Method, apparatus, device, and storage medium for determining resonator parameters

Abstract

The present disclosure provides a method, apparatus, device, and storage medium for determining resonator parameters, relating to the field of computer technologies, and particularly to the fields of quantum computers, quantum chips, and quantum signal technologies. The specific implementation solution is as follows: obtaining a signal experimental value of a target signal, where the signal experimental value of the target signal is obtained based on an actual input signal of the target resonator and an actual output signal of the target resonator; based on the signal experimental value of the target signal and a target model for determining characteristic parameters of the target resonator, obtaining target parameter values of respective first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonator, and obtaining target parameter values of respective second characteristic parameters characterizing the ideal resonance characteristic information of the target resonator; the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonator, and the ideal resonance characteristic information of the target resonator.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technologies, and particularly to the fields of quantum computers, quantum chips, and quantum signal technologies. Background Art

[0002] The measurement of the state of a quantum bit is an essential step in quantum computing. The measurement of the state of a quantum bit can be achieved by operating and measuring a read resonator (which can be simply referred to as a resonator) in a quantum computer. And obtaining multiple characteristic parameters of the read resonator is a prerequisite for operating and measuring the read resonator. Therefore, how to automatically determine multiple characteristic parameters of the read resonator has become an issue worthy of attention. Summary of the Invention

[0003] The present disclosure provides a method, an apparatus, a device, and a storage medium for determining resonator parameters.

[0004] According to one aspect of the present disclosure, a method for determining resonator parameters is provided, including:

[0005] Obtaining a signal experimental value of a target signal, where the signal experimental value of the target signal is obtained based on an actual input signal and an actual output signal of the target resonator;

[0006] Based on the signal experimental value of the target signal and a target model for determining characteristic parameters of the target resonator, obtaining a target parameter value of each first characteristic parameter among N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonator, and obtaining a target parameter value of each second characteristic parameter among N2 second characteristic parameters characterizing the ideal resonance characteristic information of the target resonator;

[0007] wherein the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonator, and the ideal resonance characteristic information of the target resonator; N1 and N2 are positive integers greater than or equal to 1.

[0008] According to another aspect of the present disclosure, a device for determining resonator parameters is provided, including:

[0009] A determination unit, configured to obtain a signal experimental value of a target signal, where the signal experimental value of the target signal is obtained based on an actual input signal and an actual output signal of the target resonator;

[0010] A parameter processing unit, configured to obtain, based on the signal experimental value of a target signal and a target model for determining characteristic parameters of the target resonator, target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonator, and obtain target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonance characteristic information of the target resonator;

[0011] Wherein, the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonator, and the ideal resonance characteristic information of the target resonator; N1 and N2 are positive integers greater than or equal to 1.

[0012] According to another aspect of the present disclosure, there is provided a computing device, including:

[0013] At least one quantum processing unit QPU;

[0014] A memory, coupled to the at least one QPU and configured to store executable instructions,

[0015] The instructions are executed by the at least one QPU, so that the at least one QPU can execute the method described above;

[0016] Or, including:

[0017] At least one processor; and

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor, so that the at least one processor can execute the method described above.

[0020] According to another aspect of the present disclosure, there is provided a non-transitory computer-readable storage medium storing computer instructions, when executed by at least one quantum processing unit, the computer instructions cause the at least one quantum processing unit to execute the method described above;

[0021] Or, the computer instructions are used to cause a computer to execute the method described above.

[0022] According to another aspect of the present disclosure, there is provided a computer program product, including a computer program, the computer program realizes the method described above when executed by at least one quantum processing unit;

[0023] Or the computer program realizes the method described above when executed by a processor.

[0024] In this way, the present disclosure solution can obtain the specific values of the characteristic parameters that can characterize the target resonant cavity based on the signal experimental values of the target signal and the pre-determined target model. Moreover, since the pre-determined target model not only includes the part that characterizes the ideal resonance characteristic information, that is, N2 second characteristic parameters, but also includes the part that characterizes the measurement and control environment characteristic information, that is, N1 first characteristic parameters. Thus, the target parameter values of the characteristic parameters obtained can fully characterize the target resonant cavity, and further provide strong support for precise measurement or operation using the target resonant cavity. Moreover, the above process does not require manual participation, so it effectively saves human resources; at the same time, the above process significantly improves the robustness.

[0025] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it used to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The drawings are used to better understand the solution of the present disclosure and do not constitute a limitation to the present disclosure. Among them:

[0027] Figure 1 is a schematic flowchart of the implementation process of the method for determining the resonant cavity parameters according to the embodiment of the present disclosure Figure 1 ;

[0028] Figure 2 is a schematic diagram of the coupling between the target resonant cavity and the qubit according to the embodiment of the present disclosure;

[0029] Figure 3 is a schematic flowchart of the implementation process of the method for determining the resonant cavity parameters according to the embodiment of the present disclosure Figure 2 ;

[0030] Figure 4 is a general implementation flowchart of extracting the characteristic parameters of the resonant cavity according to the embodiment of the present disclosure;

[0031] Figure 5 is a flowchart of the implementation of the electronic delay algorithm according to the embodiment of the present disclosure;

[0032] Figure 6 is a schematic diagram of the fitting effect in an example of the method for determining the resonant cavity parameters according to the embodiment of the present disclosure Figure 1 ;

[0033] Figure 7 is a schematic diagram of the fitting effect in an example of the method for determining the resonant cavity parameters according to the embodiment of the present disclosure Figure 2 ;

[0034] Figure 8 is a schematic diagram of the fitting effect in an example of the method for determining the resonant cavity parameters according to the embodiment of the present disclosureFigure 3 ;

[0035] Figure 9 It is a comparison diagram of the signal experimental values in an example of the method for determining the resonant cavity parameters according to the embodiments of the present disclosure and the estimated values calculated based on the respective characteristic parameters obtained after fitting.

[0036] Figure 10 It is a schematic structural diagram of the device for determining the resonant cavity parameters according to the embodiments of the present disclosure.

[0037] Figure 11 It is a block diagram of a computing device for implementing the method for determining the resonant cavity parameters according to the embodiments of the present disclosure. Detailed implementation manners

[0038] The following describes exemplary embodiments of the present disclosure with reference to the accompanying drawings. Various details of the embodiments of the present disclosure are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0039] The term "and / or" in this document merely describes the association relationship of associated objects and indicates that three relationships can exist. For example, A and / or B can represent: A exists alone, A and B exist simultaneously, and B exists alone. The term "at least one" in this document means any one of multiple types or any combination of at least two of multiple types. For example, including at least one of A, B, and C can represent including any one or more elements selected from the set composed of A, B, and C. The terms "first" and "second" in this document represent referring to multiple similar technical terms and distinguishing them, and do not mean limiting the order or limiting to only two. For example, the first feature and the second feature refer to two types / two features. The first feature can be one or more, and the second feature can also be one or more.

[0040] In addition, for better illustration of the present disclosure, numerous specific details are given in the following detailed implementation manners. Those skilled in the art should understand that the present disclosure can still be implemented without some specific details. In some instances, methods, means, elements, and circuits well-known to those skilled in the art are not described in detail to highlight the gist of the present disclosure.

[0041] Quantum computers have powerful information processing capabilities and have received great attention. In quantum computing, the measurement of the state of qubits (i.e., qubit state) is an essential part. To measure the state of qubits, a device called a readout resonator (which can also be called a resonator or a readout cavity) in a quantum computer can be used to achieve the reading of the qubit state. As a basic physical device, resonators have found extensive applications in the fields of quantum information processing, photon detection, quantum storage, etc. In the field of quantum computing, generally, a resonator is coupled with qubits, and the state of the qubits is measured by measuring the resonator, thereby achieving the reading of the qubits.

[0042] A fundamental task in resonator research is to determine the characteristic parameters of the resonator, such as determining characteristic parameters like the quality factor (Q factor) and resonator frequency. Obtaining the characteristic parameters of the resonator is a prerequisite for operating and measuring the resonator. In addition, accurately obtaining characteristic parameters such as the Q factor of the resonator also has important guiding significance for guiding the design of the resonator and improving the performance of the resonator.

