Superconducting quantum bit calibration method and device

Abstract

The invention relates to a superconducting quantum bit calibration method and device, and the method comprises the steps: scanning a to-be-calibrated quantum bit at a first sideband frequency and a second sideband frequency through employing a microwave driving frequency, and obtaining a phase spectrum and an amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency respectively; processing the phase spectrum and the amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency respectively, and determining the processed phase spectrum and the processed amplitude spectrum; performing double-Gaussian fitting on the processed phase spectrum and the processed amplitude spectrum respectively, and calculating excitation frequencies obtained by the processed phase spectrum and the processed amplitude spectrum respectively, namely a phase characteristic frequency and an amplitude characteristic frequency; and determining the excitation frequency of the quantum bit to be calibrated according to the phase characteristic frequency and the amplitude characteristic frequency. According to the invention, through a double-sideband difference Gaussian fitting technology and design of a robustness calibration process, related parameters of a single quantum bit are automatically calibrated.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of quantum information, and particularly relates to a method and device for calibrating a superconducting quantum bit. BACKGROUND

[0002] Quantum computing is considered one of the revolutionary technologies in the future computing field, and its ability to handle specific problems (such as large number factorization, complex optimization, and quantum chemical simulation) is expected to exceed that of traditional computers by utilizing the characteristics of quantum superposition and quantum entanglement. Quantum bits are the basic units of quantum computing, and have unique properties such as quantum superposition and quantum entanglement.

[0003] A superconducting quantum bit is a quantum bit realized by using a superconducting circuit, which can initialize, evolve, and read out quantum states under low-temperature conditions. Due to its high controllability and scalability, the superconducting quantum bit has become one of the most concerned technical routes in the field of quantum computing hardware, especially practical quantum computing. The research on the superconducting quantum bit began in the 1990s, when quantum phenomena based on Josephson junctions became a research hotspot. Early research focused on the manufacturing of superconducting quantum bits and the control of quantum state evolution. In this stage, the measurement and control technology was initially developed, and the research mainly focused on exciting quantum bits through pulse signals and simple readout experiments. In 2007, the Transmon quantum bit was proposed, which significantly improved the coherence time of the superconducting quantum bit through design optimization, greatly promoting the development of superconducting quantum computing. At the same time, the measurement and control technology has also made progress: the quantum electrodynamics technology of microwave cavity was introduced, and since there is a coupling between the cavity mode and the quantum bit, the quantum bit state information can be obtained non-destructively by measuring the dispersive shift of the cavity frequency, i.e., dispersive readout.

[0004] The parameters for regulating and controlling the quantum bit based on the dispersive readout technology usually include the readout frequency, the readout power, the readout Z pulse amplitude, and the excitation frequency (f10). Today, the parameter calibration of the quantum bit can be completed by different methods, for example, the f10 of the bit can be obtained by using the Rabi Oscillation and the Ramsey measurement technology based on the quantum interference effect. The readout frequency, the readout power, and the readout Z pulse amplitude can be obtained by the visibility of the |0> state and the |1> state in the IQ signal.

[0005] Achieving efficient operation of superconducting qubits requires precise calibration of relevant qubit parameters, such as the excitation frequency (f10), readout frequency, and readout power. These parameters are typically the foundation for obtaining the qubit's characteristic parameters (such as decoherence time and the fidelity of quantum gate operations). Therefore, single-qubit parameter calibration is a core prerequisite for subsequent qubit gate operations. Determining the excitation frequency (f10) is the most important and challenging task in automated single-qubit calibration. This is because determining the excitation frequency (f10) requires spectroscopic experiments using an arbitrary waveform generator (AWG). AWGs are mainly of two types: direct output and mixing. Mixing-mode AWGs are currently the most commonly used equipment in laboratories. Mixing-mode AWGs suffer from carrier leakage and sideband frequency spurious signals, resulting in many cluttered signal peaks in the qubit's energy spectrum, thus complicating the calibration of the excitation frequency (f10). Therefore, traditional calibration work is usually performed manually by experimentalists.

