

[0269] The benefit of this embodiment of steps 1910-1940 is that the accuracy of determining the second number of target quantum ratio unit subnetworks for the associated second number of target quantum computing tasks is improved based on the sum of the overall operational fidelity and the concentration.

[0270] Implementation details of the quantum hardware resource virtualization method of the disclosed embodiment

[0271] Refer to the following Fig.21 , the implementation details of the quantum hardware resource virtualization method of the embodiment of the present disclosure are explained in detail and by way of example.

[0272] In step 2110, a plurality of sample quantum computing tasks are obtained, wherein the plurality of sample quantum computing tasks include a target quantum computing task; a plurality of sample quantum bit unit topologies for the plurality of sample quantum computing tasks are obtained; a union of the plurality of sample quantum bit unit topologies is taken to obtain a universal quantum bit unit topology, and the universal quantum bit unit topology is used as the target quantum bit unit topology;

[0273] In step 2120, original qubit units in the quantum hardware resource and a first connection relationship between the original qubit units are obtained; occupied qubit units are obtained; second connection relationships between occupied qubit units and between occupied qubit units and adjacent qubit units are obtained; the occupied qubit units are removed from the original qubit units, and the second connection relationship is removed from the first connection relationship to obtain a qubit unit network;

[0274] In step 2130, the qubit unit network is traversed to obtain a plurality of post-screening qubit unit subnetworks, wherein the post-screening qubit unit subnetworks include a first number of connected qubit units; the third connection relationship between the qubit units in the target qubit unit topology is compared with the fourth connection relationship between the qubit units in each post-screening qubit unit subnetwork, so as to determine a plurality of candidate qubit unit subnetworks from the plurality of post-screening qubit unit subnetworks;

[0275] In step 2140, the overall operation fidelity of the candidate qubit unit subnetwork is determined based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operation fidelity between adjacent qubit units; the overall failure rate of the candidate qubit unit subnetwork is determined based on the failure rate of each qubit unit in the candidate qubit unit subnetwork;

[0276] In step 2150, based on the overall operational fidelity and overall failure rate of the plurality of candidate quantum bit unit subnetworks, a target quantum bit unit subnetwork is determined as a virtualized resource for the target quantum computing task.

[0277] The benefits of steps 2110-2150 include, but are not limited to, the probability that the overall calculation result generated by the target quantum bit unit subnetwork is inconsistent with the calculation result that the target quantum computing task should have is minimized, that is, the distortion is minimized. In this way, the virtualized quantum hardware resources are divided, the possibility of resource waste is low, the efficiency of resource utilization is improved, and the computing effect is guaranteed.

[0278] Description of the apparatus and device of the present disclosure

[0279] In each specific implementation of the present application, when it comes to the need to perform relevant processing based on data related to object characteristics such as object attribute information or attribute information sets, the permission or consent of the object will be obtained first, and the collection, use and processing of these data will comply with relevant laws, regulations and standards. In addition, when the embodiment of the present application needs to obtain object attribute information, the object's separate permission or separate consent will be obtained through a pop-up window or jump to a confirmation page. After clearly obtaining the object's separate permission or separate consent, the necessary object-related data for the normal operation of the embodiment of the present application will be obtained.

[0280] Reference Fig. 22 , Fig. 22 The structure diagram of the quantum hardware resource virtualization device 2200 provided in the embodiment of the present disclosure includes:

[0281] A first acquisition unit 2210, used to acquire a target quantum bit unit topology for a target quantum computing task;

[0282] A second acquisition unit 2220 is used to acquire a quantum bit unit network in the quantum hardware resources;

[0283] A third acquisition unit 2230 is used to acquire, in the qubit unit network, a plurality of candidate qubit unit sub-networks that conform to the target qubit unit topology;

[0284] A first determining unit 2240, configured to determine the overall operation fidelity of the candidate qubit unit subnetwork based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operation fidelity between adjacent qubit units;

[0285] The second determination unit 2250 is used to determine a target quantum bit unit subnetwork as a virtualized resource for a target quantum computing task based on the overall operational fidelity of multiple candidate quantum bit unit subnetworks.