[0043] Based on this, the present disclosure proposes a method for determining the characteristic parameters of a resonator to obtain the parameter values of the characteristic parameters that characterize the measurement and control environment characteristic information of the resonator, as well as the parameter values of the characteristic parameters that characterize the ideal resonance characteristic information of the resonator. In this way, it lays a foundation for subsequent efficiently obtaining the state of qubits.

[0044] Specifically, Figure 1 is a schematic implementation flow of the method for determining resonator parameters according to an embodiment of the present disclosure Figure 1 ; This method can optionally be applied to a quantum computing device with classical computing capabilities, or can also be applied to a classical computing device with quantum computing capabilities, or directly applied to a classical computing device, such as an electronic device with classical computing capabilities like a personal computer, a server, a server cluster, etc., or directly applied to a quantum computer. The present disclosure scheme does not limit this.

[0045] Furthermore, the method includes at least part of the following content. As Figure 1 shown, it includes:

[0046] Step S101: Obtain the signal experimental value of the target signal.

[0047] In one example, the signal experimental value of the target signal is obtained based on the actual input signal and the actual output signal of the target resonator; for example, in one example, the target signal can be specifically the S 21 signal, and this S 21The signal refers to the ratio of the actual input signal of the target resonant cavity to the actual output signal of the target resonant cavity.

[0048] Step S102: Based on the signal experimental value of the target signal and the target model for determining the characteristic parameters of the target resonant cavity, obtain the target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonant cavity, and obtain the target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonance characteristic information (which can also be referred to as the ideal resonant cavity signal information and can refer to the ideal resonant cavity signal) of the target resonant cavity.

[0049] Here, N1 and N2 are positive integers greater than or equal to 1.

[0050] Furthermore, the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonant cavity, and the ideal resonance characteristic information of the target resonant cavity. More specifically, the target model is used to characterize the correlation relationship between the signal value of the target signal, the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonant cavity, and the N2 second characteristic parameters characterizing the ideal resonance characteristic information of the target resonant cavity. For example, in one example, the target model can be represented by a general formula characterizing the correlation relationship among the above three.

[0051] In this way, the solution of the present disclosure can obtain the specific values of the characteristic parameters that can characterize the target resonant cavity based on the signal experimental value of the target signal and the pre-determined target model; moreover, since the pre-determined target model not only includes the part characterizing the ideal resonance characteristic information, that is, the N2 second characteristic parameters, but also includes the part characterizing the measurement and control environment characteristic information, that is, the N1 first characteristic parameters, thus, the obtained target parameter values of each characteristic parameter can fully characterize the target resonant cavity, thereby providing strong support for accurate measurement or operation using the target resonant cavity. Moreover, the above process does not require manual participation, so it effectively saves human resources; at the same time, the above process significantly improves the robustness.

[0052] In addition, since the solution of the present disclosure can not only obtain the specific values of the characteristic parameters characterizing the ideal resonance characteristic information, but also obtain the specific values of the characteristic parameters characterizing the measurement and control environment characteristic information, it also has important guiding significance for guiding the design of the resonant cavity and improving the performance of the resonant cavity.

[0053] In a specific example, after obtaining the target parameter values of each first characteristic parameter and the target parameter values of each second characteristic parameter, the target resonator can also be measured or operated based on the target parameter values of each first characteristic parameter among the N1 first characteristic parameters and the target parameter values of each second characteristic parameter among the N2 second characteristic parameters, so as to implement specific quantum tasks in the fields of quantum information processing, photon detection, quantum storage, etc.

[0054] For example, as Figure 2 shown, a schematic diagram of the coupling between the target resonator and the qubit is provided. In this scenario, after obtaining the target parameter values of each first characteristic parameter and the target parameter values of each second characteristic parameter, the target resonator can be measured based on the target parameter values of each first characteristic parameter and the target parameter values of each second characteristic parameter, so as to obtain the state of the qubit coupled to the target resonator.

[0055] In this way, since the solution of the present disclosure can automatically extract the target parameter values of each characteristic parameter of the target resonator by using the target model, and the extracted characteristic parameters can not only represent the ideal resonance characteristic information, but also represent the measurement and control environment characteristic information, in the scenario of measuring the target resonator based on the target parameter values of each characteristic parameter, the measurement accuracy is effectively improved, thus providing strong support for subsequent operations or research.

[0056] Further, in a specific example, the first characteristic parameter among the N1 first characteristic parameters is at least one of the following: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonator is located, and the electronic delay.

[0057] That is to say, in this example, the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonator is located, and the electronic delay can all be regarded as the influencing factors of the measurement and control environment characteristic information.

[0058] For example, in an example, the measurement and control environment characteristic information can be characterized by the following four parameters: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonator is located, and the electronic delay.

[0059] In this way, the solution of the present disclosure provides specific parameters for characterizing the measurement and control environment characteristic information. For example, the measurement and control environment characteristic information of the target resonator can be characterized by one or more of the above-mentioned parameters. The types of parameters are numerous and the range is wide, which provides support for comprehensively and accurately characterizing the measurement and control environment characteristic information. Furthermore, it is beneficial to more accurately characterize the target resonator and provides data support for realizing accurate measurement or accurate operation of the target resonator.

[0060] Further, in a specific example, the measurement and control environment characteristic information of the target resonator is represented by the following formula:

[0061]

[0062] where A represents the environmental amplitude of the environment where the target resonator is located, η represents the inclination degree of the target signal, α represents the environmental phase of the environment where the target resonator is located, τ represents the electronic delay. Further, f 0 represents the frequency of the target resonator.

[0063] In this way, the solution of the present disclosure provides a specific example of jointly characterizing the measurement and control environment characteristic information by using the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonator is located, the electronic delay, and the frequency of the target resonator. Thus, it is beneficial to more accurately characterize the target resonator and provides data support for realizing accurate measurement or accurate operation of the target resonator.

[0064] Further, in another specific example, the second characteristic parameter among the N2 second characteristic parameters is at least one of the following: the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch.

[0065] That is to say, in this example, the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch can all be regarded as influencing factors of the ideal resonance characteristic information.

[0066] For example, in an example, the ideal resonance characteristic information can be characterized by the following four parameters: the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch.

[0067] In this way, the solution of the present disclosure provides specific parameters for characterizing the ideal resonance characteristic information. For example, the ideal resonance characteristic information of the target resonator can be characterized by one or more of the above-mentioned parameters. The types of parameters are numerous and the range is wide, which provides support for comprehensively and accurately characterizing the ideal resonance characteristic information. Furthermore, it is beneficial to more accurately characterize the target resonator and provides data support for realizing accurate measurement or accurate operation of the target resonator.

[0068] Further, in another specific example, the ideal resonance characteristic information of the target resonator is represented by the following formula:

[0069]

[0070] where f 0 represents the frequency of the target resonator, Qi represents the internal quality factor of the target resonator, Q c represents the external quality factor of the target resonator, and φ is the phase caused by impedance mismatch.

[0071] In this way, the present disclosure provides a specific example of jointly characterizing the ideal resonance characteristic information by using the frequency, internal quality factor, external quality factor, and phase caused by impedance mismatch of the target resonator. Thus, it is beneficial to more accurately characterize the target resonator and provides data support for realizing accurate measurement or accurate operation of the target resonator.

[0072] It should be noted that generally, in order to obtain the characteristic parameters of the target resonator, when obtaining the signal experimental value of the S 21 signal of the target resonator, the signal experimental value can be fitted with a preset resonator theoretical model. For example, the signal experimental value can be fitted with the resonator theoretical model through a fitting algorithm or a fitting tool, etc. In this way, the characteristic parameters of the target resonator are extracted by using the resonator theoretical model. However, the existing resonator theoretical model can only characterize the resonator signal in the ideal state. In other words, the target resonator will be affected by factors such as the measurement and control environment, and the resonator theoretical model usually cannot effectively express it. Therefore, in the existing solutions, it is relatively complicated and highly challenging to robustly obtain the characteristic parameters of the target resonator.

[0073] Based on this, in one example, the present disclosure provides a target model that can not only characterize the ideal resonance characteristic information but also characterize the measurement and control environment characteristic information. Thus, it can more accurately characterize the target resonator. The expression of the target model can be specifically:

[0074]

[0075] Here, f represents the frequency of the driving signal (i.e., the actual input signal) applied to the target resonator, and S 21 (f) represents the S obtained when the frequency of the driving signal applied to the target resonator is f 21 signal, which can be simply referred to as the S 21 (f) signal. The signal experimental value of the S 21 (f) signal can be obtained based on measurement and is thus a known term. i represents the imaginary number.

