Quantum bit parameter calibration method, device, electronic device and storage medium

Abstract

The present disclosure provides a parameter calibration method, device, electronic device and storage medium for quantum bits, which relate to the field of computer technology, and in particular to the fields of quantum chips, quantum measurement and control, etc. The specific implementation scheme is: fix the frequency of the read pulse signal of the quantum bit to a first frequency, and apply multiple magnetic flux biases to the quantum bit in sequence, and obtain multiple in-phase orthogonal IQ signal amplitude values ​​returned in sequence by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit; based on the multiple IQ signal amplitude values, fit to obtain a target function curve; determine the target maximum point among the multiple maximum points of the target function curve; determine the magnetic flux bias corresponding to the target maximum point as the minimum magnetic flux bias corresponding to the maximum bit frequency of the quantum bit.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to the fields of quantum chips, quantum measurement and control, etc. Background Art

[0002] Quantum computing is a computing model that follows quantum mechanics and controls quantum information units to perform calculations. Compared with traditional computers, quantum computers are better than traditional general-purpose computers in dealing with certain problems. Among them, superconducting quantum computers have become one of the mainstream quantum computing implementation solutions in the industry due to their advantages such as easy control and good scalability.

[0003] In the process of superconducting quantum computing chip measurement and control calibration, it is necessary to understand the variation law of quantum bit frequency with the magnetic flux bias applied to the quantum bit, and find the minimum magnetic flux bias corresponding to the maximum bit frequency of the quantum bit, so as to use the minimum magnetic flux bias to reduce energy consumption in the subsequent measurement and control process and computing application of the quantum bit. However, in the related art, the calibration process of the minimum magnetic flux bias has problems such as long experimental time and low efficiency. Summary of the invention

[0004] The present disclosure provides a method, device, electronic device and storage medium for quanta bit parameter calibration.

[0005] According to one aspect of the present disclosure, a method for calibrating a parameter of a quantum bit is provided, comprising:

[0006] The frequency of the read pulse signal of the quantum bit is fixed to a first frequency, and a plurality of magnetic flux biases are sequentially applied to the quantum bit to obtain a plurality of IQ (In-phase and Quadrature) signal amplitude values ​​sequentially returned by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit;

[0007] Based on the multiple IQ signal amplitude values, fitting to obtain a target function curve;

[0008] Based on the magnitude relationship between the second frequency and the third frequency, a target maximum point is determined among multiple maximum points of the target function curve; wherein the second frequency is the cavity frequency of the resonant cavity when the qubit applies a second magnetic flux bias, and the third frequency is the cavity frequency of the resonant cavity when the qubit applies a third magnetic flux bias; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions;

[0009] The flux bias corresponding to the target maximum point is determined as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit.

[0010] According to another aspect of the present disclosure, a device for calibrating a parameter of a quantum bit is provided, comprising:

[0011] A one-dimensional scanning module, used to fix the frequency of the read pulse signal of the quantum bit to a first frequency, and apply multiple magnetic flux biases to the quantum bit in sequence, to obtain multiple IQ signal amplitude values ​​returned in sequence by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the quantum bit applies the first magnetic flux bias;

[0012] A fitting module, used for fitting a target function curve based on multiple IQ signal amplitude values;

[0013] A target determination module, for determining a target maximum point among multiple maximum points of a target function curve based on a magnitude relationship between a second frequency and a third frequency; wherein the second frequency is a cavity frequency of the resonant cavity when a second magnetic flux bias is applied to the quantum bit, and the third frequency is a cavity frequency of the resonant cavity when a third magnetic flux bias is applied to the quantum bit; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions;

[0014] The calibration module is used to determine the flux bias corresponding to the target maximum point as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit.

[0015] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0016] At least one quantum processing unit (QPU);

[0017] A memory is coupled to the at least one QPU and is used to store executable instructions; the instructions are executed by the at least one QPU to enable the at least one QPU to execute any method in the embodiments of the present disclosure.

[0018] According to another aspect of the present disclosure, there is provided an electronic device, comprising:

[0019] at least one processor; and

[0020] a memory communicatively connected to the at least one processor; wherein,

[0021] The memory stores instructions that can be executed 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 any method in the embodiments of the present disclosure.

[0022] According to another aspect of the present disclosure, a non-transitory computer-readable storage medium storing computer instructions is provided, wherein the computer instructions are used to enable the computer to execute any method according to the embodiments of the present disclosure.

[0023] According to another aspect of the present disclosure, a computer program product is provided, including a computer program, which implements any method according to the embodiments of the present disclosure when executed by a processor.

[0024] According to the embodiment of the present disclosure, by fixing the frequency of the read pulse signal of the quantum bit, multiple flux biases are sequentially applied to the quantum bit to obtain multiple IQ signal amplitude values. The target function curve is fitted using multiple IQ signal amplitude values, and based on the frequency magnitude relationship under different flux biases, the target maximum point where the minimum flux bias corresponding to the maximum bit frequency is located is determined at multiple maximum points of the target function curve. Therefore, the embodiment of the present disclosure realizes the calibration of the above-mentioned minimum flux bias by one-dimensional scanning of the flux bias, which greatly reduces the time consumption of calibration and improves data utilization and efficiency.

[0025] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present disclosure, nor is it intended 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 accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure.

[0027] Figure 1 is a flow chart of a method for calibrating parameters of a quantum bit according to an embodiment of the present disclosure;

[0028] Figure 2 is a flow chart of a method for calibrating parameters of a quantum bit according to another embodiment of the present disclosure;

[0029] Figure 3 is a schematic diagram of the change of cavity frequency with magnetic flux bias in one case of an embodiment of the present disclosure;

[0030] Figure 4 is a schematic diagram of the change of cavity frequency with magnetic flux bias in another case in the embodiment of the present disclosure;

[0031] Figure 5 is a schematic diagram of the change of cavity frequency with magnetic flux bias in another case in the embodiment of the present disclosure;

[0032] Fig. 6A It is a schematic diagram of the variation of IQ signal amplitude with magnetic flux bias;

[0033] Figure 6B is a schematic diagram of the change of cavity frequency with magnetic flux bias determined by the parameter calibration method according to an embodiment of the present disclosure;

[0034] Figure 7is a flow chart of a method for calibrating parameters of a quantum bit according to another embodiment of the present disclosure;

[0035] Figure 8 is a flow chart of a method for calibrating parameters of a quantum bit according to another embodiment of the present disclosure;

[0036] Fig. 9 is a flow chart of a method for calibrating parameters of a quantum bit according to another embodiment of the present disclosure;

[0037] Fig.10 is a flow chart of a method for calibrating parameters of a quantum bit according to another embodiment of the present disclosure;

[0038] Fig.11 This is a flowchart of a complete application example;

[0039] Fig.12 is a schematic block diagram of a quantum bit parameter calibration device according to an embodiment of the present disclosure;

[0040] Fig.13 is a schematic block diagram of a quantum bit parameter calibration device according to another embodiment of the present disclosure;

[0041] Fig.14 is a schematic block diagram of a quantum bit parameter calibration device according to another embodiment of the present disclosure;

[0042] Fig.15 It is a block diagram of an electronic device used to implement the parameter calibration method of the quantum bit of the embodiment of the present disclosure. DETAILED DESCRIPTION

[0043] The following is a description of exemplary embodiments of the present disclosure in conjunction with the accompanying drawings, including various details of the embodiments of the present disclosure to facilitate understanding, which should be considered as merely exemplary. Therefore, it should be recognized by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope of the present disclosure. Similarly, for the sake of clarity and conciseness, the description of well-known functions and structures is omitted in the following description.

[0044] In order to facilitate understanding of the quantum bit parameter calibration method provided in the embodiment of the present disclosure, the technical names and variables involved in the embodiment of the present disclosure are first introduced below.

[0045] 1. Readout Modulation experiment, which is used to find the experimental parameters required for the maximum intrinsic frequency of superconducting quantum bits, that is, to determine the minimum flux bias corresponding to the maximum bit frequency of superconducting quantum bits (that is, the minimum flux bias required to achieve the maximum bit frequency). It can also be used to obtain the minimum periodic parameters of the periodic change of bit frequency with flux bias.

[0046] 2. Z DC (Z-Pulse DC, flux bias): Generates a low-frequency signal through an AWG (Arbitrary Waveform Generator) to simulate a DC bias signal. It is one of the scan variables in the Readout Modulation experiment in the related technology.