[0006] Currently, the quality of quantum computing chips is still in the improvement stage, requiring numerous iterations. Researchers aim to increase the speed of chip iteration while minimizing manpower consumption. However, existing single-qubit parameter calibration tests involve a large amount of repetitive manual operation, making testing efficiency highly dependent on the condition of the control personnel, resulting in significant inefficiency. Furthermore, the number of qubits on chips is increasing, and with this increase, the calibration process will undoubtedly become extremely cumbersome and time-consuming. The Quafu quantum computing cloud platform, jointly developed by the Beijing Academy of Quantum Information Science (Beijing Quantum Academy), the Institute of Physics of the Chinese Academy of Sciences (Institute of Physics), and Tsinghua University, has achieved a maximum of 136 qubits per chip, exceeding 100 qubits, and the number of qubits per chip is expected to reach thousands or even tens of thousands in the future. Faced with the ever-increasing number of qubits, relying on traditional manual judgment of experimental data for single-qubit calibration will become inefficient and costly. Superconducting quantum computing is entering a phase of rapid development. Global research teams (internationally, such as Google and IBM; domestically, such as the University of Science and Technology of China, Zhejiang University, Beijing Institute of Quantum Computing Technology, and the Institute of Physics) are pushing forward the scaling up and performance improvement of quantum computers, and optimizing the measurement and control hardware architecture to achieve the measurement and control of hundreds of qubits. Due to the complexity of superconducting quantum computers, manual measurement and control of qubits is no longer sufficient, and automated calibration and control have become a new research direction.

[0007] Current automated methods for determining qubit parameters require prior knowledge of theoretical values. However, in experiments, due to fluctuations in quantum chip manufacturing processes, some qubit parameters often differ significantly from their theoretical expectations. Furthermore, some parameters, such as the Z-pulse amplitude (zpa) and excitation amplitude, do not have fixed theoretical expectations. Therefore, this method cannot effectively calibrate these parameters. In addition, existing methods for calibrating superconducting qubit parameters using neural network models require extensive pre-training with large amounts of raw, real data to achieve a high calibration success rate, a time-consuming and computationally intensive process.

[0008] It is evident that manipulating and calibrating individual qubits is fundamental to realizing high-performance quantum computers; however, there are still shortcomings in terms of accuracy and efficiency. Summary of the Invention

[0009] With the automation of single-qubit control and calibration becoming increasingly important, this application designs an efficient and stable automated calibration scheme for superconducting qubits to address the problems existing in the current technology. The aim is to automatically calibrate the relevant parameters of a single qubit by using a double-sideband differential Gaussian fitting technique and designing a robust calibration process. This lays the foundation for efficient control of large-scale qubit chips and promotes the development of superconducting quantum computing technology.

[0010] According to the first aspect of this application, a method for calibrating superconducting qubits is provided, characterized in that:

[0011] At the first sideband frequency and the second sideband frequency, the quantum bits to be calibrated are scanned by microwave driving frequency to obtain the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency, respectively.

[0012] Process the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency respectively, and determine the processed phase spectrum and processed amplitude spectrum;

[0013] Perform double Gaussian fitting on the processed phase spectrum and the processed amplitude spectrum respectively, and calculate the phase characteristic frequency and amplitude characteristic frequency corresponding to the processed phase spectrum and the processed amplitude spectrum respectively; and

[0014] The excitation frequency of the quantum bit to be calibrated is determined based on the phase characteristic frequency and the amplitude characteristic frequency.

[0015] According to a second aspect of this application, an electronic device is provided, comprising:

[0016] Processor; and

[0017] A memory storing computer instructions that, when executed by the processor, cause the processor to perform the method described in the first aspect.

[0018] According to a third aspect of this application, a non-transitory computer storage medium is provided, which stores a computer program that, when executed by a plurality of processors, causes the processors to perform the method described in the first aspect.

[0019] According to the calibration method and apparatus for superconducting qubits provided in this application, the law that the non-intrinsic random peaks in the qubit energy spectrum shift with the change of sideband frequency is utilized. The qubit energy spectrum at different sideband frequencies is measured and processed in the experiment. By fitting the experimental results with antisymmetric Gaussian peaks, the excitation frequency of the qubit can be effectively obtained, thereby realizing the automatic calibration of the qubit excitation frequency. In addition, this application proposes a calibration order and logical judgment for different parameters of the qubit. Combined with the calibration of the excitation frequency, multiple parameters of the qubit can be calibrated automatically in an accurate, efficient and robust manner. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings, without exceeding the scope of protection claimed by this application.