[0076] In a specific example of the present disclosure solution, based on the signal experimental value of the target signal and the target model for determining the characteristic parameters of the target resonator, the target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristics of the target resonator are obtained, and the target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonance characteristics of the target resonator are obtained. For example, as Figure 3 shown, it may specifically include:

[0077] Step S301: Obtain the signal experimental value of the target signal.

[0078] Here, the signal experimental value of the target signal is obtained based on the actual input signal of the target resonator and the actual output signal of the target resonator.

[0079] Step S302: Obtain the current estimated value of the target signal obtained based on the target model. For example, taking the current estimated value as the j-th estimated value, at this time, the j-th parameter optimization process can be executed to obtain the j-th estimated value of the target signal obtained based on the target model. Here, j is a positive integer greater than or equal to 1.

[0080] It should be noted that the relevant content of the target model can be referred to the above description and will not be elaborated here.

[0081] Here, the j-th parameter optimization process in step S302 may specifically include:

[0082] Step S302-1: Determine the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter.

[0083] In a specific example, the following method can be used to estimate the current values of each characteristic parameter. For example, step S302-1 may specifically include:

[0084] When j is greater than 1, at least some of the j1-1 values of each first characteristic parameter and the j2-1 values of each second characteristic parameter obtained in the (j - 1)-th parameter optimization process are adjusted to obtain the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter. That is to say, in one example, when j is greater than 1, the values of each characteristic parameter in the current parameter optimization process (i.e., the (j - 1)-th parameter optimization process) are obtained by adjusting the values of each characteristic parameter in the previous parameter optimization process.

[0085] Or,

[0086] When j is equal to 1, based on the target model, the initial values of each first characteristic parameter and the initial values of each second characteristic parameter are calculated. That is to say,

[0087] In one example, when j is equal to 1, the values of the respective characteristic parameters can be estimated based on the target model. At this time, the estimated values of the respective characteristic parameters can be used as the initial values in the parameter optimization process.

[0088] In this way, the present disclosure provides a specific solution for obtaining the values of the respective characteristic parameters in the parameter optimization process. Thus, it is beneficial to accurately and quickly obtain the target parameter values of the respective characteristic parameters characterizing the target resonator.

[0089] Step S302-2: Substitute the j1-th value of each first parameter and the j2-th value of each second parameter into the target model to obtain the j-th estimated value.

[0090] Step S303: Determine whether the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal meets a preset difference requirement; for example, if it is determined to be satisfied, execute step S304; otherwise, if it is determined not to be satisfied, after j + 1, return to step S302.

[0091] That is to say, when it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal does not meet the preset difference requirement, perform the j + 1 parameter optimization process and obtain the (j + 1)-th estimated value of the target signal obtained based on the target model;

[0092] Furthermore, determine whether the difference between the (j + 1)-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, and so on in a loop until the preset difference requirement is met. At this time, based on the values of the respective first characteristic parameters and the values of the respective second characteristic parameters corresponding to the estimated value that meets the preset difference requirement, the target parameter values of the respective first characteristic parameters and the target parameter values of the respective second characteristic parameters can be obtained.

[0093] In a specific example, a target function can also be pre-constructed, and this target function is used to measure the degree of difference between the estimated value of the target signal and the signal experimental value of the target signal. Further, in one example, this target function can be specifically the following first target function, which will not be elaborated here.

[0094] Step S304: When it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, use the j1-th value of the first characteristic parameter as the target parameter value of the first characteristic parameter, and use the j2-th value of the second characteristic parameter as the target parameter value of the second characteristic parameter.

[0095] In this way, the present disclosure provides a specific solution for obtaining the target parameter values of the characteristic parameters characterizing the target resonator. In this solution, first, the values of the characteristic parameters are estimated. Secondly, the estimated value of the target signal is obtained by using the target model, and the estimated value of the target signal is compared with the experimental value of the target signal. Finally, parameter optimization is performed based on the comparison result. For example, the difference between the estimated value of the target signal and the experimental value of the target signal is minimized. In this way, the target parameter values of the characteristic parameters can be obtained accurately and quickly. This process is simple, efficient, and significantly improves the robustness.

[0096] In a specific example of the present disclosure solution, a step-by-step calculation method can be used to obtain the initial values of the characteristic parameters. Specifically, based on the target model described above, the initial values of the first characteristic parameters and the initial values of the second characteristic parameters are calculated, which may include at least one of the following: the first processing flow, the second processing flow, and the third processing flow.

[0097] It should be noted that, in one example, the first processing flow, the second processing flow, and the third processing flow are asynchronous processing flows. In this way, the target model is split into multiple processing flows for calculation, which can effectively improve the robustness of the present disclosure solution, and then obtain the target parameter values of the characteristic parameters efficiently and accurately.

[0098] Furthermore, the first processing flow may specifically include: processing the target signal to obtain a target signal that meets the requirements, and based on the target signal that meets the requirements, at least obtaining the initial value of the electronic delay; here, the electronic delay is the first characteristic parameter.

[0099] Furthermore, the second processing flow may specifically include: performing data processing on the target model to remove the parameters representing the electronic delay and the environmental phase of the environment where the target resonator is located, and obtaining the initial values of the following characteristic parameters: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch; among them, the environmental amplitude of the environment where the target resonator is located and the inclination degree of the target signal are both the first characteristic parameters; the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch are all the second characteristic parameters.

[0100] Furthermore, the third processing flow may specifically include: obtaining the initial value of the environmental phase of the environment where the target resonator is located.

[0101] In this way, the present disclosure provides a specific solution for obtaining the initial values of various characteristic parameters, which is beneficial to accurately and efficiently extracting the target parameter values of various characteristic parameters of the target resonant cavity based on the target model. At the same time, the robustness of the present disclosure can also be effectively improved.

[0102] In a specific example, the following method can be used to obtain the initial value of the electronic delay, that is, the above-mentioned first processing flow may specifically include the following steps 1 to 3:

[0103] Step 1: Estimate the degree of deformation of the shape of the target signal caused by the electronic delay.

[0104] For example, in an example, a target function (corresponding to the second target function mentioned above) can be constructed in advance. This second target function is used to measure the deformation degree of the shape of the target signal caused by the electronic delay τ, such as the signal S 21 (f). Then, the function value of this second target function is obtained. At this time, this function value is the estimated degree of deformation of the shape of the target signal caused by the electronic delay.

[0105] Step 2: Process the target signal based on the degree of deformation to obtain the value of the cancellation variable used to cancel the deformation of the shape of the target signal.

[0106] For example, minimize the function value of the second target function. Then, when the minimum function value of the second target function is obtained, the value of the cancellation variable used to cancel the deformation of the shape of the target signal can be obtained based on the minimum function value.

[0107] Step 3: Based on the value of the cancellation variable, obtain the initial value of the electronic delay and the center position of the signal after canceling the deformation of the shape of the target signal.

[0108] For example, the negative value of the value of the cancellation variable is the initial value of the electronic delay.

[0109] It should be noted that in this example, the target signal that meets the requirements can specifically be the signal after canceling the deformation of the shape of the target signal.

[0110] Furthermore, it should be noted that for the principle explanation of this solution, reference can be made to the relevant content of the following electronic delay algorithm, which will not be elaborated here.

[0111] In this way, the present disclosure provides a specific solution for the initial value of the electronic delay. This solution can accurately and efficiently obtain the initial value of the electronic delay, thereby providing data support for accurately and efficiently extracting the target parameter values of various characteristic parameters of the target resonant cavity. At the same time, the robustness of the present disclosure can also be effectively improved.

[0112] In a specific example, the third processing flow is executed after the first processing flow; further, in an example, the third processing flow may specifically include:

[0113] Based on the position information of the signal after the shape of the target signal is deformed to offset the target signal, an initial value of the environmental phase of the environment where the target resonator is located is obtained.

