Method and device for determining quantum bit parameter drift

Abstract

The application discloses a quantum bit parameter drift judgment method and device, which judges whether a first parameter drifts or not by using a first directed acyclic graph and a physical model, wherein the first parameter is a quantum bit parameter corresponding to a dependent node position of the to-be-tested parameter in the first directed acyclic graph. The scheme for judging whether the quantum bit parameter drifts or not based on the application can realize rapid judgment of the drift condition of the quantum bit parameter without manual intervention, and improves the execution efficiency of the quantum computing task to a certain extent.

Description

Technical Field

[0001] This invention relates to the field of quantum computing, and in particular to a method and apparatus for determining the drift of qubit parameters. Background Technology

[0002] Quantum computing and quantum information is an interdisciplinary field that uses the principles of quantum mechanics to perform computational and information processing tasks. It is closely related to quantum physics, computer science, and informatics. It has experienced rapid development in the last two decades. Quantum algorithms based on quantum computers have demonstrated performance far exceeding that of existing classical computer-based algorithms in scenarios such as factorization and unstructured search, leading to expectations that this field will surpass current computing capabilities. Because quantum computing has the potential to far exceed the performance of classical computers in solving specific problems, realizing a quantum computer requires a quantum chip containing a sufficient number and quality of qubits, and the ability to perform extremely high-fidelity quantum logic gate operations and readouts of these qubits.

[0003] Quantum chips are to quantum computers what CPUs are to traditional computers; they are the core components of quantum computers. With the continuous advancement of quantum computing technologies, the number of qubits on quantum chips is increasing year by year. It is foreseeable that larger-scale quantum chips will emerge in the future, containing even more qubits, and quantum computers will incorporate larger-scale quantum chips. As the number of qubits increases, the problem of parameter drift in some qubits inevitably arises during use, requiring corresponding calibration operations. When a quantum chip is performing a quantum computing task, if the performance of a particular qubit in that chip malfunctions, we cannot immediately identify which parameter has drifted. Current technology typically addresses this problem by having staff judge the qubit's output signal based on past experience; this approach is inefficient and significantly impacts the execution efficiency of quantum computing tasks.

[0004] Therefore, proposing a scheme to quickly determine whether qubit parameters have drifted has become an urgent problem to be solved in this field.

[0005] It should be noted that the information disclosed in the background section of this application is intended only to enhance the understanding of the general background of this application, and should not be construed as an admission or in any way implying that the information constitutes prior art known to those skilled in the art. Summary of the Invention

[0006] The purpose of this invention is to provide a method and apparatus for determining whether qubit parameters have drifted, in order to solve the problem that the existing schemes for determining whether qubit parameters have drifted are inefficient and greatly affect the execution efficiency of quantum computing tasks.

[0007] To address the above technical problems, this invention proposes a method for determining quantum bit parameter drift, comprising:

[0008] Obtain a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters;

[0009] A physical model is obtained for the measured parameters of the sub-bit to be measured, and the physical model is used to obtain the theoretical expected value of the measured parameters;

[0010] The first parameter is determined to have drifted by using the first directed acyclic graph and the physical model. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph.

[0011] Optionally, determining whether the first parameter has drifted using the first directed acyclic graph and the physical model includes:

[0012] A first test experiment is performed on the sub-bit to be measured to obtain the experimental results of the parameter to be measured. The first test experiment is an experiment in which the sub-bit to be measured is used to obtain the parameter to be measured.

[0013] The first parameter is obtained based on the first directed acyclic graph;

[0014] Based on the physical model and the experimental results, determine whether the first parameter has drifted.

[0015] Optionally, determining whether the first parameter has drifted based on the physical model and the experimental results includes:

[0016] The degree of deviation of the experimental results is obtained based on the physical model.

[0017] Based on the degree of offset, it is determined whether the first parameter has drifted.

[0018] Optionally, determining whether the first parameter has drifted based on the degree of offset includes:

[0019] Determine whether the degree of offset is within a preset range;

[0020] If so, then it is determined that the first parameter has not drifted;

[0021] If not, then it is determined that the first parameter has drifted.