[0047] 3. f RO : The frequency of the read pulse signal. By scanning this frequency, the cavity frequency of the resonant cavity coupled to the quantum bit under a specific magnetic flux bias can be found. It is one of the scanning variables in the Readout Modulation experiment in the related technology.

[0048] 4. min , f max ]: Read the frequency scanning range of the pulse signal.

[0049] 5. IQ signal amplitude value: read the amplitude value of the cavity return signal, also recorded as |s 21 |.

[0050] 6. Z0: The minimum Z corresponding to the maximum bit frequency of the quantum bit DC .

[0051] 7. P mod :The cavity frequency of the resonant cavity coupled to the quantum bit varies with Z DC The minimum periodic parameter of periodic change, that is, the bit frequency of the quantum bit changes with Z DC Minimum period parameter for periodic changes.

[0052] The following is a description of the related technologies of the embodiments of the present disclosure. The following related technologies are optional solutions that can be arbitrarily combined with the technical solutions of the embodiments of the present disclosure, and they all belong to the protection scope of the embodiments of the present disclosure.

[0053] In the measurement and control calibration process of superconducting quantum computing chips, according to the principle of non-destructive measurement, the Readout Modulation experiment is carried out by using the synchronous relationship between the cavity frequency and the bit frequency as the magnetic flux power changes after the resonant cavity is coupled to the quantum bit. DC The frequency of the read pulse signal is used as a double independent variable. The frequency of the read pulse signal is scanned under different magnetic flux biases to find the read cavity frequency, and the variation law of the cavity frequency with the magnetic flux bias and Z0 are obtained. Specifically, it can be implemented in two ways: large-scale two-dimensional scanning and dynamic two-dimensional scanning.

[0054] (1) Large-scale 2D scanning

[0055] Large-scale 2D scanning is done at a suitable ZDC In the variation interval, the entire interval is divided into discrete flux bias scanning sequences using an appropriate number of steps, and the frequency scanning interval [f min , f max ], the reading pulse frequency scanning experiment is carried out under different flux biases, and the IQ signal amplitude data returned by the temperature control device is fitted using the Lorentz curve. Its peak and valley values ​​are used as the corresponding cavity frequency under a specific flux bias. The experiment is repeated to obtain the cavity frequency under all different flux biases, and the change law of the cavity frequency is obtained by fitting the cosine function. Since the cavity frequency and the bit frequency change synchronously (the amplitude is different but the period of change with the flux bias is the same, and the increase and decrease are synchronized), the minimum flux bias value required for the maximum bit frequency can be indirectly obtained.

[0056] (2) Dynamic 2D scanning

[0057] Unlike a wide range scan of cavity frequencies under different flux biases, dynamic 2D scanning uses the corresponding laws derived from the physical model to predict the approximate position of the cavity frequency corresponding to the next flux bias, narrowing the scan range of the read pulse frequency to focus on a relatively narrow frequency range near the known cavity frequency point. Repeating this process, when more frequencies and flux bias points are measured, this information is used to determine the approximate position of the next cavity frequency.

[0058] Even though dynamic 2D scanning can reduce the number of unnecessary scanning points to a certain extent, it is similar to large-scale 2D scanning in that it requires scanning over a large flux bias range and read pulse frequency range, so the experiment is time-consuming and inefficient. The 2D scanning of the Readout Modulation of a single quantum bit takes nearly tens of minutes, and the measurement and control calibration of the entire chip takes several hours.

[0059] In addition, in the two-dimensional scanning data, the remaining data after the first cavity frequency fitting will not be used subsequently, a large amount of scanning data will be directly wasted, and the data utilization rate is low.

[0060] Faced with different superconducting quantum chips and different quantum bits, the changing reality requires constant adjustment of experimental settings and related parameters. The above-mentioned related technologies have a low degree of automation, a high degree of human intervention, and lack of flexibility.

[0061] The technical solution of the embodiment of the present disclosure can solve at least one of the above-mentioned technical problems.

[0062] Figure 1The flowchart of the parameter calibration method of quantum bits provided by an embodiment of the present disclosure is shown. The method can be applied to electronic devices, such as classical computing devices or quantum computing devices. The electronic devices are, for example, single-machine or multi-machine terminals, servers or other processing devices. Among them, the terminal can be a user equipment (User Equipment, UE) such as a mobile device, a personal digital assistant (Personal Digital Assistant, PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. Figure 1 As shown, the method may include the following steps S110 to S140.

[0063] Step S110, fixing the frequency of the read pulse signal of the quantum bit to a first frequency, and applying multiple magnetic flux biases to the quantum bit in sequence, to obtain multiple IQ signal amplitude values ​​returned in sequence by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit.

[0064] Exemplarily, the qubit in the embodiment of the present disclosure is a superconducting qubit. It can be understood that a qubit can refer to a basic information unit of a quantum computing device.

[0065] Exemplarily, the first frequency in the embodiment of the present disclosure may be determined by scanning the frequency of the read pulse signal when the quantum bit applies the first magnetic flux bias.

[0066] Specifically, in Z DC When the first magnetic flux bias is fixed, the frequency of the read pulse signal is scanned within a preset frequency scanning interval (i.e., the frequency of the read pulse signal is set to a plurality of different frequency values ​​in sequence), and the IQ signal amplitude value returned by the resonant cavity during the scanning process is obtained (i.e., a plurality of IQ signal amplitude values ​​corresponding one to one to a plurality of different frequency values), and the frequency when the IQ signal amplitude value is a peak-to-valley value is determined as the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit.

[0067] Exemplarily, the first magnetic flux bias may be 0, that is, in the process of determining the first frequency, Z DC Fixed to 0. Since the cavity frequency varies with Z DC The range of periodic changes is relatively small, and the setting f RO The first frequency must be within the cavity frequency amplitude range of the resonant cavity to meet the experimental requirements, so the accuracy of the first frequency needs to be guaranteed. For example, the first frequency needs to be accurate to within 0.1 MHz (megahertz).

[0068] Exemplarily, in the above step S110, the multiple flux biases sequentially applied to the quantum bit may be multiple flux biases within a preset flux bias scanning interval. For example, the flux bias scanning interval is divided into discrete flux bias sequences based on a suitable step length or number of steps, and each flux bias in the flux bias sequence is sequentially applied to the quantum bit. In other words, the above step S110 is a one-dimensional scanning process for flux bias.

[0069] Optionally, the flux bias scanning interval and the segmentation step length / number of steps may be preconfigured. For example, the flux bias scanning interval may be preconfigured to [-0.9, 0.9], and the number of steps may be preconfigured to 81.

[0070] Since the frequency f of the read pulse signal RO When the cavity frequency is close to or equal to the cavity frequency of the resonant cavity, the read pulse signal will be absorbed by the cavity, and the returned IQ signal amplitude value is weak, while the cavity frequency changes with the magnetic flux bias Z. DC changes periodically, so at f RO In the fixed case, with Z DC Theoretically, the IQ signal amplitude will also show periodic changes, and there will inevitably be at least two times when the cavity frequency is equal to f RO (IQ signal amplitude reaches the minimum point), that is, f RO With Z DC Therefore, the embodiment of the present disclosure converts the scan variable and only scans Z DC By observing the change in the amplitude of the IQ signal, we can also obtain the law that the cavity frequency changes periodically with the magnetic flux bias, that is, the law that the bit frequency changes periodically with the magnetic flux bias.

[0071] Step S120: fitting a target function curve based on multiple IQ signal amplitude values.

[0072] Optionally, the function type corresponding to the IQ signal amplitude value may be determined according to the distribution of multiple IQ signal amplitude values, and curve fitting may be performed according to the function type to obtain the target function curve.

[0073] Alternatively, multiple IQ signal amplitude values ​​may be fitted based on a variant of the cosine function to obtain a target function curve. Specifically, multiple IQ signal amplitude values ​​may be fitted using the following formula:

[0074] y=|a*cos(ωx+b)+c|+d Formula (1)

[0075] Among them, a is the amplitude, ω is the frequency, b is the phase, and c and d are parameters for adjusting the y-axis position of the function.

[0076] Step S130, based on the magnitude relationship between the second frequency and the third frequency, determine the target maximum point among the multiple maximum points of the target function curve; wherein the second frequency is the cavity frequency of the resonant cavity when the quantum bit applies a second magnetic flux bias, and the third frequency is the cavity frequency of the resonant cavity when the quantum bit applies a third magnetic flux bias; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions.