[0114] In this way, the solution of the present disclosure provides a specific solution for the initial value of the environmental phase. This solution can accurately and efficiently obtain the initial value of the environmental phase, thereby providing data support for accurately and efficiently extracting the target parameter values of the various characteristic parameters of the target resonator. At the same time, the robustness of the solution of the present disclosure can also be effectively improved.

[0115] The following further elaborates on the solution of the present disclosure in combination with specific examples; in order to overcome the difficulty of extracting the characteristic parameters of the resonator, the solution of the present disclosure first constructs a theoretical model (i.e., the target model described above). This theoretical model includes two parts, namely the measurement and control environment characteristic information part and the ideal resonance characteristic information part. Secondly, the solution of the present disclosure designs a set of special step-by-step fitting processes. In this way, using this theoretical model and this step-by-step fitting process, automated data processing is realized, so that the various characteristic parameters of the resonator can be obtained automatically and robustly.

[0116] It should be noted that since the resonator is a widely used basic device, the solution of the present disclosure has strong practicability and broad application prospects.

[0117] In addition, it should be noted that the solution of the present disclosure is not limited to the field of quantum computing. For example, the solution of the present disclosure is applicable to any application scenario in the quantum field that requires a resonator. A basic condition is that a driving signal can be applied to the resonator and the S 21 signal can be obtained.

[0118] Whether it is for an ideal resonator signal or a non-ideal resonator signal with problems such as impedance mismatch, environmental phase of the environment where the resonator is located, electronic delay (or cable delay) and signal tilt, this method can achieve a good fitting effect and extract the actual parameters of the resonator.

[0119] The following clarifies the core idea and complete technical implementation solution of the solution of the present disclosure from two parts.

[0120] The first part, overall process

[0121] The target model proposed by the present disclosure solution consists of two parts. Among them, one part represents the ideal resonator signal part (corresponding to the ideal resonance characteristic information described above), and the other part is the measurement and control environment characteristic part (corresponding to the ideal resonance characteristic information described above); the specific formula of this target model is as follows:

[0122]

[0123] Among them, is the measurement and control environment characteristic part, is the ideal oscillation signal part.

[0124] Furthermore, f represents the frequency of the driving signal (i.e., the input signal) applied to the resonator, and S 21 (f) represents the S obtained when the frequency of the driving signal applied to the resonator is f 21 signal, which can be simply referred to as the S 21 (f) signal. The experimental value of the S 21 (f) signal can be obtained based on measurement and is a known term. i represents the imaginary number.

[0125] Furthermore, A, η, α, τ, f 0 , Q i , Q c , φ are 8 characteristic parameters of the resonator to be determined in the present disclosure solution, and the parameter values of each characteristic parameter among these 8 characteristic parameters can all be real numbers. Here, A represents the environmental amplitude of the target resonator's environment, η represents the inclination degree of the S 21 (f) signal, α represents the environmental phase of the target resonator's environment, τ is the electronic delay, f 0 is the frequency of the resonator, Q i represents the internal quality factor of the resonator, Q c represents the external quality factor of the resonator, and φ represents the phase caused by impedance mismatch.

[0126] In this way, since the target model constructed by the present disclosure solution can not only express the ideal resonator signal part but also express the measurement and control environment characteristic part, compared with the existing solutions, the target parameter value of the characteristic frequency of the resonator obtained by the present disclosure solution is closer to the real scenario. In other words, it can better represent the real scenario and has higher accuracy.

[0127] Furthermore, it should be noted that the target model is very sensitive to the initial values of each characteristic parameter. Therefore, if the fitting method is directly adopted to solve the characteristic parameters of the target model, the robustness may be very poor, that is, it is very likely that the solutions of each characteristic parameter cannot be obtained. Based on this, the present disclosure provides a step-by-step fitting process to solve the problems caused by direct fitting. Specifically, in the step-by-step fitting process of the present disclosure, the three phase parameters, namely, the phase φ caused by impedance mismatch, the phase factor caused by electron delay τ (i.e., e ― i2πfτ), and the environmental phase α, need to be processed separately; based on this, according to the characteristics of the signal, three different data processing processes are adopted to respectively obtain the initial values of the characteristic parameters of the resonant cavity, and then on the basis of the initial values of the characteristic parameters of the resonant cavity, the target model constructed by the present disclosure is fitted to finally obtain the target parameter values of each characteristic parameter of the resonant cavity.

[0128] It should be noted that the input of the present disclosure is: S 21 (f) the signal experimental value of the signal, which is a complex number array; the frequency f of the driving signal applied to the resonant cavity, which is a real number array. Correspondingly, the output of the present disclosure is: the target parameter values of each characteristic parameter of the resonant cavity, for example, the target parameter values of the above-mentioned 8 characteristic parameters.

[0129] As Figure 4 shown, the general implementation steps for extracting the characteristic parameters of the resonant cavity in the embodiments of the present disclosure are as follows:

[0130] Step S401, using the electron delay algorithm, obtain the initial value of the electron delay τ in the target model. For example, perform electron delay processing on the target model to obtain the initial value of the electron delay τ; further, the center position of the S 21 (f) signal after removing the electron delay τ can also be obtained. For example, denote the center position after removing the electron delay τ as to represent the optimal initial value of the center position; here, i is the imaginary unit.

[0131] Step S402, obtain the initial value of the environmental amplitude A of the environment where the target resonant cavity is located in the target model, the initial value of the inclination degree η of the S 21 (f) signal, the initial value of the frequency f 0 of the resonant cavity, the initial value of the internal quality factor Q i of the resonant cavity, the initial value of the external quality factor Q c of the resonant cavity, and the initial value of the phase φ caused by impedance mismatch, a total of six initial values of characteristic parameters.

[0132] For example, take the modulus value of S 21 (f) to obtain the modulus signal ‖S21 (f), the modulus signal ‖S 21 (f) is independent of the electronic delay τ and the environmental phase α of the environment where the target resonator is located, that is, the modulus signal ‖S 21 (f) corresponds to the part in the target model. Fit the data of the modulus signal ‖S 21 (f) to obtain the initial value of the environmental amplitude A of the environment where the target resonator is located, the initial value of the inclination degree η of the S 21 (f) signal, the initial value of the frequency f of the resonator 0 , the initial value of the internal quality factor Q of the resonator i , the initial value of the external quality factor Q of the resonator c , and the initial value of the phase φ caused by impedance mismatch, a total of six initial values of characteristic parameters.

[0133] It should be noted that the execution order of step S401 and step S402 can be reversed, and the present disclosure does not limit this.

[0134] Step S403, obtain the initial value of the environmental phase α of the environment where the target resonator is located in the target model.

[0135] In one example, the initial value of the environmental phase α of the environment where the target resonator is located can be obtained according to the results of step S401 and step S402. For example, substitute the initial values of the characteristic parameters obtained in step S401 and step S402 into the target model. At this time, when the experimental value of the signal in S 21 (f) is known, the initial value of the environmental phase α of the environment where the target resonator is located can be obtained.

[0136] Or, in another example, it is also possible to obtain the initial value of the environmental phase α of the environment where the target resonator is located based on the center position of the S 21 (f) signal obtained in step S401 after removing the electronic delay τ . For example, based on and obtain the initial value of the environmental phase α of the environment where the target resonator is located.

[0137] So far, substitute the initial values of the above-mentioned characteristic parameters into the target model, and the estimated value of the S 21 (f) signal can be calculated, which can be denoted as S' 21 (f). In this way, based on the estimated value of the S 21 (f) signal, that is, S' 21 (f), and S 21(f) Based on the initial values of each characteristic parameter, optimize at least some of the characteristic parameters among all the characteristic parameters to minimize the difference between the experimental value of the signal and the estimated value S' of the signal S, so that S' approximates S. 21 (f) The estimated value S' of the signal 21 (f) approximates S 21 (f) The experimental value of the signal.

[0138] Step S404: When the initial values of each characteristic parameter are obtained, use the following parameter optimization process to obtain the target parameter values of each characteristic parameter in the target model, and the target parameter values can be approximated as the actual values of the characteristic parameters of the resonant cavity.