[0022] Optionally, obtaining the degree of offset of the experimental results through the physical model includes:

[0023] The theoretical expected value of the parameter to be measured is obtained using the physical model.

[0024] The degree of deviation of the experimental results is obtained based on the theoretical expected value.

[0025] Optionally, obtaining the degree of deviation of the experimental results based on the theoretical expected value includes:

[0026] The degree of deviation is obtained by using goodness of fit to the theoretical expected value and the experimental results.

[0027] Optionally, obtaining the degree of deviation by using goodness of fit on the theoretical expected value and the experimental results includes:

[0028] Construct the first formula, which is:

[0029]

[0030] Among them, R 2 For the degree of offset, y fit For the theoretical expected value, y raw The experimental results are as described. The average value of the experimental results;

[0031] The degree of offset is obtained using the first formula.

[0032] Based on the same inventive concept, the present invention also proposes a method for calibrating quantum bit parameters, which uses the method for judging the drift of quantum bit parameters described in any of the above-described features to judge the first parameter, and performs a calibration operation on the first parameter when the judgment result is yes.

[0033] Based on the same inventive concept, this invention also proposes a device for determining the drift of quantum bit parameters, comprising:

[0034] A directed acyclic graph acquisition module is configured to acquire a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters.

[0035] A physical model acquisition module is configured to acquire a physical model of the measured parameters of the measured sub-bit, wherein the physical model is used to acquire the theoretical expected value of the measured parameters.

[0036] The parameter drift determination module is configured to determine whether a first parameter has drifted using the first directed acyclic graph and the physical model. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph.

[0037] Based on the same inventive concept, the present invention also proposes a quantum control system, which uses the method for judging the drift of quantum bit parameters described in any of the above-described features to judge the first parameter, or the device for judging the drift of quantum bit parameters described in the above-described features.

[0038] Based on the same inventive concept, the present invention also proposes a quantum computer, including the quantum control system described in the above feature description.

[0039] Based on the same inventive concept, the present invention also proposes a readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, it can implement the method for determining the drift of the qubit parameters as described in any of the above-described features, or implement the method for calibrating the qubit parameters as described in the above-described features.

[0040] Compared with the prior art, the present invention has the following beneficial effects:

[0041] The present invention proposes a method for determining qubit parameter drift. This method utilizes a first directed acyclic graph (DAG) and the physical model to determine whether a first parameter has drifted. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be measured in the first DAG. Based on the scheme proposed in this application for determining whether qubit parameters have shifted, no manual intervention is required, enabling rapid determination of qubit parameter drift and improving the execution efficiency of quantum computing tasks to a certain extent.

[0042] The calibration method for qubit parameters, the device for determining qubit parameter drift, the quantum control system, the quantum computer, and the readable storage medium proposed in this invention belong to the same inventive concept as the method for determining qubit parameter drift, and therefore have the same beneficial effects, which will not be elaborated here. Attached Figure Description

[0043] Figure 1 This is a flowchart illustrating a method for determining quantum bit parameter drift according to an embodiment of the present invention.

[0044] Figure 2 This is a schematic diagram of a first directed acyclic graph shown in an embodiment of the present invention;

[0045] Figure 3 The modulation curve of the DC voltage on the reading resonant cavity;

[0046] Figure 4 The modulation curve of the cavity frequency on the amplitude of the read signal;

[0047] Figure 5 This is a schematic diagram of a device for determining the drift of qubit parameters according to another embodiment of the present invention. Detailed Implementation

[0048] The specific embodiments of the present invention will now be described in more detail with reference to the accompanying drawings. The advantages and features of the present invention will become clearer from the following description and claims. It should be noted that the drawings are all in a very simplified form and use non-precise proportions, and are only used to facilitate and clarify the illustration of the embodiments of the present invention.

[0049] In the description of this invention, it should be understood that the terms "center", "upper", "lower", "left", "right", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this invention.

[0050] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this invention, "a plurality of" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0051] Please refer to Figure 1 This invention proposes a method for determining the drift of qubit parameters, including:

[0052] S10: Obtain a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters;

[0053] S20: Obtain a physical model of the parameters to be measured for the sub-bit to be measured, wherein the physical model is used to obtain the theoretical expected value of the parameters to be measured;

[0054] S30: Use the first directed acyclic graph and the physical model to determine whether the first parameter has drifted. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph.