[0077] Specifically, the first magnetic flux bias can be offset in different directions to obtain the second magnetic flux bias and the third magnetic flux bias, and then, for the second magnetic flux bias and the third magnetic flux bias, the frequency of the read pulse signal is scanned respectively to determine the second frequency and the third frequency. For details, please refer to the determination method of the first frequency mentioned above, which will not be repeated here. After determining the second frequency and the third frequency, based on the size relationship between the two, the target maximum point is determined among the multiple maximum points of the target function curve.

[0078] It can be understood that the maximum point of the objective function curve, that is, the cavity frequency corresponding to the flux bias, deviates from the fixed f RO The maximum point, therefore, the flux bias corresponding to the maximum point of the target function curve generally corresponds to the maximum or minimum value of the cavity frequency, that is, corresponds to the maximum bit frequency or minimum bit frequency of the quantum bit. Based on this, the multiple maximum points include the target maximum point to be found (the point where the flux bias corresponding to the maximum bit frequency of the quantum bit is located). Since the second flux bias and the third flux bias are located in different directions relative to the first flux bias, the direction of the cavity frequency-flux bias curve can be known based on the cavity frequency corresponding to the second flux bias and the cavity frequency corresponding to the third flux bias, so that the target maximum point can be determined among the multiple maximum points.

[0079] Step S140: determine the flux bias corresponding to the target maximum point as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit.

[0080] As described above, the target maximum point is the point where the flux bias corresponding to the maximum bit frequency of the quantum bit is located. Therefore, the flux bias corresponding to the target maximum point can be directly determined as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit. The minimum flux bias can be used to control the quantum bit frequency to the maximum in the measurement and control process and / or computing application of the quantum bit. It can be understood that the use of this minimum flux bias can reduce energy consumption compared to using other flux biases corresponding to the maximum bit frequency.

[0081] It can be seen that the above method provided by the embodiment of the present disclosure applies multiple flux biases to the quantum bit in sequence by fixing the frequency of the read pulse signal of the quantum bit to obtain multiple IQ signal amplitude values. The target function curve is fitted using multiple IQ signal amplitude values, and the target maximum point where the minimum flux bias corresponding to the maximum bit frequency is located is determined at multiple maximum points of the target function curve based on the frequency magnitude relationship under different flux biases. Therefore, the embodiment of the present disclosure realizes the calibration of the above minimum flux bias by one-dimensional scanning of the flux bias, which greatly reduces the time consumption of calibration and improves data utilization and efficiency.

[0082] In some embodiments, the first frequency, the second frequency, and the third frequency are determined by applying a specific magnetic flux bias to the quantum bit and performing a one-dimensional scan of the frequency of the read pulse signal within a frequency scanning interval.

[0083] By performing a one-dimensional scan of the frequency of the read pulse signal within the frequency scanning range, the cavity frequency corresponding to the quantum bit when a specific magnetic flux bias is applied can be accurately determined, thereby improving the accuracy of parameter calibration.

[0084] Figure 2 FIG. 1 is a flow chart of a method for calibrating quantum bit parameters according to another embodiment of the present disclosure. Figure 2 As shown, the method may further include the following steps S210 to S230.

[0085] Step S210: Determine the period size based on the target function curve.

[0086] In some scenarios, the cycle size can be determined according to parameters in the objective function curve, such as ω in the above formula (1).

[0087] Step S220: determining a first magnetic flux bias offset based on a periodicity of the cavity frequency changing with the magnetic flux bias and a first ratio.

[0088] Step S230: Based on the first magnetic flux bias offset, the first magnetic flux bias is offset in different directions to obtain a second magnetic flux bias and a third magnetic flux bias.

[0089] Exemplarily, the product of the above-mentioned period size and the first ratio is used as the first flux bias offset. Optionally, the first ratio can be 1 / 4, or approximately equal to 1 / 4. Since the first ratio is approximately 1 / 4, the first flux bias offset is 1 / 4 of the period of the IQ signal change, and the first flux bias is offset in different directions based on the offset, and the distance between the obtained second flux bias and the third flux bias can reach about 1 / 2 IQ period. It can be seen that by determining the flux bias offset based on the above-mentioned period size and the first ratio, the span of the second flux bias and the third flux bias can be controlled to be related to the period size, and based on the size relationship between the cavity frequency corresponding to the second flux bias and the cavity frequency corresponding to the third flux bias and the position of the extreme point of the target function curve, the direction of the cavity frequency changing with the flux bias can be judged more accurately.

[0090] In some embodiments, the above-mentioned step S130, based on the size relationship between the second frequency and the third frequency, determining the target maximum point among multiple maximum points of the target function curve, may include: when the difference between the second frequency and the third frequency is greater than or equal to the first threshold, offsetting the first flux bias in a single direction to obtain a fourth flux bias; applying the fourth flux bias to the quantum bit to obtain a fourth frequency; based on the size relationship between the first frequency and the fourth frequency, determining the frequency increase or decrease of the bit frequency of the quantum bit between the first flux bias and the fourth flux bias; based on the frequency increase or decrease, determining the target maximum point among multiple maximum points.

[0091] The first threshold may be determined based on the accuracy requirement of the application scenario. For example, the first threshold may be 0.1 MHz, 1 MHz, etc. If the difference between the second frequency and the third frequency is greater than or equal to the first threshold, it indicates that the second frequency is different from the third frequency.

[0092] In practical applications, when the second frequency, the third frequency and the first frequency are all different, the fourth magnetic flux bias can be determined, and then the target maximum value can be determined based on the fourth magnetic flux bias.

[0093] For ease of understanding, assuming that the second flux bias is obtained by shifting the first flux bias in the negative direction (left), and the third flux bias is obtained by shifting the first flux bias in the positive direction (right), then the second frequency corresponding to the second flux bias can be recorded as f L , the third frequency corresponding to the third flux bias can be recorded as f R .f L With f R The difference between the two is greater than or equal to the first threshold value, indicating that f L ≠f R If f L ≠f R ≠f RO , then we can assume that fRO In the middle of the cavity frequency variation with flux bias. Figure 3 Figure 2 shows the schematic diagram of the cavity frequency changing with the magnetic flux bias in this case. It can be seen that at f L ≠f R ≠f RO In the case of RO Located at L With f R between.

[0094] f RO Located at L With f R When the maximum points on both sides of the first flux bias on the target function curve are between , the maximum points may be the target maximum points. In the disclosed embodiment, the first flux bias is further offset in a single direction, and the offset is less than the offset of the first flux bias, to obtain a fourth flux bias, and the fourth frequency is determined by using the fourth flux bias, so that based on the magnitude relationship between the fourth frequency and the first frequency, the increase and decrease of the cavity frequency and the bit frequency near the first frequency can be determined. In this way, the target maximum point can be accurately determined based on the increase and decrease.

[0095] Specifically, if the fourth flux bias is obtained by offsetting in the positive direction (right) relative to the first flux bias, then the fourth frequency is greater than the first frequency, indicating that the bit frequency is increasing to the right near the first frequency, and the fourth frequency is less than the first frequency, indicating that the bit frequency is decreasing to the right near the first frequency.

[0096] On the contrary, if the fourth flux bias is obtained by offsetting in the negative direction (left) relative to the first flux bias, then the fourth frequency is greater than the first frequency, indicating that the bit frequency is decreasing to the right near the first frequency, and the fourth frequency is less than the first frequency, indicating that the bit frequency is increasing to the right near the first frequency.

[0097] In some embodiments, determining a target maximum point among multiple maximum points based on the increase or decrease of frequency may include: determining an offset direction of the target maximum point relative to a first frequency based on the increase or decrease of frequency; and taking a maximum point among the multiple maximum points that is closest to the first magnetic flux bias in the offset direction as the target maximum point.

[0098] Specifically, the offset direction of the target maximum point relative to the first magnetic flux bias, or which side of the first magnetic flux bias it is on, is first determined based on the increase and decrease characteristics, so as to find the point with the smallest absolute value of the magnetic flux bias in this direction as the target maximum point.

[0099] Among them, if the bit frequency increases to the right near the first frequency, the target maximum point is the maximum point on the right side of the first flux bias that is closest to the first flux bias; if the bit frequency increases to the left near the first frequency, the target maximum point is the maximum point on the left side of the first flux bias that is closest to the first flux bias.