[0021] Figure 1 This is a flowchart illustrating the process of determining the excitation frequency of a superconducting quantum bit according to an embodiment of this application.

[0022] Figure 2 These are the phase spectrum and amplitude spectrum of the IQ signal corresponding to the first sideband frequency according to an embodiment of this application.

[0023] Figure 3 These are the phase spectrum and amplitude spectrum of the IQ signal corresponding to the second sideband frequency according to an embodiment of this application.

[0024] Figure 4 These are the processed phase spectrum and processed amplitude spectrum and their fitting results according to the embodiments of this application.

[0025] Figure 5 This is a schematic flowchart illustrating the process of determining the calibration parameters of a superconducting quantum bit according to an embodiment of this application.

[0026] Figure 6 It is based on the Rabi oscillation experimental data and the extracted bit excitation amplitude according to the embodiments of this application.

[0027] Figure 7The distinction between the |0> state and the |1> state according to the embodiments of this application varies with the read power.

[0028] Figure 8 The distinguishability between the |0> state and the |1> state according to the embodiments of this application varies with the reading Z pulse amplitude;

[0029] Figure 9 The method described in this application is to measure the center distance of the IQ signals to optimize the read frequency of the frequency bits.

[0030] Figure 10 This is a flowchart of a method for calibrating superconducting qubits according to the first embodiment of this application.

[0031] Figure 11 This is a flowchart of a method for calibrating superconducting qubits according to a second embodiment of this application.

[0032] Figure 12 This is a flowchart of a method for calibrating superconducting qubits according to a third embodiment of this application.

[0033] Figure 13 This is a flowchart of a method for calibrating superconducting qubits according to the fourth embodiment of this application.

[0034] Figure 14 This is a flowchart of a method for calibrating superconducting qubits according to the fifth embodiment of this application.

[0035] Figure 15 This is a flowchart of a method for calibrating superconducting qubits according to the sixth embodiment of this application.

[0036] Figure 16 This is a flowchart of a method for calibrating superconducting qubits according to the seventh embodiment of this application.

[0037] Figure 17 This is a schematic diagram of the structure of an electronic device provided in this application.

[0038] Terminology Explanation:

[0039] 1. Quantum bit: In quantum computing, the quantum bit is the quantum version of the classical binary bit, the basic unit of quantum information. It is a two-state (or two-level) quantum mechanical system and one of the simplest quantum systems, demonstrating the special nature of quantum mechanics.

[0040] 2. Quantum state: The state in which a qubit exists. The ground state (|0>) and the excited state (|1>) are the basic quantum states of a qubit.

[0041] 3. The IQ signal (In-phase and Quadrature Signal) is represented by a complex plane consisting of the in-phase component (I) and the quadrature component (Q) of the signal. During quantum state calibration, after the readout signal carrying the state information of the qubit is demodulated, it will form a distribution in the IQ complex plane, referred to as the IQ distribution.

[0042] 4. IQ Inverse Mixing: IQ represents two orthogonal I (in-phase) and Q (quadrature) signals in the complex plane. During quantum state calibration, the readout signal carrying the qubit state information has a frequency of approximately 6-8 GHz, exceeding the maximum frequency that our signal acquisition card can receive and process. Therefore, we need to use inverse mixing to down-convert the frequency. In this case, the readout signal is input from the RF (radio frequency) terminal of the IQ mixer, and the carrier is input from the LO terminal. The outputs of the I and Q terminals of the IQ mixer are the signals we need to detect.

[0043] 5. Rabi oscillation: For a two-level system (such as a quantum bit), when the frequency of the incident electromagnetic wave is exactly equal to the energy difference between the two levels, the atoms in the system will continuously transition between the two energy levels. This phenomenon is called Rabi oscillation.

[0044] 6. Ramsey Interference: Ramsey measurement is an efficient method based on the Ramsey interference principle. By applying two π / 2 pulses to a qubit and changing the time interval τ between the two pulses, oscillations of the |1> state probability caused by phase accumulation can be observed. The oscillation frequency reflects the detuning Δf. It is used in quantum computing for frequency calibration and dynamic adjustment and is an indispensable tool in qubit research and applications.