[0286] Optionally, the first determining unit 2240 is specifically configured to:

[0287] Obtaining a first weight of the self-operation fidelity and a second weight of the mutual operation fidelity;

[0288] Based on the first weight and the second weight, a weighted sum is performed on the self-operation fidelity and the mutual operation fidelity to obtain the overall operation fidelity.

[0289] Optionally, the first determining unit 2240 is further configured to:

[0290] Obtain the task type of the target quantum computing task;

[0291] Based on the task type, a preset mapping relationship between the task type and the weight is searched to obtain a first weight and a second weight.

[0292] Optionally, the target quantum bit unit topology is a universal quantum bit unit topology; the first acquisition unit 2210 is specifically used for:

[0293] Acquire multiple sample quantum computing tasks, wherein the multiple sample quantum computing tasks include a target quantum computing task;

[0294] obtaining a plurality of sample quantum bit unit topologies for a plurality of sample quantum computing tasks;

[0295] Take the union of multiple sample qubit unit topologies to obtain the universal qubit unit topology.

[0296] Optionally, the second acquiring unit 2220 is specifically configured to:

[0297] Acquire original quantum bit units in quantum hardware resources, and a first connection relationship between the original quantum bit units;

[0298] Obtaining occupied quantum bit units;

[0299] Acquire a second connection relationship between occupied qubit units and between an occupied qubit unit and an adjacent qubit unit;

[0300] The occupied quantum bit units are removed from the original quantum bit units, and the second connection relationship is removed from the first connection relationship to obtain a quantum bit unit network.

[0301] Optionally, the target qubit unit topology includes a first number of qubit units; the third acquisition unit 2230 is specifically used to:

[0302] Traversing the quantum bit unit network to obtain a plurality of selected quantum bit unit sub-networks, wherein the selected quantum bit unit sub-networks include a first number of connected quantum bit units;

[0303] The third connection relationship between the qubit units in the target qubit unit topology is compared with the fourth connection relationship between the qubit units in each screened qubit unit subnetwork to determine multiple candidate qubit unit subnetworks from the multiple screened qubit unit subnetworks.

[0304] Optionally, the second determining unit 2250 is specifically configured to:

[0305] Determining an overall failure rate of the candidate qubit unit subnetwork based on the failure rate of each qubit unit in the candidate qubit unit subnetwork;

[0306] Based on the overall operational fidelity and overall failure rate of multiple candidate quantum bit unit sub-networks, a target quantum bit unit sub-network is determined.

[0307] Optionally, the second determining unit 2250 is specifically configured to:

[0308] Obtain the importance of the target quantum computing task;

[0309] Determine the fidelity level corresponding to the importance;

[0310] A candidate quantum bit unit subnetwork whose overall operational fidelity belongs to the fidelity level among multiple candidate quantum bit unit subnetworks is determined as a target quantum bit unit subnetwork.

[0311] Optionally, the number of target quantum computing tasks is a second number, and the number of candidate quantum bit unit subnetworks is a third number, wherein the second number is less than the third number; the second determining unit 2250 is specifically configured to:

[0312] sorting the third number of candidate quantum bit unit sub-networks according to overall operational fidelity;

[0313] The top second number of candidate quantum bit unit sub-networks in the sorting are determined as the second number of target quantum bit unit sub-networks for the second number of target quantum computing tasks.

[0314] Optionally, the target quantum computing task is a second number of associated target quantum computing tasks, and the candidate quantum bit unit subnetwork is a third number of candidate quantum bit unit subnetworks, wherein the second number is less than the third number;

[0315] Optionally, the second determining unit 2250 is specifically configured to:

[0316] Traversing a third number of candidate quantum bit unit sub-networks to obtain a plurality of candidate sub-network combinations, wherein the candidate sub-network combinations include a second number of candidate quantum bit unit sub-networks;

[0317] Determining the sum of the overall operational fidelity of a second number of candidate qubit unit sub-networks in the candidate sub-network combination;

[0318] determining a concentration of a second number of candidate qubit unit sub-networks in the candidate sub-network combination;

[0319] Based on the sum and concentration of the plurality of candidate sub-network combinations, a target sub-network combination is determined from the plurality of candidate sub-network combinations as a second number of target quantum bit unit sub-networks for a second number of target quantum computing tasks.