[0055] Unlike existing technologies, the method for determining qubit parameter drift proposed in this embodiment utilizes the first directed acyclic graph and the physical model to determine whether a first parameter has drifted. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be measured in the first directed acyclic graph. Based on the scheme for determining whether qubit parameters have shifted proposed in this application, no manual intervention is required, enabling rapid determination of qubit parameter drift and improving the execution efficiency of quantum computing tasks to a certain extent.

[0056] To facilitate understanding of the technical solution of this application, in this embodiment, all the first directed acyclic graphs are represented as... Figure 2 For example, please refer to the directed acyclic graph shown in the figure. Figure 2 Each node represents a different qubit parameter, such as the parameters of a single-bit logic gate or the parameters of a qubit control signal. The parameters of a single-bit logic gate include, but are not limited to, the voltage amplitude of the pi pulse or the frequency of the readout pulse, the pi pulse length, the pi / 2 pulse length, the pi pulse amplitude, and the pi / 2 pulse amplitude. The parameters of a qubit control signal include, but are not limited to, the readout pulse frequency, the readout pulse length, and the readout pulse power. There are many other qubit parameters, which will not be listed here. The specific parameters can be determined according to the type and characteristics of the qubit. Figure 2 The directed acyclic graph in the diagram illustrates the dependencies of the parameters of each qubit. The backward node is influenced by the forward node (i.e., the dependent node) that has a connection relationship with it. The forward node refers to the starting point of the arrow in the diagram, and the backward node refers to the point to which the arrow points. Of course, the forward node and the backward node are relative definitions and are not fixed for a particular node. For example, node 2 is the backward node of node 1 and also the forward node of node 3. Therefore, node 2 is influenced by node 1, and node 2 also influences node 3. Other nodes are similar, and will not be elaborated on here. Figure 2 Node 1 is the starting node of the entire directed acyclic graph, and node 13 is the ending node of the entire directed acyclic graph.

[0057] As will be understood by those skilled in the art, in a quantum computer, a quantum chip is a processor that performs quantum computing. The quantum chip integrates multiple one-to-one corresponding and mutually coupled qubits and readout resonant cavities. The portion of each readout resonant cavity furthest from its corresponding qubit is connected to a readout signal transmission line integrated on the quantum chip. Each qubit is coupled to an XY signal transmission line and a Z signal transmission line. The XY signal transmission line is used to receive quantum state modulation signals, and the Z signal transmission line is used to receive magnetic flux modulation signals. The magnetic flux modulation signals include a bias voltage signal (DC voltage) and / or a pulse bias modulation signal. Both the bias voltage signal and the pulse bias modulation signal can modulate the frequency of the qubit. The readout signal transmission line is used to receive readout detection signals and transmit readout feedback signals.

[0058] Additionally, it's important to note that the execution process of quantum computing can be summarized as follows: The frequency of the qubit is adjusted to its operating frequency using a magnetic flux modulation signal on the Z-signal transmission line. Then, a quantum state modulation signal is applied through the XY-signal transmission line to manipulate the initial state of the qubit. Finally, a readout resonant cavity is used to read the quantum state of the manipulated qubit. Specifically, a frequency-increasing pulse signal, commonly called a readout probe signal, is applied through the readout signal transmission line. This readout probe signal is typically a microwave signal with a frequency of 4-8 GHz. The quantum state of the qubit is determined by analyzing the readout feedback signal output from the readout signal transmission line. The fundamental reason why the readout resonant cavity can read the quantum state of a qubit is that different quantum states of the qubit produce different dispersion frequency shifts in response to the readout probe signal applied to the readout resonant cavity. This results in different responses from different quantum states of the qubit to the readout probe signal applied to the readout resonant cavity; this response signal is called the readout feedback signal. Only when the carrier frequency of the read detection signal of the qubit is very close to the natural frequency (also called the resonant frequency) of the read resonant cavity will the read resonant cavity show a significant difference in the response of the qubit to the read detection signal due to different quantum states, that is, the read feedback signal has maximum distinguishability.