[0045] 7. Visibility: On the IQ signal plane obtained from quantum state reading, it is used to characterize the degree of distinguishability of different quantum states of a qubit in the measurement results. The higher the value, the more accurate the quantum state identification.

[0046] 8. Two-photon excitation: Two-photon absorption is the process by which a medium absorbs two photons. In this process, each individual photon lacks sufficient energy to excite a molecule to an excited state. Instead, the two photons work together, moving from the ground state through a virtual state to the excited state. This process involves the absorption of two photons in total, hence the name two-photon absorption. This situation may occur during qubit calibration if the microwave frequency and intensity are not properly selected.

[0047] 9. Crosstalk excitation: refers to the interference phenomenon caused by unintended electromagnetic coupling between qubits or leakage of control pulse signals, which leads to the operation of the target qubit causing neighboring qubits to be erroneously excited to non-target energy levels.

[0048] 10. Read Z-pulse amplitude (read zpa): The amplitude parameter of the low-frequency electrical pulse applied to optimize the accuracy of qubit state measurement. By adjusting this amplitude, the influence of impurity energy levels on the readout can be reduced, and the coupling between the qubit energy level and the readout resonant cavity can be adjusted, thereby enhancing quantum state discrimination and improving readout fidelity. Detailed Implementation

[0049] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of this application. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0050] Figure 1 This is a flowchart illustrating the process of determining the excitation frequency of a superconducting quantum bit according to an embodiment of this application.

[0051] In one embodiment, a qubit spectroscopy experiment can be performed to determine the qubit excitation frequency. In step 11, for two sideband frequencies that differ in magnitude by a predetermined value, for example, a predetermined value of 300 MHz, where the first sideband frequency is -100 MHz and the second sideband frequency is 200 MHz, the qubit to be calibrated is scanned using a microwave drive frequency to obtain the phase spectrum γ of the IQ (In-phase / Quadrature-phase) signal of the qubit corresponding to the first and second sideband frequencies, respectively. p (s,f) and amplitude spectrum γ a (s,f), such as Figure 2 and Figure 3 As shown. During superconducting quantum bit readout, the signal is represented using "IQ data" (In-phase / Quadrature-phase). IQ data represents two orthogonal components of a complex signal: I (In-phase): the component in phase with the reference carrier; Q (Quadrature): the component out of phase with the reference carrier by 90°. These two components together constitute a complex signal: IQ = I + iQ. The microwave driving frequency range is related to the excitation frequency, for example, it can be from 4 GHz to 5 GHz.

[0052] It is understood that the values ​​of the two sideband frequencies and the predetermined difference between them are not limited to the above embodiments. Those skilled in the art can choose appropriate values ​​according to actual needs. This application does not limit them in any way, and all of them are within the scope of this application.

[0053] Next, in step 12, the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency, respectively, can be processed to determine the processed phase spectrum and the processed amplitude spectrum. In a specific embodiment, the phase spectrum and amplitude spectrum corresponding to the first sideband frequency can be shifted by a predetermined value to the position corresponding to the second sideband frequency, or the phase spectrum and amplitude spectrum corresponding to the second sideband frequency can be shifted by a predetermined value to the position corresponding to the first sideband frequency. Then, the phase spectrum corresponding to the first sideband frequency and the phase spectrum corresponding to the second sideband frequency are subtracted, and the amplitude spectrum corresponding to the first sideband frequency and the amplitude spectrum corresponding to the second sideband frequency are subtracted to obtain the processed phase spectrum and the processed amplitude spectrum.

[0054] For example, shifting the data coordinate axis from -100MHz to the right by 300MHz yields the phase spectrum γ. p (-100, f+300) and amplitude spectrum γ a (-100, f+300), then subtract the 100MHz phase spectrum and amplitude spectrum data from the 200MHz phase spectrum and amplitude spectrum data respectively to obtain the processed phase spectrum γ. p (200,f)-γ p (-100, f+300) and amplitude spectrum γ a (200,f)-γ a (-100, f+300), the result is as follows Figure 4 As shown, you can see Figure 2 and Figure 3 The chaotic energy spectrum peaks disappeared, leaving only two prominent bit peaks.