[0320] Optionally, the second determining unit 2250 is further configured to:

[0321] Determine the center point distances between two of the second number of candidate quantum bit unit sub-networks in the candidate sub-network combination;

[0322] The reciprocal of the average distance of the center point distance is determined as the concentration of the second number of candidate quantum bit unit sub-networks.

[0323] Reference Fig.23 , Fig.23 The structural block diagram of the terminal part of the method for virtualizing quantum hardware resources in the embodiment of the present disclosure is as follows: the terminal includes: a radio frequency (RF) circuit 2310, a memory 2315, an input unit 2330, a display unit 2340, a sensor 2350, an audio circuit 2360, a wireless fidelity (WiFi) module 2370, a processor 2380, and a power supply 2390. Those skilled in the art can understand that Fig.23 The terminal structure shown in the figure does not constitute a limitation on the mobile phone or computer, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0324] The RF circuit 2310 may be used for receiving and sending signals during information transmission or calls. In particular, after receiving the downlink information from the base station, it is sent to the processor 2380 for processing; in addition, the designed uplink data is sent to the base station.

[0325] The memory 2315 may be used to store software programs and modules. The processor 2380 executes various functional applications and data processing of the terminal by running the software programs and modules stored in the memory 2315 .

[0326] The input unit 2330 may be used to receive input digital or character information and generate key signal input related to the terminal's settings and function control. Specifically, the input unit 2330 may include a touch panel 2331 and other input devices 2332 .

[0327] The display unit 2340 may be used to display input information or provided information and various menus of the terminal. The display unit 2340 may include a display panel 2341.

[0328] The audio circuit 2360, the speaker 2361, and the microphone 2362 may provide an audio interface.

[0329] In this embodiment, the processor 2380 included in the terminal can execute the quantum hardware resource virtualization method of the previous embodiment.

[0330] The terminals of the embodiments of the present disclosure include but are not limited to mobile phones, computers, intelligent voice interaction devices, smart home appliances, vehicle terminals, aircraft, etc. The embodiments of the present invention can be applied to various scenarios, including but not limited to quantum computing, distributed quantum computing, superconducting quantum computing, etc.

[0331] Fig.24 A block diagram of the structure of a portion of a server for implementing the quantum hardware resource virtualization method of an embodiment of the present disclosure. The server may have relatively large differences due to different configurations or performances, and may include one or more central processing units (CPUs) 2482 (for example, one or more processors) and a memory 2432, and one or more storage media 2430 (for example, one or more mass storage devices) storing application programs 2442 or data 2444. Among them, the memory 2432 and the storage medium 2430 may be short-term storage or permanent storage. The program stored in the storage medium 2430 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the server 2400. Furthermore, the central processing unit 2422 may be configured to communicate with the storage medium 2430 to execute a series of instruction operations in the storage medium 2430 on the server 2400.

[0332] The server 2400 may also include one or more power supplies 2426, one or more wired or wireless network interfaces 2450, one or more input and output interfaces 2458, and / or one or more operating systems 2441, such as Windows ServerTM, Mac OS XTM, UnixTM, LinuxTM, FreeBSDTM, etc.

[0333] The processor in the server 2400 may be used to execute the quantum hardware resource virtualization method according to the embodiment of the present disclosure.

[0334] The embodiments of the present disclosure also provide a computer-readable storage medium, which is used to store program codes, and the program codes are used to execute the quantum hardware resource virtualization methods of the aforementioned embodiments.

[0335] The embodiment of the present disclosure also provides a computer program product, which includes a computer program. A processor of a computer device reads and executes the computer program, so that the computer device executes the above-mentioned quantum hardware resource virtualization method.

[0336] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present disclosure described herein can, for example, be implemented in an order other than those illustrated or described herein. In addition, the terms "comprises" and "comprising" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0337] It should be understood that in the present disclosure, "at least one (item)" means one or more, and "plurality" means two or more. "And / or" is used to describe the association relationship of associated objects, indicating that three relationships may exist. For example, "A and / or B" can mean: only A exists, only B exists, and A and B exist at the same time, where A and B can be singular or plural. The character " / " generally indicates that the objects associated before and after are in an "or" relationship. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b or c can mean: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, c can be single or multiple.