[0139] Step S404-1: Construct the first objective function, which can characterize the difference between the estimated value of the signal S(f) and the experimental value of the signal S(f). For example, the first objective function can be specifically: 21

[0140] (f) The difference between the estimated value of the signal and the experimental value of the signal S(f), for example, the first objective function can be specifically: 21 (f) The difference degree between the estimated value of the signal and the experimental value of the signal S(f). For example, the first objective function can be specifically:

[0141] ∑ f ‖S 21 (f) The experimental value of the signal - S' 21 (f)‖ 2 ;

[0142] Here, S' 21 (f) represents the estimated value of the signal S(f), that is, the signal to be optimized and fitted. 21 (f) The estimated value of the signal, that is, the signal to be optimized and fitted.

[0143] Step S404-2: Determine the values of each characteristic parameter in the current optimization process. For example, for the j-th optimization process, determine the j-th values of each characteristic parameter, and substitute the j-th values of each characteristic parameter into the target model to obtain the j-th estimated value of the signal S(f). 21 (f) The j-th estimated value of the signal.

[0144] It should be noted that for the first optimization process, that is, when j = 1, the first values of each characteristic parameter are the initial values obtained above.

[0145] Furthermore, for non-first optimization processes, that is, when j is a positive integer greater than or equal to 2, at this time, for the j-th optimization process, at least some of the (j - 1)-th values of the characteristic parameters can be adjusted, and the adjusted values are used as the j-th values of the j-th optimization process. Correspondingly, the unadjusted (j - 1)-th values can be directly used as the j-th values of this j-th optimization process.

[0146] For example, the j-1th value of the electronic delay, the j-1th value of the internal quality factor, and the j-1th value of the external quality factor are adjusted, and the adjusted values are used as the jth values. That is, the value obtained by adjusting the j-1th value of the electronic delay is used as the jth value of the electronic delay. Similarly, the j-1th value of the internal quality factor is used as the jth value of the internal quality factor, and the value obtained by adjusting the j-1th value of the external quality factor is used as the jth value of the external quality factor. Further, the j-1th value of the remaining characteristic parameters is directly used as the jth value.

[0147] It should be noted that the above parameterization adjustment process is only an exemplary illustration. In actual applications, there may be other adjustment methods, and the present disclosure does not limit this.

[0148] Step S404-3: Based on the jth estimated value of the S 21 (f) signal and the S 21 (f) signal experimental value, obtain the jth optimized value of the first objective function.

[0149] Step S404-4: Determine whether the jth optimized value of the first objective function is less than the preset threshold. If so, execute Step S404-5; otherwise, after j+1, return to Step S404-2.

[0150] Step S404-5: Use the jth value of the characteristic parameter as the target parameter value of the characteristic parameter to obtain the target parameter values of each characteristic parameter.

[0151] That is to say, when the jth optimized value of the first objective function is less than the preset threshold, this jth optimized value can be considered as the minimum value of the first objective function. At this time, the value of the characteristic parameter corresponding to the minimum value can be used as the target parameter value of the characteristic parameter to obtain the target parameter values of each characteristic parameter.

[0152] The second part, electronic delay algorithm

[0153] In some embodiments, the initial value of the electronic delay τ can be obtained by using the electronic delay algorithm provided in this part. For example, the experimental signal value of the S 21 (f) signal (such as a complex number array) and the frequency f of the drive signal applied to the resonant cavity (for example, a real number array) are used as the inputs of this electronic delay algorithm. At this time, the outputs of this electronic delay algorithm are the electronic delay τ and the center position after removing the electronic delay τ

[0154] It should be noted that the core idea of the electronic delay algorithm of the present disclosure is as follows:

[0155] After analysis, it can be seen that in the absence of electronic delay, S21 (f) The shape of the signal in the complex plane is circular, and the electronic delay τ causes the S 21 (f) signal to deform, and other characteristic parameters do not cause the S 21 (f) signal to change its shape. Based on this, a variable for canceling the electronic delay can be set. For example, it is called the cancellation variable and denoted as τ′. At the same time, a second objective function is set, and this second objective function can measure the S 21 (f) degree of deformation of the signal shape; at this time, if the above cancellation variable τ′ can completely cancel (or approximately cancel) the electronic delay τ at a specific value, even if the S 21 (f) signal shape returns to a circle, then the specific value of this cancellation variable τ′ is the actual value of the electronic delay τ, that is, the initial value of the electronic delay τ to be confirmed in the present disclosure solution. Further, in this process, the center position of the circle of the S 21 (f) signal after removing the electronic delay τ can also be obtained

[0156] As Figure 5 shown, the specific steps of the electronic delay algorithm are as follows:

[0157] Step S501, construct a second objective function; this second objective function can measure the S 21 (f) degree of deformation of the signal shape caused by the electronic delay τ, for example, it can be specifically:

[0158] VAR{‖S 21 (f)e i2πfτ′ ―(x 0 +iy 0 )‖};

[0159] Among them, τ′ represents the variable for canceling the electronic delay, that is, the cancellation variable; S 21 (f)e i2πfτ′ represents the S 21 (f) signal after canceling the influence of the electronic delay τ, (x 0 +iy 0 ) represents the center position of the S 21 (f) signal after removing the influence of the electronic delay τ, for example, it can be denoted as (x 0 +iy 0 ). Here, i is the imaginary unit.

[0160] Further, VAR represents taking the variance of {‖.‖}. It should be noted that the variance VAR here can also be replaced by the standard deviation STD, and the present disclosure solution does not limit this. As long as the second objective function can measure the S 21 (f) degree of deformation of the signal shape.

[0161] In addition, it should be noted that the above second objective function contains three parameters to be optimized, namely the cancellation variable τ′, the actual position of the center of the circle (x 0 +iy 0 ) where x 0 and y 0 . Thus, by iterating the optimizer to minimize the second objective function, the optimal parameter values of the above three parameters to be optimized can be finally obtained.

[0162] It can be understood that the optimal parameter value of the obtained cancellation variable τ′ can be used as the initial value of the electronic delay τ. Correspondingly, the optimal parameter value of x 0 is the position of the center of the circle after removing the electronic delay τ in y 0 The optimal parameter value is the position of the center of the circle after removing the electronic delay τ in

[0163] Step S502, obtain the initial value of the cancellation variable τ′ and the initial value of the position of the center of the circle.

[0164] For example, in one example, based on the target model, the argument of the S 21 (f) signal is taken, and the taken argument is linearly fitted to obtain a slope, and the negative of the slope is used as the initial value of the cancellation variable τ′.

[0165] In another example, the real part of the S 21 (f) signal can be taken, and half of the sum of the maximum value and the minimum value of the real part is used as the initial value of x 0 in the position of the center of the circle. The imaginary part of the S 21 (f) signal is taken, and half of the sum of the maximum value and the minimum value of the imaginary part is used as the initial value of y 0 in the position of the center of the circle.

[0166] Step S503, use the optimizer to minimize the second objective function by adjusting the initial value of the cancellation variable τ′ and the initial value of the position of the center of the circle, and when it is determined that the second objective function is at the minimum value (for example, when the function value of the second objective function is less than a preset value, it can be considered that the function value of the second objective function is at the minimum value), the value of the cancellation variable τ′ corresponding to the second objective function at the minimum value is used as the optimal value of the cancellation variable τ′, and the position of the center of the circle corresponding to the second objective function at the minimum value is used as the optimal initial value of the position of the center of the circle, which can be denoted as

[0167] It should be noted that the disclosed solution does not limit the specific optimizer. In other words, it does not limit the specific optimization method, as long as the minimum value of the second objective function can be solved.

[0168] In summary, the disclosed solution proposes an 8-parameter theoretical model (i.e., the above-mentioned target model), and designs the initial values of 8 characteristic parameters to be extracted step by step, so as to robustly extract the target parameter values of each characteristic parameter of the resonator. This method can not only achieve good parameter extraction effect for the ideal read resonator signal, but also accurately extract the resonator parameters in the case of environmental influences such as impedance mismatch, environmental phase, electronic delay and signal tilt.