[0100] For example, assuming that the fourth flux bias is relative to the first flux bias (Z DC =0) is offset in the positive direction (right), and by applying a fourth magnetic flux bias on the quantum bit, scanning the frequency of the read pulse signal, the fourth frequency corresponding to the fourth magnetic flux bias is found, which is recorded as f direct , and f RO Perform size comparison.

[0101] If f direct <f RO , then Z DC = 0. When the cavity frequency moves to the right, it decreases; when it moves to the left, it increases. In this case, Z0 is located at Z DC = 0; the target maximum point is located on the target function curve at Z DC =The nearest maximum point to the left of 0.

[0102] If f direct >f RO , then Z DC = 0. When the cavity frequency increases to the right, it decreases to the left. In this case, Z0 is located at Z DC = 0; the target maximum point is located on the target function curve at Z DC =The nearest maximum point to the right of 0.

[0103] It can be seen that through the above embodiment, when the second frequency, the third frequency and the first frequency are all different, the target maximum point can be accurately and uniquely determined, thereby accurately determining the minimum flux bias corresponding to the maximum bit frequency.

[0104] In some embodiments, the first magnetic flux bias is offset in a single direction to obtain a fourth magnetic flux bias, including: determining a second magnetic flux bias offset based on the above-mentioned period size and the second ratio, wherein the second magnetic flux bias offset is smaller than the first magnetic flux bias offset of the second magnetic flux bias and the third magnetic flux bias relative to the first magnetic flux bias; based on the second magnetic flux bias offset, the first magnetic flux bias is offset in a single direction to obtain a fourth magnetic flux bias.

[0105] Exemplarily, the second ratio may be 1 / 16, or approximately 1 / 16. Accordingly, the second magnetic flux bias offset may be 1 / 16 of a cycle of the IQ signal change.

[0106] According to the above embodiment, the fourth magnetic flux bias can be controlled to be within a smaller range relative to the first magnetic flux bias, thereby improving the accuracy of judging the increase or decrease and correspondingly improving the accuracy of parameter calibration.

[0107] In some embodiments, the above-mentioned step S130, based on the size relationship between the second frequency and the third frequency, determining the target maximum point among multiple maximum points of the target function curve, may include: when the difference between the second frequency and the third frequency is less than or equal to the second threshold, taking the maximum point among the multiple maximum points that is closest to the first flux bias as the target maximum point.

[0108] The second threshold value may be determined based on the accuracy requirements of the application scenario. For example, the second threshold value may be 0.1 MHz, 1 MHz, etc. The difference between the second frequency and the third frequency being less than or equal to the second threshold value indicates that the second frequency is approximately equal to the third frequency. It should be noted that the second threshold value may be the same as the first threshold value in the aforementioned embodiment, or may be different from the first threshold value in the aforementioned embodiment.

[0109] In practical applications, when the second frequency is approximately equal to the third frequency, the first frequency should be located at or close to (considering the error) the maximum point or minimum point on the curve of the cavity frequency changing with the magnetic flux bias. At this time, it can be considered that the increase and decrease of the bit frequency on the left and right sides of the first magnetic flux bias corresponding to the first frequency is the same, and the maximum point closest to the first magnetic flux bias among the multiple maximum points can be directly used as the target maximum point.

[0110] It should be noted that when the first frequency is at or close to the maximum point of the curve of the cavity frequency changing with the flux bias, the point corresponding to the first frequency on the target function curve may be the target maximum point, but considering the errors in the cavity frequency scanning, data fitting and other processes, the accuracy of the target maximum point can be improved by confirming the maximum point closest to the first flux bias among the multiple maximum points of the target function curve.

[0111] For ease of understanding, assuming that the second flux bias is obtained by offsetting the first flux bias in the negative direction (left) by 1 / 4 of the period of the target function curve, and the third flux bias is obtained by offsetting the first flux bias in the positive direction (right) by 1 / 4 of the period of the target function curve, then the second frequency corresponding to the second flux bias can be recorded as f L , the third frequency corresponding to the third flux bias can be recorded as f R .f L With f R The difference between them is less than or equal to the first threshold value, indicating that f L ≈f R There are two situations at this time. Figure 4 and Figure 5 Schematic diagram showing the variation of cavity frequency with flux bias in two cases:

[0112] Case 1: If Figure 4 As shown, if f L ≈f R <f R0 , we can determine y = f R0 The straight line is located at the maximum value.

[0113] Case 2: If Figure 5 As shown, if f L ≈f R >f R0 , we can determine y = f R0 The straight line is located at the minimum.

[0114] It should be noted that if the first frequency is between the maximum and minimum points of the curve of cavity frequency changing with flux bias, the period size corresponding to the target function curve is the period size of the cavity frequency changing with flux bias. If the first frequency is at the maximum or minimum point of the curve of cavity frequency changing with flux bias, the period size corresponding to the target function curve may be twice the period size of the cavity frequency changing with flux bias. Therefore, in the above example, f L ≈f R And the corresponding flux bias and f R0 The distance between the corresponding flux biases is 1 / 4 of the target function curve. Figure 4 and Figure 5 Displayed as f L 、f R The corresponding flux bias of the two is respectively R0 The distance between the corresponding flux biases is 1 / 2 of the period of the cavity frequency changing with the flux bias.

[0115] In order to facilitate understanding of the above-mentioned quantum bit parameter calibration method, a specific application example is provided below for illustration in combination with specific test data. Fig. 6A The frequency of the pulse signal to read is fixed at f R0 Schematic diagram of the change of IQ signal amplitude with flux bias obtained by traversing multiple flux bias points in the flux bias scanning sequence under the condition of . Figure 6B A schematic diagram of the change of cavity frequency with magnetic flux bias determined according to the parameter calibration method of an embodiment of the present disclosure.

[0116] In this application example, first determine f R0 Specifically, the first magnetic flux bias Z is set DC =0, by scanning and reading the frequency of the pulse signal, determine the first frequency f R0 , that is, Z DC = 0. Then, the frequency of the read pulse signal is fixed to f R0 , and in Z DCScan sequence through each Z DC ,get Fig. 6A It can be seen that in Z DC = 0, the IQ signal amplitude is close to the weakest, indicating that f R0 Z DC Corresponding cavity frequency. Using multiple sample points, the target function curve can be fitted according to the above formula (1), where the distance Z DC =0, the two nearest maximum points are likely to be the maximum points corresponding to the minimum flux bias Z0 (i.e., the target maximum points).

[0117] In order to determine the maximum point corresponding to the minimum flux bias Z0, according to the above method, refer to Figure 6B In Z DC = 0, and the second frequency f is found by scanning and reading the frequency of the pulse signal at a 1 / 4 period (the period of the target function curve) on both sides. L With the third frequency f R At this time, we judge f L 、f R and f R0 What kind of situation does the size relationship belong to. L 、f R and f R0 When Z DC = 0, and the fourth frequency f is found by scanning and reading the frequency of the pulse signal at the right side offset by 1 / 16 period (the period of the target function curve). direct . In f R0 >f direct When the cavity frequency changes with the magnetic flux bias, it can be determined that the cavity frequency is at Z DC = 0 is decreasing to the right, so we can determine that the target maximum point is at Z DC =0, and then Fig. 6A Middle Z DC =0 is taken as the target maximum point.

[0118] Through the application examples, we can see that in the above method, only a small amount of one-dimensional scanning is required to achieve the minimum magnetic flux bias corresponding to the maximum bit frequency of the quantum bit. Compared with the two-dimensional scanning method of related technologies, it can greatly reduce time consumption and improve data utilization.

[0119] Figure 7 FIG. 1 is a flow chart of a method for calibrating quantum bit parameters according to another embodiment of the present disclosure. Figure 7 As shown, the above step S120, based on multiple IQ signal amplitude values, fitting to obtain a target function curve, includes:

[0120] Step S121, performing autocorrelation function calculation based on multiple IQ signal amplitude values, and determining the number of first cycles in which the IQ signal amplitude value changes with the magnetic flux bias within the magnetic flux bias scanning interval where the multiple magnetic flux biases are located;

[0121] Step S122: When the first cycle number is within the target number interval, a target function curve is obtained by fitting based on multiple IQ signal amplitude values.

[0122] According to the above embodiment, the autocorrelation function can be used to roughly determine the number of cycles in which the amplitude values ​​of multiple IQ signals change with the flux bias, which is recorded as the first cycle number. When the first cycle number is within the target number interval, that is, when the first cycle number is greater than or equal to a threshold value and less than or equal to another threshold value, curve fitting is performed.