[0338] It should be understood that in the description of the embodiments of the present disclosure, the meaning of multiple (or multiple items) is more than two, greater than, less than, exceed, etc. are understood to not include the number, and above, below, within, etc. are understood to include the number.

[0339] In the several embodiments provided in the present disclosure, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0340] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0341] In addition, each functional unit in each embodiment of the present disclosure may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0342] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present disclosure is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the various embodiments of the present disclosure. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, referred to as ROM), random access memory (Random Access Memory, referred to as RAM), disk or optical disk and other media that can store program codes.

[0343] It should also be understood that the various implementations provided in the embodiments of the present disclosure can be combined arbitrarily to achieve different technical effects.

[0344] The above is a specific description of the implementation methods of the present disclosure, but the present disclosure is not limited to the above implementation methods. Technical personnel familiar with the art can also make various equivalent modifications or substitutions without violating the spirit of the present disclosure. These equivalent modifications or substitutions are all included in the scope defined by the claims of the present disclosure.

Claims

1. A method for virtualizing quantum hardware resources, characterized in that: include: Obtaining a target quantum bit unit topology for a target quantum computing task; Obtain the quantum bit unit network in the quantum hardware resource; In the qubit unit network, a plurality of candidate qubit unit subnetworks that conform to the target qubit unit topology are obtained; Determining the overall operational fidelity of the candidate qubit unit subnetwork based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operational fidelity between adjacent qubit units; Based on the overall operational fidelity of the plurality of candidate quantum bit unit subnetworks, a target quantum bit unit subnetwork is determined as a virtualized resource for the target quantum computing task.

2. The method according to claim 1, characterized in that: Determining the overall operation fidelity of the candidate qubit unit subnetwork based on the self-operation fidelity of each qubit unit in the candidate qubit unit subnetwork and the mutual operation fidelity between adjacent qubit units includes: Obtaining a first weight of the self-operation fidelity and a second weight of the mutual operation fidelity; Based on the first weight and the second weight, a weighted sum is performed on the self-operation fidelity and the mutual operation fidelity to obtain the overall operation fidelity.

3. The method according to claim 2, characterized in that The obtaining of the first weight of the self-operation fidelity and the second weight of the mutual operation fidelity includes: Obtaining a task type of the target quantum computing task; Based on the task type, a preset mapping relationship between the task type and the weight is searched to obtain the first weight and the second weight.

4. The method according to claim 1, characterized in that: The target qubit unit topology is a universal qubit unit topology; The step of obtaining a target quantum bit unit topology for a target quantum computing task includes: Acquire a plurality of sample quantum computing tasks, wherein the plurality of sample quantum computing tasks include the target quantum computing task; Acquire a plurality of sample quantum bit unit topologies for a plurality of the sample quantum computing tasks; The union of multiple sample quantum bit unit topologies is taken to obtain the universal quantum bit unit topology.

5. The method according to claim 1, characterized in that The step of obtaining a quantum bit unit network in a quantum hardware resource includes: Acquire original quantum bit units in a quantum hardware resource, and a first connection relationship between the original quantum bit units; Obtaining occupied quantum bit units; Acquire a second connection relationship between the occupied qubit units and between the occupied qubit unit and an adjacent qubit unit; The occupied quantum bit unit is removed from the original quantum bit unit, and the second connection relationship is removed from the first connection relationship to obtain the quantum bit unit network.

6. The method according to claim 1, characterized in that The target qubit unit topology includes a first number of qubit units; The step of obtaining, in the quantum bit unit network, a plurality of candidate quantum bit unit sub-networks that conform to the target quantum bit unit topology comprises: Traversing the qubit unit network to obtain a plurality of post-screening qubit unit sub-networks, the post-screening qubit unit sub-networks comprising the first number of connected qubit units; The third connection relationship between the quantum bit units in the target quantum bit unit topology is compared with the fourth connection relationship between the quantum bit units in each of the screened quantum bit unit sub-networks to determine a plurality of candidate quantum bit unit sub-networks from the plurality of screened quantum bit unit sub-networks.