[0169] Part Three, Validity Verification

[0170] To better understand the disclosed solution, the following validity verification is carried out:

[0171] For example, corresponding to step S401 in the overall process, that is, the electronic delay algorithm adopted, first take out the 21 argument of the S Figure 6 (f) signal, and perform linear fitting. Take the negative of the slope obtained by linear fitting to get the initial value of the cancellation variable τ′. The initial value of the cancellation variable τ′ is a rough estimate of the cancellation variable τ′, that is, a rough estimate of the electronic delay τ. As shown, it is the effect diagram of linear fitting. Among them, the solid line part corresponds to the phase of the S 21 (f) signal, and the dotted line part corresponds to the fitting result of the phase of the S 21 (f) signal. Further, estimate the initial values of the center position, including the initial values of the two parameters x 0 and y 0

[0172] Further, after obtaining the initial values of the cancellation variable τ′ and the center position (x 0 +iy 0 ), use the optimizer to optimize these three parameters. The optimization effect is as Figure 7 shown. Among them, the solid line part corresponds to the S 21 (f) signal on the complex plane (i.e., the original data corresponding to the figure), and the solid line part with solid dots represents the S 21 (f) signal after removing the influence of electronic delay (i.e., the processed data corresponding to the figure). The position with stars represents the center position after removing the influence of electronic delay, that is, the optimal initial value, denoted as

[0173] Further, corresponding to step S402 in the overall process, that is, for S 21(f) Take the modulus value of the signal and perform data fitting on the modulus value signal ‖S 21 (f) ‖, and the fitting effect obtained is as Figure 8 shown, where the dotted line part corresponds to the modulus value data sample of the S 21 (f) signal, and the solid line part corresponds to the fitting result of the modulus value data of the S 21 (f) signal.

[0174] Furthermore, corresponding to step S403 in the overall process, that is, according to the center position obtained in step S401 and the parameters obtained by fitting the modulus value signal ‖S 21 (f) ‖, calculate the initial value of the environmental phase. For example, in an example, the argument of the center position can be used as the initial value of the environmental phase α of the environment where the target resonator is located; or, in another example, the initial values of the various characteristic parameters (a total of 6) obtained by fitting the modulus value signal ‖S 21 (f) ‖ are substituted into the target model to obtain the algebraic part of the initial values of the 6 characteristic parameters included in the target model. At the same time, the initial value of the electronic delay is substituted into the target model, and the algebraic part including the initial value of the electronic delay can also be obtained. Divide the signal experimental value of the target model by these two algebraic parts, take the argument of the obtained part, and then take the mean or bias of the argument as the initial value of the environmental phase α.

[0175] Furthermore, after obtaining the initial values of the various characteristic parameters, according to step S404 in the overall process and based on the designed first objective function, optimization can be performed to finally obtain the target parameter values of 8 characteristic parameters, as Figure 9 shown, the comparison diagram of the signal experimental value of the S 21 (f) signal and the estimated value calculated according to the 8-parameter target model, so that it is sufficient to illustrate that the present disclosure can efficiently and accurately extract the parameters of the resonator.

[0176] The solution of the present disclosure also provides a device for determining the parameters of a resonator, as Figure 10 shown, the device includes:

[0177] A determination unit 1001, configured to obtain the signal experimental value of the target signal, where the signal experimental value of the target signal is obtained based on the actual input signal and the actual output signal of the target resonator;

[0178] A parameter processing unit 1002, configured to obtain target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonant cavity, and target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonance characteristic information of the target resonant cavity, based on the signal experimental value of the target signal and a target model for determining characteristic parameters of the target resonant cavity;

[0179] wherein, the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonant cavity, and the ideal resonance characteristic information of the target resonant cavity; N1 and N2 are positive integers greater than or equal to 1.

[0180] In a specific example of the present disclosure solution, the apparatus further includes: an operation unit; wherein,

[0181] The operation unit is configured to measure or operate on the target resonant cavity based on the target parameter values of each of the N1 first characteristic parameters and the target parameter values of each of the N2 second characteristic parameters.

[0182] In a specific example of the present disclosure solution, the first characteristic parameter among the N1 first characteristic parameters is at least one of the following:

[0183] The environmental amplitude of the environment where the target resonant cavity is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonant cavity is located, and the electronic delay.

[0184] In a specific example of the present disclosure solution, the measurement and control environment characteristic information of the target resonant cavity is represented by the following formula:

[0185]

[0186] wherein, A represents the environmental amplitude of the environment where the target resonant cavity is located, η represents the inclination degree of the target signal, α represents the environmental phase of the environment where the target resonant cavity is located, τ represents the electronic delay; f 0 represents the frequency of the target resonant cavity.

[0187] In a specific example of the present disclosure solution, the second characteristic parameter among the N2 second characteristic parameters is at least one of the following:

[0188] The frequency of the target resonant cavity, the internal quality factor of the target resonant cavity, the external quality factor of the target resonant cavity, and the phase caused by impedance mismatch.

[0189] In a specific example of the present disclosure solution, the ideal resonance characteristic information of the target resonant cavity is represented by the following formula:

[0190]

[0191] Among them, f 0 represents the frequency of the target resonator, Q i represents the internal quality factor of the target resonator, Q c represents the external quality factor of the target resonator, and φ is the phase caused by impedance mismatch.

[0192] In a specific example of the present disclosure solution, the parameter processing unit is specifically configured to:

[0193] Execute the j-th parameter optimization process to obtain the j-th estimated value of the target signal obtained based on the target model; j is a positive integer greater than or equal to 1;

[0194] When it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, take the j1-th value of the first characteristic parameter as the target parameter value of the first characteristic parameter, and take the j2-th value of the second characteristic parameter as the target parameter value of the second characteristic parameter;

[0195] Among them, the j-th parameter optimization process includes:

[0196] Determine the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter;

[0197] Substitute the j1-th value of each first parameter and the j2-th value of each second parameter into the target model to obtain the j-th estimated value.

[0198] In a specific example of the present disclosure solution, the parameter processing unit is further configured to:

[0199] When it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal does not meet the preset difference requirement, execute the (j + 1)-th parameter optimization process to obtain the (j + 1)-th estimated value of the target signal obtained based on the target model;

[0200] Determine whether the difference between the (j + 1)-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, so as to obtain the target parameter values of each first characteristic parameter and each second characteristic parameter.

[0201] In a specific example of the present disclosure solution, the parameter processing unit is specifically configured to:

[0202] When j is greater than 1, at least some of the (j1 - 1) - th values of the first characteristic parameters and the (j2 - 1) - th values of the second characteristic parameters obtained in the optimization process of the (j - 1) - th parameter are adjusted to obtain the j1 - th values of the first characteristic parameters and the j2 - th values of the second characteristic parameters;

[0203] Or,

[0204] When j is equal to 1, based on the target model, the initial values of the first characteristic parameters and the initial values of the second characteristic parameters are calculated.

[0205] In a specific example of the present disclosure solution, the parameter processing unit is specifically configured to perform at least one of the following:

[0206] The first processing flow, the second processing flow, and the third processing flow;

[0207] Among them, the first processing flow includes: processing the target signal to obtain a target signal that meets the requirements, and based on the target signal that meets the requirements, at least obtaining the initial value of the electronic delay; the electronic delay is a first characteristic parameter;

[0208] The second processing flow includes: performing data processing on the target model to remove the environmental phase representing the electronic delay and the environment where the target resonator is located in the target model, and obtaining the initial values of the following characteristic parameters: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch; among them, the environmental amplitude of the environment where the target resonator is located and the inclination degree of the target signal are both first characteristic parameters; the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch are all second characteristic parameters;

[0209] The third processing flow includes: obtaining the initial value of the environmental phase of the environment where the target resonator is located, where the environmental phase of the environment where the target resonator is located is a first characteristic parameter.

[0210] In a specific example of the present disclosure solution, the first processing flow, the second processing flow, and the third processing flow are asynchronous processing flows.

[0211] In a specific example of the present disclosure solution, the parameter processing unit is specifically configured to:

[0212] Estimate the degree of deformation of the shape of the target signal caused by the electronic delay;

[0213] Process the target signal based on the degree of deformation to obtain the value of the cancellation variable used to cancel the deformation of the shape of the target signal;

[0214] Based on the value of the cancellation variable, obtain the initial value of the electronic delay and the center position of the signal after canceling the deformation of the shape of the target signal.

[0215] In a specific example of the present disclosure solution, the third processing flow is executed after the first processing flow;

[0216] Among them, the parameter processing unit is specifically used for:

[0217] Based on the center position of the signal after canceling the deformation of the shape of the target signal, obtain the initial value of the environmental phase of the environment where the target resonator is located.