[0059] In this embodiment of the invention, the physical model is used to obtain the theoretical expected value of the parameter to be measured. A corresponding physical model is established for each node in the first directed acyclic graph. Each node's physical model represents a theoretical expectation of the experimental data for that node. By fitting the experimental results to the physical model and comparing them with the theoretical expected value, the consistency between the experimental results and the physical model's theoretical expectation is verified. When the experimental results of a node fail to meet the theoretical expectation of the physical model, we consider it to be due to a drift in its preceding node, i.e., the dependent node. This method allows for rapid identification of which parameter of the qubit has drifted. To facilitate understanding of the technical solutions of this application by those skilled in the art, the following examples of physical models for several qubit parameters are provided for illustration:

[0060] Suppose that a node in the first directed acyclic graph is used to acquire the modulation of the DC voltage on the read resonant cavity. For ease of understanding, we can assume that this node is... Figure 2 Node 2, which mainly reflects the coupling between the readout resonant cavity and the qubit through experiments, has the following physical model established by the applicant for its parameters:

[0061] DC voltage modulates the reading resonant cavity. r (v) satisfies:

[0062]

[0063] Among them, f q (v) represents the modulation of the quantum bit frequency by the DC voltage, g represents the coupling strength between the readout resonant cavity and the quantum bit, δ represents the detuning difference between the quantum bit and the readout resonant cavity, and f c The anharmonic quantity representing a qubit.

[0064] Please refer to Figure 3 ,in, Figure 3 Curve A represents the modulation curve of DC voltage on the reading resonant cavity obtained from the fitting experimental results, while curve B represents the modulation curve of DC voltage on the reading resonant cavity in the physical model. It can be seen that although the experimental results do not completely match the physical model, the results are acceptable. In some applications with high tolerance, the experimental results can be considered to meet the requirements.

[0065] Assumption Figure 2 Node 3 is the location used to test the cavity frequency when the DC voltage is at its maximum value and in the 0-state reading. The cavity frequency refers to the frequency at which the resonant cavity is read. The applicant has established the following physical model for the parameters of this node:

[0066]

[0067] In this context, A1, A2, A3, and A4 are all pre-configured coefficients, fr represents the cavity frequency in the 0 state, Q1 represents the quality factor of the resonant cavity, y represents the amplitude of the read signal (the result of our experimental measurement), x represents the cavity frequency, and x is the quantity to be scanned in this experiment.

[0068] Please refer to Figure 4 ,in, Figure 4 The C-curve represents the modulation curve of the cavity frequency on the amplitude of the read signal obtained from the fitting experiment, while the D-curve represents the modulation curve of the cavity frequency on the amplitude of the read signal in the physical model. It can be seen that although the experimental results do not perfectly match the physical model, the results are acceptable. In some applications with high tolerance, the experimental results can be considered satisfactory. However, in some applications with lower tolerance, the experimental results are considered unsatisfactory. In such cases, we need to combine... Figure 2 The directed acyclic graph can determine that the parameter corresponding to node 2 has shifted. Those skilled in the art will understand that in practical applications, the number of parameters to be measured is large, and therefore there are many corresponding physical models. This embodiment only exemplifies two of them; there are many other types of physical models, which will not be elaborated upon here.

[0069] Specifically, in this embodiment, determining whether the first parameter has drifted using the first directed acyclic graph and the physical model includes:

[0070] A first test experiment is performed on the sub-bit to be measured to obtain the experimental results of the parameter to be measured. The first test experiment is an experiment in which the sub-bit to be measured is used to obtain the parameter to be measured.

[0071] The first parameter is obtained based on the first directed acyclic graph;

[0072] Based on the physical model and the experimental results, determine whether the first parameter has drifted.

[0073] Those skilled in the art will understand that the first test experiment corresponds to the experiment for the parameter to be tested, for example, Figure 2 The first test experiment corresponding to node 2 is the experiment of obtaining the modulation of the reading resonant cavity by the DC voltage, and the first test experiment corresponding to node 3 is the experiment of the modulation of the reading signal amplitude by the cavity frequency.

[0074] Further, determining whether the first parameter has drifted based on the physical model and the experimental results includes:

[0075] The degree of deviation of the experimental results is obtained based on the physical model.