[0123] That is, it is necessary to perform curve fitting and subsequent steps when the number of first cycles meets certain conditions. In this way, the number of extreme points in the objective function curve can be sufficient to determine the target extreme points, while avoiding increasing the system error caused by subsequent data processing.

[0124] like Figure 7 As shown, the parameter calibration method of the quantum bit may also include:

[0125] Step S710: When the number of first cycles is less than or equal to the minimum value of the target number interval, determine the minimum flux bias corresponding to the maximum bit frequency of the quantum bit by two-dimensionally scanning the flux bias and the frequency of the read pulse signal.

[0126] Here, the two-dimensional scanning of the flux bias and the frequency of the read pulse signal may include the large-range two-dimensional scanning or the dynamic two-dimensional scanning in the aforementioned related art.

[0127] When the first cycle number is less than the minimum value of the target number interval, due to the limitation of directly processing the power of the temperature control device, the flux bias scanning interval cannot be changed well to obtain more cycles, so as to obtain enough maximum points on the target function curve. Therefore, switching to a two-dimensional scanning method can ensure the effective execution of parameter calibration.

[0128] In some embodiments, Figure 7 As shown, the parameter calibration method of the quantum bit may also include:

[0129] S720. When the number of the first period is greater than or equal to the maximum value of the target number range, narrow the magnetic flux bias scanning range, and re-determine multiple magnetic flux biases within the narrowed magnetic flux bias scanning range. Then, return to the step of fixing the frequency of the read pulse signal of the qubit to the first frequency and sequentially applying multiple magnetic flux biases to the qubit until the number of the first period is within the target number range.

[0130] When the number of the first period is greater than the maximum value of the target number range, since a large number of periods will increase the systematic error generated by subsequent data fitting and does not meet the actual situation requirements, by narrowing the magnetic flux bias scanning range and re-performing the one-dimensional frequency scanning, the accuracy of subsequent processing can be ensured.

[0131] Exemplarily, in the above embodiment, the target number range can be (1, 10). Assume that the number of the first period is n1:

[0132] If n1 ≤ 1, then switch to two-dimensional scanning to determine the minimum magnetic flux bias corresponding to the maximum qubit frequency, such as dynamic two-dimensional scanning;

[0133] If n1 ≥ 10, then the magnetic flux bias scanning range can be narrowed to half of the original and steps S110 and subsequent steps can be re-performed;

[0134] If 1 < n1 < 10, then proceed to the next step, perform curve fitting and find the target maximum point.

[0135] Figure 8 It is a schematic flowchart of a method for calibrating parameters of a qubit according to another embodiment of the present disclosure. As Figure 8 shown, the method for calibrating parameters of a qubit may further include:

[0136] Step S810. Determine the correlation coefficient between multiple IQ signal amplitude values and the target function curve;

[0137] Step S820. When the correlation coefficient is less than the third threshold, adjust the parameters for determining multiple magnetic flux biases to re-determine multiple magnetic flux biases, and return to the step of fixing the frequency of the read pulse signal of the qubit to the first frequency and sequentially applying multiple magnetic flux biases to the qubit until the correlation coefficient is greater than or equal to the third threshold.

[0138] Optionally, when the correlation coefficient is greater than or equal to the third threshold, step S130 is executed. Exemplarily, the third threshold can be a positive number slightly less than 1, such as 0.8, 0.9, etc., and can be specifically determined according to actual accuracy requirements.

[0139] According to the above embodiment, after the curve is fitted, the correlation coefficient between the original data and the fitted data is calculated to determine the fitting effect. If the correlation coefficient is less than the third threshold value, indicating that the fitting effect is poor, the parameters can be adjusted and the parameter calibration can be restarted. Specifically, the initial parameters can be adjusted, such as the boundary value of the flux bias scanning range, the step length or number of steps of the scanning, etc. In this way, the error of the parameter calibration can be reduced.

[0140] Fig. 9 FIG. 1 is a flow chart of a method for calibrating the parameters of a quantum bit according to another embodiment of the present disclosure. Fig. 9 As shown, the parameter calibration method of the quantum bit may also include:

[0141] Step S910, based on the target function curve, determining the number of second cycles in which the amplitude value of the IQ signal changes with the flux bias in the flux bias scanning interval where the plurality of flux biases are located;

[0142] Step S920: When the second number of cycles is greater than or equal to the fourth threshold, the magnetic flux bias scanning interval is reduced, and multiple magnetic flux biases are re-determined within the reduced magnetic flux bias scanning interval. The process returns to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and sequentially applying multiple magnetic flux biases to the quantum bit until the second number of cycles is less than the fourth threshold.

[0143] Optionally, when the second cycle number is less than a fourth threshold, step S130 is performed. Exemplarily, the fourth threshold may be 5, 7, etc., which may be determined according to actual accuracy requirements.

[0144] According to the above embodiment, after curve fitting, the accurate number of cycles in the magnetic flux bias scanning interval according to the objective function curve is recorded as the second number of cycles. If the number of cycles is too large, the subsequent error may be large, affecting the subsequent data analysis, then the magnetic flux bias scanning interval can be reduced, for example, reduced to half of the original, and the parameter calibration can be restarted. In this way, the error of parameter calibration can be reduced.

[0145] Fig.10 FIG. 1 is a flow chart of a method for calibrating the parameters of a quantum bit according to another embodiment of the present disclosure. Fig.10 As shown, the parameter calibration method of the quantum bit may also include:

[0146] Step S1010: determining the number of flux biases in a single cycle in which the IQ signal amplitude value changes with the flux bias among the multiple flux biases based on the target function curve;

[0147] Step S1020: When the number of magnetic flux biases in a single cycle is less than the fifth threshold, the step size or number of steps used to determine the multiple magnetic flux biases is adjusted to redetermine the multiple magnetic flux biases. The process returns to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and sequentially applying the multiple magnetic flux biases to the quantum bit until the number of magnetic flux biases in a single cycle is greater than or equal to the fifth threshold.

[0148] Optionally, when the number of magnetic flux biases in a single cycle is greater than or equal to a fifth threshold, step S130 is performed. Exemplarily, the fifth threshold may be a value such as 15 or 18.

[0149] It can be understood that the above-mentioned number of flux bias is the sample points in a single cycle. According to the above embodiment, after the curve is fitted, it is determined whether the next operation can be performed according to the number of sample points in a single cycle. If the number of sample points in a single cycle is too small and the fitting result is unreliable, it is necessary to adjust the step size or number of steps, for example, increase the number of sample points to twice the original number and restart the parameter calibration. In this way, the error of parameter calibration can be reduced.

[0150] It should be noted that the above Figures 7 to 10 The solutions shown can be implemented one by one, or two or more solutions can be combined, all of which fall within the protection scope of the embodiments of the present disclosure.

[0151] For ease of understanding, Fig.11 A complete application example is shown in Figure 1. Fig.11 As shown, the parameter calibration method of the quantum bit may include:

[0152] Step 1: Pre-scan. Specifically, you need to scan to get the current Z DC = 0 when the exact cavity frequency f R0 ; Then, fix the frequency of the read pulse signal to f R0 , Z DC As a scan item. The scan range is [0.9, 0.9] and the number of steps is 81. Scan Z DC The experimental data (IQ signal amplitude data) obtained are used to determine the approximate period and the number of periods n1 within the scanning range through the autocorrelation function. If n1≤1, proceed to step 2.1; if n1≥10, the flux bias scanning interval can be reduced to half of the original and the pre-scan and this judgment process can be repeated; if 1<n1<10, proceed to step 2.2.

[0153] Step 2.1: Connect to dynamic 2D scanning.

[0154] Step 2.2: Data fitting analysis.

[0155] After obtaining experimental data that meets the standard through pre-scanning, the experimental data is fitted using the above formula (1). After fitting, the correlation coefficient R between the original data and the fitted data is calculated. 2 To judge the fitting effect. The calculation of the correlation coefficient refers to the following formula:

[0156]

[0157] If R 2 <0.8, the fitting fails and the initial parameters or boundary values ​​need to be changed to refit;

[0158] If R 2 ≥0.8, the fitting is successful, and the next step of data processing is carried out.