[0218] For the specific functions and example descriptions of the units of the device according to the embodiments of the present disclosure, reference may be made to the relevant descriptions of the corresponding steps in the above method embodiments, which will not be elaborated here.

[0219] The present disclosure solution also provides a non-transitory computer-readable storage medium storing computer instructions, which, when executed by at least one quantum processing unit, cause the at least one quantum processing unit to execute the above method applied to the quantum computing device.

[0220] The present disclosure solution also provides a computer program product, including a computer program, where the computer program, when executed by a processor, implements the above method applied to the classical computing device;

[0221] Alternatively, the computer program, when executed by at least one quantum processing unit, implements the method applied to the quantum computing device.

[0222] The present disclosure solution also provides a quantum computing device, which includes:

[0223] At least one quantum processing unit;

[0224] A memory coupled to the at least one QPU and used to store executable instructions,

[0225] The instructions are executed by the at least one quantum processing unit, so that the at least one quantum processing unit can execute the method applied to the quantum computing device.

[0226] It can be understood that the quantum processing unit (quantum processing unit, QPU) used in the present disclosure solution, which can also be referred to as a quantum processor or a quantum chip, may involve a physical chip including multiple quantum bits interconnected in a specific manner.

[0227] Moreover, it can be understood that the qubits described in the present disclosure solution may refer to the basic information units of a quantum computing device. Qubits are included in the QPU and generalize the concept of classical digital bits.

[0228] According to an embodiment of the present disclosure, the present disclosure also provides a computing device, a readable storage medium, and a computer program product.

[0229] Figure 11 FIG. shows a schematic block diagram of an example computing device 1100 that can be used to implement embodiments of the present disclosure. The computing device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The computing device can also represent various forms of mobile devices, such as, a personal digital assistant, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the present disclosure described and / or claimed herein.

[0230] As Figure 11 shown, the device 1100 includes a computing unit 1101, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1102 or a computer program loaded from a storage unit 1108 into a random access memory (RAM) 1103. In the RAM 1103, various programs and data required for the operation of the device 1100 can also be stored. The computing unit 1101, the ROM 1102, and the RAM 1103 are connected to each other through a bus 1104. An input / output (I / O) interface 1105 is also connected to the bus 1104.

[0231] A plurality of components in the device 1100 are connected to the I / O interface 1105, including: an input unit 1106, such as a keyboard, a mouse, etc.; an output unit 1107, such as various types of displays, speakers, etc.; a storage unit 1108, such as a magnetic disk, an optical disk, etc.; and a communication unit 1109, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1109 allows the device 1100 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0232] The computing unit 1101 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 1101 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 1101 executes the various methods and processes described above, such as the method for determining the resonator parameters. For example, in some embodiments, the method for determining the resonator parameters can be implemented as a computer software program tangibly embodied in a machine-readable medium, such as the storage unit 1108. In some embodiments, part or all of the computer program can be loaded and / or installed onto the device 1100 via the ROM 1102 and / or the communication unit 1109. When the computer program is loaded into the RAM 1103 and executed by the computing unit 1101, one or more steps of the method for determining the resonator parameters described above can be executed. Alternatively, in other embodiments, the computing unit 1101 can be configured to execute the method for determining the resonator parameters by any other suitable means (e.g., by means of firmware).

[0233] Various embodiments of the systems and techniques described above in this document can be implemented in digital electronic circuitry, integrated circuit systems, field-programmable gate arrays (FPGA), application-specific integrated circuits (ASIC), application-specific standard products (ASSP), systems-on-a-chip (SOC), complex programmable logic devices (CPLD), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special or general-purpose programmable processor, receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0234] The program code for implementing the methods of the present disclosure can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program code can be executed entirely on the machine, partially on the machine, as a stand-alone software package partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0235] In the context of this disclosure, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0236] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0237] The systems and techniques described herein can be implemented in a computing system including backend components (e.g., as a data server), or a computing system including middleware components (e.g., an application server), or a computing system including frontend components (e.g., a user computer having a graphical user interface or a web browser through which the user can interact with an implementation of the systems and techniques described herein), or a computing system including any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), and the Internet.

[0238] A computer system can include a client and a server. The client and the server are generally remote from each other and typically interact through a communication network. The client-server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, can also be a server of a distributed system, or a server incorporating a blockchain.

[0239] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and no limitation is imposed herein.

[0240] The above specific embodiments do not constitute a limitation on the protection scope of this disclosure. Those skilled in the art should understand that various modifications, combinations, sub - combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the principles of this disclosure shall be included within the protection scope of this disclosure.

Claims

1. A method for determining the parameters of a resonant cavity, comprising: obtaining the experimental signal value of the target signal, where the experimental signal value of the target signal is obtained based on the actual input signal and the actual output signal of the target resonant cavity; based on the experimental signal value of the target signal and a target model for determining the characteristic parameters of the target resonant cavity, obtaining the target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonant cavity, and obtaining the target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonant characteristic information of the target resonant cavity; wherein, the target model is used to characterize the correlation relationship between the signal value of the target signal, the measurement and control environment characteristic information of the target resonant cavity, and the ideal resonant characteristic information of the target resonant cavity; N1 and N2 are positive integers greater than or equal to 1; wherein, the first characteristic parameter among the N1 first characteristic parameters is at least one of the following: the environmental amplitude of the environment where the target resonant cavity is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonant cavity is located, and the electronic delay; and / or, the second characteristic parameter among the N2 second characteristic parameters is at least one of the following: the frequency of the target resonant cavity, the internal quality factor of the target resonant cavity, the external quality factor of the target resonant cavity, and the phase caused by impedance mismatch.

2. The method according to claim 1, further comprising: based on the target parameter values of each of the N1 first characteristic parameters and the target parameter values of each of the N2 second characteristic parameters, measuring or operating on the target resonant cavity.

3. The method according to claim 1, wherein, the measurement and control environment characteristic information of the target resonant cavity in the target model is represented by the following formula: Among them, represents the environmental amplitude of the environment where the target resonator is located, represents the degree of inclination of the said target signal, represents the environmental phase of the environment where the target resonator is located, represents the electronic delay; represents the frequency of the target resonator.

4. The method according to claim 1, wherein, the ideal resonant characteristic information of the target resonant cavity in the target model is represented by the following formula: Among them, represents the frequency of the target resonator, represents the internal quality factor of the target resonator, represents the external quality factor of the target resonator, is the phase caused by impedance mismatch.

5. The method according to any one of claims 1-4, wherein, the step of obtaining the target parameter values of each of the N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonant cavity, and the target parameter values of each of the N2 second characteristic parameters characterizing the ideal resonant characteristic information of the target resonant cavity based on the experimental signal value of the target signal and a target model for determining the characteristic parameters of the target resonant cavity, includes: performing the j-th parameter optimization process to obtain the j-th estimated value of the target signal obtained based on the target model; j is a positive integer greater than or equal to 1; when it is determined that the difference between the j-th estimated value of the target signal and the experimental signal value of the target signal meets the preset difference requirement, taking the j1-th value of the first characteristic parameter as the target parameter value of the first characteristic parameter, and taking the j2-th value of the second characteristic parameter as the target parameter value of the second characteristic parameter; wherein, the j-th parameter optimization process includes: determining the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter; Substitute the j1-th value of each first parameter and the j2-th value of each second parameter into the target model to obtain the j-th estimated value.

6. The method according to claim 5, further comprises: When it is determined that the difference between the j-th estimated value of the target signal and the experimental value of the target signal does not meet the preset difference requirement, perform the j+1 parameter optimization process to obtain the (j+1)-th estimated value of the target signal obtained based on the target model; Determine whether the difference between the (j+1)-th estimated value of the target signal and the experimental value of the target signal meets the preset difference requirement, so as to obtain the target parameter values of each first characteristic parameter and the target parameter values of each second characteristic parameter.

7. The method according to claim 5, wherein, the determination of the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter includes: When j is greater than 1, adjust at least some of the (j-1)-th values of each first characteristic parameter and the (j-1)-th values of each second characteristic parameter obtained in the (j-1) parameter optimization process to obtain the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter; or, When j is equal to 1, based on the target model, calculate the initial values of each first characteristic parameter and the initial values of each second characteristic parameter.