[0076] Based on the degree of offset, it is determined whether the first parameter has drifted.

[0077] It should be noted that, in this embodiment, the degree of deviation refers to the degree of deviation between the experimental results and the physical model, for example... Figure 3 curves A and B, and Figure 4 Curve C and curve D.

[0078] Different application scenarios have different requirements for the magnitude of the offset. For some nodes with low precision requirements, experimental results deviating within a certain range may be acceptable. In this case, the threshold for the offset can be set relatively large. However, for some nodes with high precision requirements, the experimental results need to be very close to the physical model. In this case, the threshold for the offset needs to be set relatively small. In this embodiment, determining whether the first parameter has drifted based on the offset includes:

[0079] Determine whether the degree of offset is within a preset range;

[0080] If so, then it is determined that the first parameter has not drifted;

[0081] If not, then it is determined that the first parameter has drifted.

[0082] Specifically, obtaining the degree of deviation of the experimental results through the physical model includes:

[0083] The theoretical expected value of the parameter to be measured is obtained using the physical model.

[0084] The degree of deviation of the experimental results is obtained based on the theoretical expected value.

[0085] Those skilled in the art will understand that, in this embodiment, obtaining the theoretical expected value of the parameter to be measured using the physical model is actually obtaining the fitting curve of the parameter to be measured using the physical model, similar to... Figure 3 Curve B and Figure 4 Curve D in the diagram.

[0086] To obtain the degree of deviation of the experimental results, the applicant proposes to use goodness of fit, which refers to how well the regression line fits the observed values. This mainly involves using the coefficient of determination and the regression standard deviation to test the model's fit to the sample observations. When the explanatory variables are multivariate, an adjusted goodness of fit should be used to address the impact of increasing variable elements on the goodness of fit. Assuming a population can be divided into r classes, a sample is obtained from this population—this is a batch of categorical data. We need to use this categorical data to determine whether the probability of each class in the population occurs matches the known probabilities. For example, to test whether a die is fair, the die can be rolled several times, and the number of times each face appears can be recorded. From this data, we can test whether the probability of each face appearing is always 1 / 6. The goodness of fit test is used to test whether the distribution of the population from which a batch of categorical data comes is consistent with a certain theoretical distribution. Specifically, obtaining the degree of deviation of the experimental results based on the theoretical expected value includes:

[0087] The degree of deviation is obtained by using goodness of fit to the theoretical expected value and the experimental results.

[0088] In this embodiment, obtaining the degree of deviation by using goodness of fit on the theoretical expected value and the experimental results includes:

[0089] Construct the first formula, which is:

[0090]

[0091] Among them, R 2 For the degree of offset, y fit For the theoretical expected value, y raw The experimental results are given, and the average value of the experimental results is given.

[0092] The degree of offset is obtained using the first formula.

[0093] It should be noted that the R 2 The closer the value of is to 1, the smaller the offset. For example, Figure 3 R in 2 The value is 0.955, indicating that Figure 3 The experimental results did not deviate too much from the physical model. Figure 4 Chinese R 2 The value is 0.914, which indicates that the deviation of the experimental results in the soil from the physical model is within an acceptable range. However, it is unacceptable for some applications requiring high precision. The value can be adjusted according to actual needs, and no restrictions are imposed here.

[0094] Based on the same inventive concept, this application also proposes a method for calibrating qubit parameters. The method for determining whether a qubit parameter has drifted, as described in any of the above-described features, is used to determine the first parameter. If the determination result is yes, the first parameter is calibrated.

[0095] Please refer to Figure 5 Based on the same inventive concept, embodiments of this application also propose a device for determining the drift of quantum bit parameters, comprising:

[0096] A directed acyclic graph acquisition module 100 is configured to acquire a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters.

[0097] The physical model acquisition module 200 is configured to acquire a physical model of the measured parameters of the measured sub-bit, the physical model being used to acquire the theoretical expected value of the measured parameters.

[0098] The parameter drift determination module 300 is configured to determine whether a first parameter has drifted using the first directed acyclic graph and the physical model. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph.