[0055] Next, in step 13, double Gaussian fitting can be performed on the processed phase spectrum and the processed amplitude spectrum respectively to calculate the excitation frequencies obtained from the processed phase spectrum and the processed amplitude spectrum, which are the phase characteristic frequency and the amplitude characteristic frequency respectively.

[0056] In one specific embodiment, the double Gaussian fitting equation can be expressed as follows:

[0057]

[0058] Where a represents the peak height (usually only one), f represents the microwave driving frequency, b represents the center position of the peak (corresponding to the excitation frequency of the bit), c measures the peak width, s1 and s2 represent the two selected sideband frequencies, residual represents the residual baseline, which is a constant, and g represents the fitted data. Within the preset microwave driving frequency range, the corresponding fitted data g can be determined at predetermined intervals (e.g., 1 MHz). Performing double Gaussian fitting on the processed phase spectrum and the processed amplitude spectrum respectively yields the phase characteristic frequencies f corresponding to the processed phase spectrum and the processed amplitude spectrum, respectively. phase 10 and amplitude characteristic frequency f amp 10.

[0059] In one embodiment, the phase characteristic frequency f can be used as a basis. phase 10 and amplitude characteristic frequency f amp 10. Determine the excitation frequency of the quantum bit to be calibrated. A preset threshold can be set. If the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency is not greater than the preset threshold, the arithmetic mean of the phase characteristic frequency and the amplitude characteristic frequency is determined as the excitation frequency of the quantum bit to be calibrated. In a specific embodiment, the preset threshold can be 20MHz, and the difference between the two is |f phase 10-f amp If 10 is less than 20MHz, it can be considered that the bit excitation frequency has been found, and its value can be determined as |f|. phase 10+f amp 10| / 2.

[0060] In some cases, the excitation peak of the bit to be calibrated may be sensitive to only one parameter (phase or amplitude) but not the other, resulting in the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency exceeding a preset threshold. In such cases, a confidence comparison is required. The confidence level indicates the goodness of fit between the processed phase spectrum and the processed amplitude spectrum using a double Gaussian difference method. For example, if the processed phase spectrum and / or amplitude spectrum are themselves a single Gaussian function or a straight line, the double Gaussian fit will usually be poor, and the confidence level will be correspondingly low. However, if the processed phase spectrum and / or amplitude spectrum are themselves double Gaussian functions, the fit will usually be good, and the confidence level will be correspondingly high.

[0061] In one specific embodiment, a preset range can be determined first. Based on the double Gaussian fitting equation and the corresponding error function, the first confidence level corresponding to the processed phase spectrum and the second confidence level corresponding to the processed amplitude spectrum are calculated respectively. Then, the excitation frequency of the bit to be calibrated is determined based on whether the ratio of the first confidence level to the second confidence level is within the preset range. If the ratio of the first confidence level to the second confidence level is not within the preset range, the larger confidence level is determined, and the frequency corresponding to the larger confidence level is determined as the excitation frequency of the quantum bit to be calibrated. If the ratio of the first confidence level to the second confidence level is within the preset range, the range of the microwave driving frequency and the scanning intensity can be adjusted, and the steps described above for scanning the quantum bit to be calibrated using the microwave driving frequency to determine the phase spectrum and amplitude spectrum can be returned to, and the excitation frequency can be recalculated.

[0062] The confidence level can be calculated using the following equation:

[0063] r=|a / θ|(2)

[0064] Where a represents the height of the peak, and θ represents the error function under the double Gaussian fitting equation.

[0065] In one specific embodiment, the error function can be calculated using the following formula:

[0066]

[0067] Within the preset microwave driving frequency range, corresponding fitting data g can be determined at predetermined intervals (e.g., 1 MHz), and correspondingly, n data points y can be determined. i and g i These represent the magnitudes of the phase spectrum or amplitude spectrum data and the fitted data at the i-th microwave driving frequency, respectively.

[0068] When calculating the confidence level based on the processed phase spectrum, obtain the confidence level r corresponding to the processed phase spectrum. phase However, when calculating the confidence level based on the processed amplitude spectrum, the confidence level r corresponding to the processed amplitude spectrum is obtained. amp .