8. The method according to claim 7, wherein, the calculation of the initial values of each first characteristic parameter and the initial values of each second characteristic parameter based on the target model includes at least one of the following: The first processing flow, the second processing flow, the third processing flow; wherein, the first processing flow includes: processing the target signal to obtain a target signal that meets the requirements, and based on the target signal that meets the requirements, at least obtain the initial value of the electronic delay; the electronic delay is the first characteristic parameter; The second processing flow includes: performing data processing on the target model to remove the electronic delay and the environmental phase of the environment where the target resonator is located in the target model, and obtaining the initial values of the following characteristic parameters: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch; wherein, the environmental amplitude of the environment where the target resonator is located and the inclination degree of the target signal are both the first characteristic parameters; the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch are all the second characteristic parameters; The third processing flow includes: obtaining the initial value of the environmental phase of the environment where the target resonator is located, wherein the environmental phase of the environment where the target resonator is located is the first characteristic parameter.

9. The method according to claim 8, wherein, the first processing flow, the second processing flow, and the third processing flow are asynchronous processing flows.

10. The method according to claim 8, wherein, Processing the target signal to obtain a target signal meeting the requirements, and based on the target signal meeting the requirements, at least obtaining an initial value of electronic delay, including: Estimating the degree of deformation of the shape of the target signal caused by electronic delay; Based on the degree of deformation, processing the target signal to obtain a value of a cancellation variable for canceling the deformation of the shape of the target signal; Based on the value of the cancellation variable, obtaining an initial value of electronic delay and obtaining the center position of the signal after canceling the deformation of the shape of the target signal.

11. The method according to claim 10, wherein, The third processing flow is executed after the first processing flow; wherein, obtaining an initial value of the environmental phase of the environment where the target resonator is located includes: Based on the center position of the signal after canceling the deformation of the shape of the target signal, obtaining an initial value of the environmental phase of the environment where the target resonator is located.

12. A device for determining resonator parameters, including: A determination unit for obtaining a signal experimental value of a target signal, where the signal experimental value of the target signal is obtained based on the actual input signal of the target resonator and the actual output signal of the target resonator; A parameter processing unit for obtaining target parameter values of each first characteristic parameter among N1 first characteristic parameters characterizing the measurement and control environment characteristic information of the target resonator, and obtaining target parameter values of each second characteristic parameter among N2 second characteristic parameters characterizing the ideal resonance characteristic information of the target resonator, based on the signal experimental value of the target signal and a target model for determining the characteristic parameters of the target resonator; wherein, the target model is used to characterize the correlation between the signal value of the target signal, the measurement and control environment characteristic information of the target resonator, and the ideal resonance characteristic information of the target resonator; N1 and N2 are positive integers greater than or equal to 1; wherein, the first characteristic parameter among the N1 first characteristic parameters is at least one of the following: The environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the environmental phase of the environment where the target resonator is located, electronic delay; and / or, the second characteristic parameter among the N2 second characteristic parameters is at least one of the following: The frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, the phase caused by impedance mismatch.

13. The device according to claim 12, further including: An operation unit; wherein, The operation unit is used to measure or operate the target resonator based on the target parameter values of each first characteristic parameter among the N1 first characteristic parameters and the target parameter values of each second characteristic parameter among the N2 second characteristic parameters.

14. The device according to claim 12, wherein, The measurement and control environment characteristic information of the target resonator is represented by the following formula: Among them, represents the environmental amplitude of the environment where the target resonator is located, represents the inclination degree of the said target signal, represents the environmental phase of the environment where the target resonator is located, represents the electronic delay; represents the frequency of the target resonator.

15. The device according to claim 12, wherein, The ideal resonance characteristic information of the target resonator is represented by the following formula: Among them, represents the frequency of the target resonator, represents the internal quality factor of the target resonator, represents the external quality factor of the target resonator, is the phase caused by impedance mismatch.

16. The device according to any one of claims 12-15, wherein, The parameter processing unit is specifically used for: Execute the j-th parameter optimization process to obtain the j-th estimated value of the target signal obtained based on the target model; j is a positive integer greater than or equal to 1; When it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, take the j1-th value of the first characteristic parameter as the target parameter value of the first characteristic parameter, and take the j2-th value of the second characteristic parameter as the target parameter value of the second characteristic parameter; Among them, the j-th parameter optimization process includes: Determine the j1-th value of each first characteristic parameter and the j2-th value of each second characteristic parameter; Substitute the j1-th value of each first parameter and the j2-th value of each second parameter into the target model to obtain the j-th estimated value.

17. The device according to claim 16, Among them, The parameter processing unit is further configured to: When it is determined that the difference between the j-th estimated value of the target signal and the signal experimental value of the target signal does not meet the preset difference requirement, execute the (j + 1)-th parameter optimization process to obtain the (j + 1)-th estimated value of the target signal obtained based on the target model; Determine whether the difference between the (j + 1)-th estimated value of the target signal and the signal experimental value of the target signal meets the preset difference requirement, so as to obtain the target parameter values of each first characteristic parameter and each second characteristic parameter.

18. The device according to claim 16, Among them, The parameter processing unit is specifically configured to: When j is greater than 1, adjust at least part of the j1-1-th values of each first characteristic parameter and the j2-1-th values of each second characteristic parameter obtained in the (j - 1)-th parameter optimization process to obtain the j1-th values of each first characteristic parameter and the j2-th values of each second characteristic parameter; Or, When j is equal to 1, calculate the initial values of each first characteristic parameter and the initial values of each second characteristic parameter based on the target model.

19. The device according to claim 18, Among them, The parameter processing unit is specifically configured to execute at least one of the following: The first processing flow, the second processing flow, the third processing flow; Among them, the first processing flow includes: processing the target signal to obtain a target signal that meets the requirements, and based on the target signal that meets the requirements, at least obtain the initial value of the electronic delay; the electronic delay is the first characteristic parameter; The second processing flow includes: performing data processing on the target model to remove the environmental phase representing the electronic delay and the environment where the target resonator is located in the target model, and obtaining the initial values of the following characteristic parameters: the environmental amplitude of the environment where the target resonator is located, the inclination degree of the target signal, the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch; among them, the environmental amplitude of the environment where the target resonator is located and the inclination degree of the target signal are both the first characteristic parameters; the frequency of the target resonator, the internal quality factor of the target resonator, the external quality factor of the target resonator, and the phase caused by impedance mismatch are all the second characteristic parameters; The third processing flow includes: obtaining an initial value of the environmental phase of the environment where the target resonator is located, where the environmental phase of the environment where the target resonator is located is a first characteristic parameter.

20. The apparatus according to claim 19, wherein, the first processing flow, the second processing flow, and the third processing flow are asynchronous processing flows.

21. The apparatus according to claim 19, wherein, the parameter processing unit is specifically configured to: estimate the degree of deformation of the shape of the target signal caused by the electronic delay; process the target signal based on the degree of deformation to obtain a value of a cancellation variable for canceling the deformation of the shape of the target signal; obtain an initial value of the electronic delay and obtain the center position of the signal after canceling the deformation of the shape of the target signal based on the value of the cancellation variable.

22. The apparatus according to claim 21, wherein, the third processing flow is executed after the first processing flow; wherein the parameter processing unit is specifically configured to: obtain an initial value of the environmental phase of the environment where the target resonator is located based on the center position of the signal after canceling the deformation of the shape of the target signal.

23. A computing device, comprising: at least one quantum processing unit QPU; a memory coupled to the at least one QPU and configured to store executable instructions, the instructions being executed by the at least one QPU to enable the at least one QPU to execute the method according to any one of claims 1-11; or, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to execute the method according to any one of claims 1-11.

24. A non-transitory computer-readable storage medium storing computer instructions, characterized in that when executed by at least one quantum processing unit, the computer instructions cause the at least one quantum processing unit to execute the method according to any one of claims 1-11; or, the computer instructions are used to cause the computer to execute the method according to any one of claims 1-11.

25. A computer program product comprising a computer program, the computer program implementing the method according to any one of claims 1-11 when executed by at least one quantum processing unit; or the computer program implementing the method according to any one of claims 1-11 when executed by a processor.

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