[0099] It is understood that the directed acyclic graph acquisition module 100, the physical model acquisition module 200, and the parameter drift determination module 300 can be implemented in a single device, or any one of these modules can be split into multiple sub-modules. Alternatively, at least some of the functions of one or more of the directed acyclic graph acquisition module 100, the physical model acquisition module 200, and the parameter drift determination module 300 can be combined with at least some of the functions of other modules and implemented in a single functional module. According to embodiments of the present invention, at least one of the directed acyclic graph acquisition module 100, the physical model acquisition module 200, and the parameter drift determination module 300 can be at least partially implemented as hardware circuitry, such as a field-programmable gate array (FPGA), a programmable logic array (PLA), a system-on-a-chip, a system-on-a-substrate, a system-on-package, an application-specific integrated circuit (ASIC), or can be implemented in hardware or firmware in any other reasonable manner by integrating or packaging the circuitry, or in a suitable combination of software, hardware, and firmware implementations. Alternatively, at least one of the directed acyclic graph acquisition module 100, the physical model acquisition module 200, and the parameter drift judgment module 300 can be at least partially implemented as a computer program module, which can perform the functions of the corresponding module when the program is run by a computer.

[0100] Based on the same inventive concept, this application also proposes a quantum control system, which uses the method for judging the drift of quantum bit parameters described in any of the above-described features to judge the first parameter, or includes the device for judging the drift of quantum bit parameters as described in the above-described features.

[0101] Based on the same inventive concept, embodiments of this application also propose a quantum computer, including the quantum control system described in the above feature description.

[0102] Based on the same inventive concept, embodiments of this application also propose a readable storage medium storing a computer program thereon. When the computer program is executed by a processor, it can implement the method for determining the drift of the quantum bit parameters as described in any of the above-described features, or implement the method for calibrating the quantum bit parameters as described in the above-described features.

[0103] The readable storage medium can be a tangible device capable of holding and storing instructions for use by an instruction execution device, such as, but not limited to, electrical storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any suitable combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), static random access memory (SRAM), portable compact disc read-only memory (CD-ROM), digital multifunction disc (DVD), memory sticks, floppy disks, mechanical encoding devices, such as punch cards or recessed protrusions storing instructions thereon, and any suitable combination thereof. The computer programs described herein can be downloaded from the readable storage medium to various computing / processing devices, or downloaded via a network, such as the Internet, local area network, wide area network, and / or wireless network, to an external computer or external storage device. The network can include copper transmission cables, fiber optic transmission, wireless transmission, routers, firewalls, switches, gateway computers, and / or edge servers. Each computing / processing device's network adapter card or network interface receives the computer program from the network and forwards it for storage in a readable storage medium within the respective computing / processing device. The computer program used to perform the operations of this invention can be assembly instructions, instruction set architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, or source code or object code written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Smalltalk, C++, etc., and conventional procedural programming languages ​​such as "C" or similar languages. The computer program can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, electronic circuits, such as programmable logic circuits, field-programmable gate arrays (FPGAs), or programmable logic arrays (PLAs), are personalized by utilizing state information from a computer program. These electronic circuits can execute computer-readable program instructions, thereby realizing various aspects of the present invention.

[0104] Various aspects of the present invention are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of the invention. It should be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by a computer program. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that, when executed by the processor of the computer or other programmable data processing apparatus, they create means for implementing the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. These computer programs can also be stored in a readable storage medium that causes a computer, programmable data processing apparatus, and / or other device to operate in a particular manner; thus, the readable storage medium storing the computer program comprises an article of manufacture including instructions for implementing aspects of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams.

[0105] A computer program may also be loaded onto a computer, other programmable data processing apparatus, or other device to cause a series of operational steps to be performed on the computer, other programmable data processing apparatus, or other device to produce a computer-implemented process, thereby causing the computer program executing on the computer, other programmable data processing apparatus, or other device to perform the functions / actions specified in one or more boxes of a flowchart and / or block diagram.

[0106] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," or "specific example," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments. In addition, those skilled in the art can combine and integrate the different embodiments or examples described in this specification.

[0107] The above are merely preferred embodiments of the present invention and do not constitute any limitation on the present invention. Any equivalent substitutions or modifications made by those skilled in the art to the technical solutions and content disclosed in the present invention without departing from the scope of the present invention shall be deemed to have remained within the protection scope of the present invention.