7. The method according to claim 1, characterized in that The step of determining a target qubit unit subnetwork based on the overall operational fidelity of the plurality of candidate qubit unit subnetworks comprises: Determining an overall failure rate of the candidate qubit unit subnetwork based on the failure rate of each of the qubit units in the candidate qubit unit subnetwork; A target quantum bit unit sub-network is determined based on the overall operational fidelity and the overall failure rate of the plurality of candidate quantum bit unit sub-networks.

8. The method according to claim 1, characterized in that The step of determining a target qubit unit subnetwork based on the overall operational fidelity of the plurality of candidate qubit unit subnetworks comprises: Obtaining the importance of the target quantum computing task; determining a fidelity level corresponding to the importance; The candidate quantum bit unit subnetwork whose overall operation fidelity belongs to the fidelity level among the multiple candidate quantum bit unit subnetworks is determined as the target quantum bit unit subnetwork.

9. The method according to claim 1, characterized in that: The number of the target quantum computing tasks is a second number, and the number of the candidate quantum bit unit subnetworks is a third number, wherein the second number is smaller than the third number; The step of determining a target qubit unit subnetwork based on the overall operational fidelity of the plurality of candidate qubit unit subnetworks comprises: sorting the third number of candidate quantum bit unit sub-networks according to the overall operational fidelity; The first second number of the candidate quantum bit unit sub-networks in the sorting are determined as the second number of the target quantum bit unit sub-networks for the second number of the target quantum computing tasks.

10. The method according to claim 1, characterized in that The target quantum computing task is a second number of the associated target quantum computing tasks, and the candidate quantum bit unit subnetwork is a third number of the candidate quantum bit unit subnetwork, wherein the second number is less than the third number; The step of determining a target qubit unit subnetwork based on the overall operational fidelity of the plurality of candidate qubit unit subnetworks comprises: Traversing the third number of the candidate quantum bit unit sub-networks to obtain a plurality of candidate sub-network combinations, wherein the candidate sub-network combinations include the second number of the candidate quantum bit unit sub-networks; Determining the sum of the overall operational fidelity of a second number of the candidate qubit unit sub-networks in the candidate sub-network combination; Determining the concentration of a second number of the candidate quantum bit unit sub-networks in the candidate sub-network combination; Based on the sum and the concentration of the plurality of candidate sub-network combinations, a target sub-network combination is determined from the plurality of candidate sub-network combinations as a second number of the target quantum bit unit sub-networks for a second number of the target quantum computing tasks.

11. The method according to claim 10, characterized in that Determining the concentration of a second number of the candidate quantum bit unit sub-networks in the candidate sub-network combination includes: Determine the center point distances between two of the second number of candidate quantum bit unit sub-networks in the candidate sub-network combination; The reciprocal of the average distance of the center point distance is determined as the concentration of the second number of the candidate quantum bit unit sub-networks.

12. A quantum hardware resource virtualization device, characterized in that: include: A first acquisition unit, used to acquire a target quantum bit unit topology for a target quantum computing task; A second acquisition unit, used to acquire a quantum bit unit network in a quantum hardware resource; A third acquisition unit is used to acquire, in the quantum bit unit network, a plurality of candidate quantum bit unit sub-networks that conform to the target quantum bit unit topology; A first determining unit, configured to determine the overall operation fidelity of the candidate quantum bit unit subnetwork based on the self-operation fidelity of each quantum bit unit in the candidate quantum bit unit subnetwork and the mutual operation fidelity between adjacent quantum bit units; The second determination unit is used to determine a target quantum bit unit subnetwork as a virtualized resource for the target quantum computing task based on the overall operational fidelity of the plurality of candidate quantum bit unit subnetworks.

13. An electronic device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the quantum hardware resource virtualization method according to any one of claims 1 to 11 is implemented.

14. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the quantum hardware resource virtualization method according to any one of claims 1 to 11 is implemented.

15. A computer program product, comprising a computer program, wherein the computer program is read and executed by a processor of a computer device, so that the computer device executes the quantum hardware resource virtualization method according to any one of claims 1 to 11.

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