[0069] The aforementioned preset range can be a suitable range set by technicians based on their experience, such as... Figure 1As shown, the confidence level can be between 0.67 and 1.5. If the ratio of the first confidence level to the second confidence level is not within the preset range, the larger confidence level between the first and second confidence levels is determined, and the frequency corresponding to the larger confidence level is determined as the excitation frequency of the quantum bit to be calibrated in the phase characteristic frequency and amplitude characteristic frequency. If the ratio of the first confidence level to the second confidence level is within the preset range, the range of the microwave driving frequency and the scanning intensity can be adjusted, and the steps of scanning the quantum bit to be calibrated using the microwave driving frequency to determine the phase spectrum and amplitude spectrum can be returned to, and the excitation frequency can be recalculated.

[0070] After determining the excitation frequency of the bit to be calibrated, other parameters can be determined. Figure 5 This is a schematic flowchart illustrating the process of determining the calibration parameters of a superconducting quantum bit according to an embodiment of this application. Figure 5 As shown, the excitation amplitude of the bit to be calibrated can then be determined.

[0071] It is understood that the calculation of the confidence level and error function is not limited to the method given in the above embodiments. Other alternative methods that can be conceived by those skilled in the art under the inspiration of this application are all within the scope of this application. The above-mentioned preset scope is not limited to the scope given in the above embodiments. Other suitable scopes that can be conceived by those skilled in the art under the inspiration of this application are all within the scope of this application.

[0072] In one embodiment, in step 14, a Rabi oscillation experiment can be performed to calibrate the excitation amplitude of the bit (i.e., the π pulse amplitude). As the microwave excitation amplitude continues to increase, the bit will oscillate back and forth between the |0> state and the |1> state, as... Figure 6 As shown, the amplitude spectrum and phase spectrum can be fitted with sinusoidal functions separately, and then averaged to roughly obtain the excitation amplitude of the bit to be calibrated.

[0073] In an optional embodiment, in step 15, after determining the excitation frequency and excitation amplitude of the bit to be calibrated, an IQ signal test can be performed on the current excitation frequency and excitation amplitude of the quantum bit to be calibrated. In one embodiment, in the IQ inverse mixing readout method, the difference between the |0> state (without π pulse) and the |1> state (with π pulse) of the bit is reflected in the planar distribution of the readout IQ signal. The visibility between the |0> state and the |1> state can be denoted as the first visibility. A preset value (first preset value) can be set, for example, 0.1. If the first visibility is less than the first preset value, for example, not less than 0.1, it indicates that the bit parameters (including excitation frequency and excitation amplitude) calibrated above are correct. Otherwise, further parameter adjustments are required, for example, changing the range of the microwave driving frequency and the scanning intensity of the scan bit, for example, expanding the range of the microwave driving frequency and increasing the scanning intensity, returning to the steps above of using the microwave driving frequency to scan the quantum bit to be calibrated to determine the phase spectrum and amplitude spectrum, and recalculating the excitation frequency and excitation amplitude.

[0074] The above steps provide a rough calibration of the bit parameters. Subsequent steps will perform automated, high-precision parameter calibration to achieve high-precision bit manipulation. Since the bit's excitation frequency and amplitude are the most critical parameters and influence each other, the excitation amplitude and frequency are calibrated first. However, reading the Z-pulse amplitude affects the optimal bit reading frequency; therefore, the reading frequency is calibrated last, as detailed below. Figure 5 As shown.

[0075] In one embodiment, in step 16, if the first discrimination is not less than a first preset value, fine adjustment of the excitation amplitude and excitation frequency of the bit is performed to obtain the optimized excitation frequency and optimized excitation amplitude. There is a correlation between the excitation amplitude and excitation frequency parameters, therefore cross-optimization is required. First, the excitation amplitude of the bit is slightly changed to find the excitation amplitude corresponding to the maximum probability of the |1> state after the bit is excited by a π pulse. Next, the excitation frequency of the bit is finely adjusted. This step can use the Ramsey interferometry calibration technique. Two π / 2 pulses are applied to the bit, and by changing the time interval τ between the two pulses, the oscillation of the |1> state probability caused by phase accumulation can be observed. The oscillation frequency can reflect the detuning Δf. This method has high accuracy and can reduce the excitation frequency error to within 0.1MHz. The above process can be repeated twice, thereby achieving high-precision calibration of the excitation amplitude and excitation frequency through two stages of cross-optimization.