Claims

1. A method for determining the drift of quantum bit parameters, characterized in that, include: Obtain a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters; A physical model is obtained for the measured parameters of the sub-bit to be measured, and the physical model is used to obtain the theoretical expected value of the measured parameters; The first parameter is determined to have drifted by using the first directed acyclic graph and the physical model. The first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph. The step of determining whether the first parameter has drifted using the first directed acyclic graph and the physical model includes: A first test experiment is performed on the sub-bit to be measured to obtain the experimental results of the parameter to be measured. The first test experiment is an experiment in which the sub-bit to be measured is used to obtain the parameter to be measured. The first parameter is obtained based on the first directed acyclic graph; Based on the physical model and the experimental results, determine whether the first parameter has drifted; The step of determining whether the first parameter has drifted based on the physical model and the experimental results includes: The degree of deviation of the experimental results is obtained based on the physical model. Based on the degree of offset, determine whether the first parameter has drifted; The degree of deviation of the experimental results is obtained through the physical model, including: The theoretical expected value of the parameter to be measured is obtained using the physical model. The degree of deviation of the experimental results is obtained based on the theoretical expected value; The process of obtaining the degree of deviation of the experimental results based on the theoretical expected value includes: The degree of deviation is obtained by using goodness of fit to the theoretical expected value and the experimental results.

2. The method as described in claim 1, characterized in that, The step of determining whether the first parameter has drifted based on the degree of offset includes: Determine whether the degree of offset is within a preset range; If so, then it is determined that the first parameter has not drifted; If not, then it is determined that the first parameter has drifted.

3. The method as described in claim 1, characterized in that, The process of obtaining the degree of deviation by using goodness-of-fit on the theoretical expected value and the experimental results includes: Construct the first formula, which is: Among them, R 2 For the degree of offset, y fit For the theoretical expected value, y raw The experimental results are as described. The average value of the experimental results; The degree of offset is obtained using the first formula.

4. A method for calibrating quantum bit parameters, characterized in that, The first parameter is judged using the method for judging the drift of the quantum bit parameter as described in any one of claims 1-3, and when the judgment result is yes, the first parameter is calibrated.

5. A device for determining the drift of quantum bit parameters, characterized in that, include: A directed acyclic graph acquisition module is configured to acquire a first directed acyclic graph, which is used to characterize multiple qubit parameters of the sub-bit to be measured and the dependencies between the multiple qubit parameters. A physical model acquisition module is configured to acquire a physical model of the measured parameters of the measured sub-bit, wherein the physical model is used to acquire the theoretical expected value of the measured parameters. The parameter drift judgment module is configured to use the first directed acyclic graph and the physical model to determine whether the first parameter has drifted, wherein the first parameter is the qubit parameter corresponding to the dependent node position of the parameter to be tested in the first directed acyclic graph; The parameter drift determination module is configured as follows: A first test experiment is performed on the sub-bit to be measured to obtain the experimental results of the parameter to be measured. The first test experiment is an experiment in which the sub-bit to be measured is used to obtain the parameter to be measured. The first parameter is obtained based on the first directed acyclic graph; Based on the physical model and the experimental results, determine whether the first parameter has drifted; The parameter drift determination module is configured as follows: The degree of deviation of the experimental results is obtained based on the physical model. Based on the degree of offset, determine whether the first parameter has drifted; The parameter drift determination module is configured as follows: The theoretical expected value of the parameter to be measured is obtained using the physical model. The degree of deviation of the experimental results is obtained based on the theoretical expected value; The parameter drift determination module is configured as follows: The degree of deviation is obtained by using goodness of fit to the theoretical expected value and the experimental results.

6. A quantum control system, characterized in that, The first parameter is determined using the method for determining quantum bit parameter drift as described in any one of claims 1-3, or the method includes the device for determining quantum bit parameter drift as described in claim 5.

7. A quantum computer, characterized in that, Including the quantum control system as described in claim 6.

8. A readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it can implement the method for determining the drift of the quantum bit parameters as described in any one of claims 1 to 3, or the method for calibrating the quantum bit parameters as described in claim 4.

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