[0159] After the fitting is successful, the fitting function period is calculated to obtain the current Z DC The number of cycles within the scanning range n2 and the number of scanning points in a single cycle N0:

[0160] If n2 ≥ 5, the subsequent fitting error is large, and the Z DC The scanning range is half of the original one and the pre-scan is repeated;

[0161] If N0 is less than 15, the fitting result is unreliable and the number of scanning points should be doubled and the experiment should be repeated.

[0162] If n2<5 and N0≥15, proceed to step 3.3.

[0163] Step 3: Scan type to determine.

[0164] According to the characteristics of the cosine function and the physical meaning of the periodic change of the cavity frequency, by scanning Z DC = Two cavity frequencies f under the flux bias of about 1 / 4 cycle distance on both sides of 0 L and f R , and respectively with f RO Make a comparison.

[0165] If f L ≈f R <f R0 , then determine y = f R0 The straight line is at the maximum value, go to step 3.1;

[0166] If f L ≈f R >f R0 , then determine y = f R0 The straight line is at the minimum value, go to step 3.2;

[0167] If f L ≠f R ≠f R0, then determine y = f R0 When the straight line is in the middle, proceed to step 3.3.

[0168] Step 3.1: f R0 When it is at the maximum value, Z0 is at Z DC =0, but usually due to system errors such as fine scanning cavity frequency and data fitting, the abscissa of the maximum point of the fitting function closest to 0 is taken as Z0.

[0169] Step 3.2: f R0 When it is at the minimum value, the distance Z DC =0 The nearest maximum point of the fitting function is the Z0 value of the quantum bit, because its physical meaning is the magnetic flux power required at the maximum bit frequency.

[0170] Step 3.3: f R0 When it is in the middle, it is necessary to determine the Z0 direction. R0 When it is located in the middle of the original two-dimensional cosine cavity frequency change, the distance from Z DC =0, both the nearest two maximum points may be what we are looking for, and we need to further judge based on the physical meaning and go to step 4.

[0171] Step 4. Scan distance Z DC = Cavity frequency f under flux bias at 1 / 16 period distance to the right of 0 direct , and f RO Compare sizes.

[0172] Step 4.1. If f direct <f RO , then Z DC = 0. When the cavity frequency moves to the right, it decreases; when it moves to the left, it increases. In this case, Z0 is located at Z DC = left side of 0;

[0173] Step 4.2. If f direct >f RO , then Z DC = 0. When the cavity frequency increases to the right, it decreases to the left. In this case, Z0 is located at Z DC = to the right of 0.

[0174] Finally, we find the correct direction and Z DC =0 is the nearest extreme point.

[0175] The method provided by the embodiment of the present disclosure has the following advantages: compared with the original large-scale scanning or improved two-dimensional scanning, the overall calibration process can be reduced by more than half, with higher efficiency and more effective use of physical laws and data information. For different superconducting chips and bits, a series of key measures such as period judgment and type distinction are also provided to consider multiple situations as much as possible and improve the robustness of the overall process. There is no need to provide preset parameters. If fitting or experimental failure occurs, the experiment will be automatically repeated to a certain extent, and specific error information will be returned in case of failure.

[0176] According to an embodiment of the present disclosure, the present disclosure also provides a quantum bit parameter calibration device, Fig.12 A schematic block diagram of a quantum bit parameter calibration device provided by an embodiment of the present disclosure is shown. Fig.12 As shown, the device comprises:

[0177] The one-dimensional scanning module 1210 is used to fix the frequency of the read pulse signal of the quantum bit to a first frequency, and apply multiple magnetic flux biases to the quantum bit in sequence, so as to obtain multiple in-phase orthogonal IQ signal amplitude values ​​returned in sequence by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the quantum bit applies the first magnetic flux bias;

[0178] A fitting module 1220, configured to obtain a target function curve by fitting based on multiple IQ signal amplitude values;

[0179] A target determination module 1230 is used to determine a target maximum point among multiple maximum points of the target function curve based on the magnitude relationship between the second frequency and the third frequency; wherein the second frequency is the cavity frequency of the resonant cavity when the qubit applies a second magnetic flux bias, and the third frequency is the cavity frequency of the resonant cavity when the qubit applies a third magnetic flux bias; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions;

[0180] The calibration module 1240 is used to determine the flux bias corresponding to the target maximum point as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit.

[0181] In some embodiments, Fig.13 As shown, the device also includes:

[0182] A cycle size determination module 1310, for determining a cycle size based on an objective function curve;

[0183] An offset determination module 1320, configured to determine a first magnetic flux bias offset based on the period size and the first ratio;

[0184] The magnetic flux bias determination module 1330 is used to offset the first magnetic flux bias in different directions based on the first magnetic flux bias offset to obtain the second magnetic flux bias and the third magnetic flux bias.

[0185] In some embodiments, the target determination module 1230 is used to:

[0186] When the difference between the second frequency and the third frequency is greater than or equal to the first threshold, the first magnetic flux bias is shifted in a single direction to obtain a fourth magnetic flux bias;

[0187] applying a fourth magnetic flux bias to the quantum bit to obtain a fourth frequency;

[0188] Based on the magnitude relationship between the first frequency and the fourth frequency, determining the frequency increase and decrease of the bit frequency of the quantum bit between the first magnetic flux bias and the fourth magnetic flux bias;

[0189] Based on the increase and decrease of frequency, a target maximum point is determined among multiple maximum points.

[0190] In some embodiments, the target determination module 1230 is used to:

[0191] Based on the frequency increase and decrease, determining the offset direction of the target maximum point relative to the first frequency;

[0192] The local maximum point closest to the first magnetic flux bias in the offset direction among the multiple local maximum points is used as the target local maximum point.

[0193] In some embodiments, the target determination module 1230 is used to:

[0194] Determine a second magnetic flux bias offset based on the period size and the second ratio; wherein the second magnetic flux bias offset is less than the first magnetic flux bias offset of the second magnetic flux bias and the third magnetic flux bias relative to the first magnetic flux bias;

[0195] Based on the second magnetic flux bias offset, the first magnetic flux bias is offset in a single direction to obtain a fourth magnetic flux bias.

[0196] In some embodiments, the target determination module 1230 is used to:

[0197] When the difference between the second frequency and the third frequency is less than or equal to the second threshold, the local maximum point closest to the first magnetic flux bias among the multiple local maximum points is used as the target local maximum point.

[0198] In some embodiments, the fitting module 1220 is used to:

[0199] An autocorrelation function is calculated based on multiple IQ signal amplitude values ​​to determine the number of first cycles in which the IQ signal amplitude value changes with the flux bias within the flux bias scanning interval where the multiple flux biases are located;

[0200] When the first cycle number is within the target number interval, a target function curve is obtained by fitting based on a plurality of IQ signal amplitude values.

[0201] In some embodiments, Fig.14 As shown, the device also includes:

[0202] The two-dimensional scanning module 1410 is used to determine the minimum flux bias corresponding to the maximum bit frequency of the quantum bit by two-dimensionally scanning the flux bias and the frequency of the read pulse signal when the first cycle number is less than or equal to the minimum value of the target number interval.

[0203] In some embodiments, Fig.14 As shown, the device also includes:

[0204] The first scanning interval adjustment module 1420 is used to reduce the flux bias scanning interval when the first cycle number is greater than or equal to the maximum value of the target number interval, and redetermine multiple flux biases within the reduced flux bias scanning interval, and return to the step of fixing the frequency of the quantum bit read pulse signal to the first frequency and applying multiple flux biases to the quantum bit in sequence until the first cycle number is within the target number interval.

[0205] In some embodiments, Fig.14 As shown, the device also includes:

[0206] A correlation coefficient determination module 1430, used to determine the correlation coefficients between the multiple IQ signal amplitude values ​​and the target function curve;

[0207] The parameter adjustment module 1440 is used to adjust the parameters used to determine multiple flux biases when the correlation coefficient is less than the third threshold value, so as to redetermine the multiple flux biases, and return to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying the multiple flux biases to the quantum bit in sequence until the correlation coefficient is greater than or equal to the third threshold value.

[0208] In some embodiments, Fig.14 As shown, the device also includes:

[0209] The cycle number determination module 1450 is used to determine the second cycle number of the IQ signal amplitude value changing with the flux bias in the flux bias scanning interval where the plurality of flux biases are located based on the target function curve;

[0210] The second scanning interval adjustment module 1460 is used to reduce the flux bias scanning interval when the number of second cycles is greater than or equal to the fourth threshold, and redetermine multiple flux biases within the reduced flux bias scanning interval, return to the step of fixing the frequency of the quantum bit's read pulse signal to the first frequency, and apply multiple flux biases to the quantum bit in sequence until the number of second cycles is less than the fourth threshold.

[0211] In some embodiments, Fig.14 As shown, the device also includes:

[0212] The sample point number determination module 1470 is used to determine the number of flux biases in a single cycle in which the amplitude value of the IQ signal changes with the flux bias among the multiple flux biases based on the target function curve;

[0213] The step size adjustment module 1480 is used to adjust the step size or number of steps used to determine multiple flux biases when the number of flux biases in a single cycle is less than the fifth threshold value, so as to redetermine the multiple flux biases and return to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying multiple flux biases to the quantum bit in sequence until the number of flux biases in a single cycle is greater than or equal to the fifth threshold value.

[0214] In some embodiments, the first frequency, the second frequency, and the third frequency are determined by applying a specific magnetic flux bias to the quantum bit and performing a one-dimensional scan of the frequency of the read pulse signal within a frequency scanning interval.

[0215] For the description of specific functions and examples of each module and submodule of the device in the embodiment of the present disclosure, reference can be made to the relevant description of the corresponding steps in the above method embodiment, which will not be repeated here.

[0216] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device, a readable storage medium and a computer program product.

[0217] In some embodiments, the electronic device may be a quantum computing device, the quantum computing device comprising:

[0218] At least one QPU (Quantum Processing Unit);

[0219] A memory is coupled to the at least one QPU and is used to store executable instructions; the instructions are executed by the at least one QPU to enable the at least one quantum processing unit to perform a method applied to a quantum computing device.

[0220] It will be appreciated that the QPU used in the embodiments of the present disclosure, which may also be referred to as a quantum processor or a quantum chip, may involve a physical chip comprising a plurality of quantum bits interconnected in a specific manner.

[0221] Moreover, it is understood that the quantum bit of the disclosed solution can refer to the basic information unit of a quantum computing device. The quantum bit is contained in the QPU and generalizes the concept of the classical digital bit.

[0222] In some embodiments, the electronic device may be a classical computing device. Fig.15 A schematic block diagram of an example electronic device 1500 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital assistants, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.

[0223] like Fig.15 As shown, the device 1500 includes a computing unit 1501, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 1502 or a computer program loaded from a storage unit 1508 into a random access memory (RAM) 1503. In the RAM 1503, various programs and data required for the operation of the device 1500 can also be stored. The computing unit 1501, the ROM 1502, and the RAM 1503 are connected to each other via a bus 1504. An input / output (I / O) interface 1505 is also connected to the bus 1504.

[0224] A number of components in the device 1500 are connected to the I / O interface 1505, including: an input unit 1506, such as a keyboard, a mouse, etc.; an output unit 1507, such as various types of displays, speakers, etc.; a storage unit 1508, such as a disk, an optical disk, etc.; and a communication unit 1509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 1509 allows the device 1500 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0225] The computing unit 1501 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 1501 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, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 1501 performs the various methods and processes described above, such as a parameter calibration method for a quantum bit. For example, in some embodiments, the parameter calibration method for a quantum bit may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 1508. In some embodiments, part or all of the computer program may be loaded and / or installed on the device 1500 via the ROM 1502 and / or the communication unit 1509. When the computer program is loaded into the RAM 1503 and executed by the computing unit 1501, one or more steps of the parameter calibration method for the quantum bit described above may be performed. Alternatively, in other embodiments, the computing unit 1501 may be configured to execute the parameter calibration method of the quantum bit by any other appropriate means (for example, by means of firmware).

[0226] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations 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 purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0227] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0228] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, 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 disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0229] 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 pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types 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, voice input, or tactile input).

[0230] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may 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.

[0231] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0232] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded 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 this document does not limit this.

[0233] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the principles of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for calibrating a quantum bit parameter, comprising: The frequency of the read pulse signal of the quantum bit is fixed to a first frequency, and a plurality of magnetic flux biases are sequentially applied to the quantum bit to obtain a plurality of in-phase orthogonal IQ signal amplitude values ​​sequentially returned by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit; Based on the multiple IQ signal amplitude values, fitting to obtain a target function curve; Based on the magnitude relationship between the second frequency and the third frequency, a target maximum point is determined among the multiple maximum points of the target function curve; wherein the second frequency is the cavity frequency of the resonant cavity when the second magnetic flux bias is applied to the qubit, and the third frequency is the cavity frequency of the resonant cavity when the third magnetic flux bias is applied to the qubit; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions; the second frequency and the third frequency are used to determine the direction of the cavity frequency-magnetic flux bias curve; the target maximum point is determined based on the direction of the cavity frequency-magnetic flux bias curve; The magnetic flux bias corresponding to the target maximum point is determined as the minimum magnetic flux bias corresponding to the maximum bit frequency of the quantum bit.

2. The method according to claim 1, further comprising: Based on the objective function curve, determining the period size; Determining a first flux bias offset based on the period size and the first ratio; Based on the first magnetic flux bias offset, the first magnetic flux bias is offset in different directions to obtain the second magnetic flux bias and the third magnetic flux bias.

3. The method according to claim 1 or 2, wherein: The step of determining a target maximum point from a plurality of maximum points of the target function curve based on the magnitude relationship between the second frequency and the third frequency includes: When the difference between the second frequency and the third frequency is greater than or equal to a first threshold, the first magnetic flux bias is shifted in a single direction to obtain a fourth magnetic flux bias; Applying the fourth magnetic flux bias to the quantum bit to obtain a fourth frequency; Based on the magnitude relationship between the first frequency and the fourth frequency, determining the frequency increase and decrease of the bit frequency of the quantum bit between the first magnetic flux bias and the fourth magnetic flux bias; Based on the frequency increase and decrease, a target local maximum point is determined among the plurality of local maximum points.

4. The method according to claim 3, wherein: The step of determining a target maximum point among the plurality of maximum points based on the frequency increase and decrease includes: Based on the frequency increase and decrease, determining the offset direction of the target maximum point relative to the first frequency; A local point among the plurality of local points that is closest to the first magnetic flux bias in the offset direction is used as a target local point.

5. The method according to claim 3, wherein: The step of offsetting the first magnetic flux bias in a single direction to obtain a fourth magnetic flux bias includes: Determine a second magnetic flux bias offset based on the period size of the target function curve and the second ratio; wherein the second magnetic flux bias offset is smaller than the first magnetic flux bias offset of the second magnetic flux bias and the third magnetic flux bias relative to the first magnetic flux bias; Based on the second magnetic flux bias offset, the first magnetic flux bias is offset in a single direction to obtain the fourth magnetic flux bias.

6. The method according to claim 1 or 2, wherein: The step of determining a target maximum point from a plurality of maximum points of the target function curve based on the magnitude relationship between the second frequency and the third frequency includes: When the difference between the second frequency and the third frequency is less than or equal to a second threshold, a local maximum point among the plurality of local maximum points that is closest to the first magnetic flux bias is used as the target local maximum point.

7. The method according to claim 1 or 2, wherein: The fitting to obtain a target function curve based on the multiple IQ signal amplitude values ​​includes: Performing autocorrelation function calculation based on the multiple IQ signal amplitude values ​​to determine the first number of cycles in which the IQ signal amplitude value changes with the magnetic flux bias within the magnetic flux bias scanning interval where the multiple magnetic flux biases are located; When the first cycle number is within a target number interval, the target function curve is obtained by fitting based on the multiple IQ signal amplitude values.

8. The method according to claim 7, further comprising: When the first number of cycles is less than or equal to the minimum value of the target number interval, the minimum flux bias corresponding to the maximum bit frequency of the quantum bit is determined by two-dimensionally scanning the flux bias and the frequency of the read pulse signal.

9. The method according to claim 7, further comprising: When the first number of cycles is greater than or equal to the maximum value of the target number interval, the flux bias scanning interval is reduced, and the multiple flux biases are redetermined within the reduced flux bias scanning interval, and the step of fixing the frequency of the quantum bit's read pulse signal to the first frequency and applying multiple flux biases to the quantum bit in sequence is returned until the first number of cycles is within the target number interval.

10. The method according to claim 1 or 2, further comprising: Determining a correlation coefficient between the multiple IQ signal amplitude values ​​and the target function curve; When the correlation coefficient is less than the third threshold, the parameters used to determine the multiple flux biases are adjusted to redetermine the multiple flux biases, and the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying multiple flux biases to the quantum bit in sequence is returned until the correlation coefficient is greater than or equal to the third threshold.

11. The method according to claim 1 or 2, further comprising: Based on the target function curve, determining the number of second cycles in which the amplitude value of the IQ signal changes with the flux bias within the flux bias scanning interval where the plurality of flux biases are located; When the second number of cycles is greater than or equal to the fourth threshold, the flux bias scanning interval is reduced, and the multiple flux biases are redetermined within the reduced flux bias scanning interval, and the step of fixing the frequency of the quantum bit's read pulse signal to the first frequency and applying multiple flux biases to the quantum bit in sequence is returned until the second number of cycles is less than the fourth threshold.

12. The method according to claim 1 or 2, further comprising: Based on the target function curve, determining the number of flux biases in the plurality of flux biases that are within a single cycle in which the IQ signal amplitude value changes with the flux bias; When the number of flux biases within the single cycle is less than the fifth threshold, the step size or number of steps used to determine the multiple flux biases is adjusted to redetermine the multiple flux biases, and the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying multiple flux biases to the quantum bit in sequence is returned until the number of flux biases within the single cycle is greater than or equal to the fifth threshold.

13. The method according to claim 1 or 2, wherein: The first frequency, the second frequency, and the third frequency are determined by applying a specific magnetic flux bias to the quantum bit and performing a one-dimensional scan of the frequency of a read pulse signal within a frequency scanning interval.

14. A quantum bit parameter calibration device, comprising: A one-dimensional scanning module, used to fix the frequency of the read pulse signal of the quantum bit to a first frequency, and apply a plurality of magnetic flux biases to the quantum bit in sequence, to obtain a plurality of in-phase orthogonal IQ signal amplitude values ​​returned in sequence by the resonant cavity coupled to the quantum bit; wherein the first frequency is the cavity frequency of the resonant cavity when the first magnetic flux bias is applied to the quantum bit; A fitting module, configured to obtain a target function curve by fitting based on the multiple IQ signal amplitude values; A target determination module, for determining a target maximum point among multiple maximum points of the target function curve based on the magnitude relationship between the second frequency and the third frequency; wherein the second frequency is the cavity frequency of the resonant cavity when the qubit applies a second magnetic flux bias, and the third frequency is the cavity frequency of the resonant cavity when the qubit applies a third magnetic flux bias; the second magnetic flux bias and the third magnetic flux bias are determined by offsetting the first magnetic flux bias in different directions; the second frequency and the third frequency are used to determine the direction of the cavity frequency-magnetic flux bias curve; the target maximum point is determined based on the direction of the cavity frequency-magnetic flux bias curve; A calibration module is used to determine the flux bias corresponding to the target maximum point as the minimum flux bias corresponding to the maximum bit frequency of the quantum bit.

15. The apparatus according to claim 14, further comprising: A cycle size determination module, used to determine the cycle size based on the objective function curve; an offset determination module, configured to determine a first magnetic flux bias offset based on the period size and the first ratio; The magnetic flux bias determination module is used to offset the first magnetic flux bias in different directions based on the first magnetic flux bias offset to obtain the second magnetic flux bias and the third magnetic flux bias.

16. The device according to claim 14 or 15, wherein: The target determination module is used to: When the difference between the second frequency and the third frequency is greater than or equal to a first threshold, the first magnetic flux bias is shifted in a single direction to obtain a fourth magnetic flux bias; Applying the fourth magnetic flux bias to the quantum bit to obtain a fourth frequency; Based on the magnitude relationship between the first frequency and the fourth frequency, determining the frequency increase and decrease of the bit frequency of the quantum bit between the first magnetic flux bias and the fourth magnetic flux bias; Based on the frequency increase and decrease, a target local maximum point is determined among the plurality of local maximum points.

17. The device according to claim 16, wherein: The target determination module is used to: Based on the frequency increase and decrease, determining the offset direction of the target maximum point relative to the first frequency; A local point among the plurality of local points that is closest to the first magnetic flux bias in the offset direction is used as a target local point.

18. The device according to claim 17, wherein: The target determination module is used to: Determine a second magnetic flux bias offset based on the period size of the target function curve and the second ratio; wherein the second magnetic flux bias offset is smaller than the first magnetic flux bias offset of the second magnetic flux bias and the third magnetic flux bias relative to the first magnetic flux bias; Based on the second magnetic flux bias offset, the first magnetic flux bias is offset in a single direction to obtain the fourth magnetic flux bias.

19. The device according to claim 14 or 15, wherein: The target determination module is used to: When the difference between the second frequency and the third frequency is less than or equal to a second threshold, a local maximum point among the plurality of local maximum points that is closest to the first magnetic flux bias is used as the target local maximum point.

20. The device according to claim 14 or 15, wherein: The fitting module is used to: Performing autocorrelation function calculation based on the multiple IQ signal amplitude values ​​to determine the first number of cycles in which the IQ signal amplitude value changes with the magnetic flux bias within the magnetic flux bias scanning interval where the multiple magnetic flux biases are located; When the first cycle number is within a target number interval, the target function curve is obtained by fitting based on the multiple IQ signal amplitude values.

21. The apparatus according to claim 20, further comprising: A two-dimensional scanning module is used to determine the minimum flux bias corresponding to the maximum bit frequency of the quantum bit by two-dimensionally scanning the flux bias and the frequency of the reading pulse signal when the first cycle number is less than or equal to the minimum value of the target number interval.

22. The apparatus according to claim 20, further comprising: The first scanning interval adjustment module is used to reduce the flux bias scanning interval when the first cycle number is greater than or equal to the maximum value of the target number interval, and redetermine the multiple flux biases within the reduced flux bias scanning interval, and return to the step of fixing the frequency of the quantum bit read pulse signal to the first frequency and applying multiple flux biases to the quantum bit in sequence until the first cycle number is within the target number interval.

23. The apparatus according to claim 14 or 15, further comprising: A correlation coefficient determination module, used to determine the correlation coefficient between the multiple IQ signal amplitude values ​​and the target function curve; A parameter adjustment module is used to adjust the parameters used to determine the multiple flux biases when the correlation coefficient is less than a third threshold value, so as to redetermine the multiple flux biases, and return to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying multiple flux biases to the quantum bit in sequence until the correlation coefficient is greater than or equal to the third threshold value.

24. The apparatus according to claim 14 or 15, further comprising: A cycle number determination module, used to determine, based on the target function curve, the second cycle number of the IQ signal amplitude value changing with the flux bias in the flux bias scanning interval where the multiple flux biases are located; The second scanning interval adjustment module is used to reduce the flux bias scanning interval when the second cycle number is greater than or equal to the fourth threshold value, and redetermine the multiple flux biases within the reduced flux bias scanning interval, and return to the step of fixing the frequency of the quantum bit's read pulse signal to the first frequency and applying multiple flux biases to the quantum bit in sequence until the second cycle number is less than the fourth threshold value.

25. The apparatus according to claim 14 or 15, further comprising: A sample point number determination module, used to determine the number of flux biases in a single cycle in which the IQ signal amplitude value changes with the flux bias among the multiple flux biases based on the target function curve; A step size adjustment module is used to adjust the step size or number of steps used to determine the multiple flux biases when the number of flux biases in the single cycle is less than the fifth threshold value, so as to redetermine the multiple flux biases, and return to the step of fixing the frequency of the read pulse signal of the quantum bit to the first frequency and applying the multiple flux biases to the quantum bit in sequence until the number of flux biases in the single cycle is greater than or equal to the fifth threshold value.

26. The device according to claim 14 or 15, wherein: The first frequency, the second frequency, and the third frequency are determined by applying a specific magnetic flux bias to the quantum bit and performing a one-dimensional scan of the frequency of a read pulse signal within a frequency scanning interval.

27. An electronic 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 are executed by the at least one QPU to enable the at least one QPU to perform the method of any one of claims 1-13.

28. An electronic device comprising: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed 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 perform the method according to any one of claims 1 to 13.

29. A non-transitory computer-readable storage medium storing computer instructions, wherein: The computer instructions are used to cause the computer to execute the method according to any one of claims 1-13.

30. A computer program product comprising a computer program, which, when executed by a processor, implements the method according to any one of claims 1 to 13.

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