[0076] Next, in an optional embodiment, in step 17, an IQ signal test can be performed based on the optimized excitation frequency and optimized excitation amplitude to determine the distinguishability between the |0> state and the |1> state, which can be denoted as the second distinguishability. A preset value (second preset value) can be set, for example, 0.1. If the second distinguishability is not less than the second preset value, for example, not less than 0.1, it indicates that the bit parameters (including excitation frequency and excitation amplitude) calibrated above are correct. Otherwise, it may indicate that the |0> state and the |1> state of the bit cannot be distinguished, and the bit excitation frequency may be two-photon excitation or crosstalk excitation, requiring further parameter adjustment. For example, the scanning intensity of the microwave driving frequency of the scanned bit can be changed, for example, the scanning intensity can be reduced. Then, return to the steps above of using the microwave driving frequency to scan the quantum bit to be calibrated to determine the phase spectrum and amplitude spectrum, and recalculate the excitation frequency and excitation amplitude.

[0077] In one embodiment, such as Figure 5 As shown, before step 11, which uses microwave driving frequency scanning to determine the phase spectrum and amplitude spectrum of the quantum bit to be calibrated, step 10 involves scanning the quantum bit to be calibrated within its corresponding design microwave frequency band to determine the estimated readout power and estimated readout frequency. In one specific embodiment, scanning the readout frequency and readout power of a quantum bit to be calibrated can be achieved by continuously inputting microwave signals of different frequencies and powers within its design microwave frequency band range (e.g., the design microwave frequency band corresponding to the quantum bit, such as 6 GHz to 7 GHz) to obtain the absorption spectrum of the readout signal, thereby determining the approximate estimated readout power and readout frequency.

[0078] like Figure 5 As shown, after determining the optimized excitation frequency and optimized excitation amplitude, the read power of the bit can be fine-tuned in step 18. In one embodiment, if the second discrimination is not less than the second preset value, an IQ signal test can be performed based on the optimized excitation frequency and optimized excitation amplitude to determine the discrimination of the |0> state and |1> state corresponding to the range near the estimated read power (which can correspond to the ranges on both sides of the estimated read power), which can be denoted as the third discrimination. Figure 7 As shown, different read powers are tried in the range of the estimated read power to find the read power corresponding to the maximum third discrimination.

[0079] In one embodiment, if the second discrimination is not less than the second preset value, IQ signal testing can be performed based on the optimized excitation frequency and optimized excitation amplitude to determine the third discrimination of the |0> state and |1> state corresponding to the preset range of the estimated read power; the read power corresponding to the maximum value in the third discrimination is determined as the read power of the quantum bit to be calibrated.

[0080] like Figure 5As shown, after determining the optimized excitation frequency, optimized excitation amplitude, and read power of the quantum bit to be calibrated, the read Z-pulse amplitude of the bit to be calibrated can be determined in step 19. In one embodiment, an IQ signal test can be performed based on the optimized excitation frequency, optimized excitation amplitude, and read power of the quantum bit to be calibrated to determine the discrimination between the |0> state and the |1> state corresponding to the preset range of the read Z-pulse amplitude, which can be denoted as the fourth discrimination. Figure 8 As shown, different Z-pulse amplitude values ​​are tried within a preset range of reading Z-pulse amplitude values ​​to find the reading Z-pulse amplitude value corresponding to the maximum fourth discrimination.

[0081] In the above embodiment for determining the reading Z-pulse amplitude of the bit to be calibrated, on the one hand, since there may be some impurity energy levels near the excitation frequency of the bit, the reading of the bit is disturbed. By changing the magnitude of the reading Z-pulse amplitude, the bit is read at a relatively clean energy level, thereby achieving the optimal distinguishability. On the other hand, the reading Z-pulse amplitude may also increase the dispersion shift during resonant cavity reading, thereby enhancing the quantum state distinguishability and improving the reading fidelity.

[0082] like Figure 5 As shown, after determining the optimized excitation frequency, optimized excitation amplitude, read power of the quantum bit to be calibrated, and read Z-pulse amplitude, the read frequency of the quantum bit to be calibrated can be determined in step 20. In one embodiment, IQ signal testing can be performed based on the optimized excitation frequency, optimized excitation amplitude, read power of the quantum bit to be calibrated, and read Z-pulse amplitude to determine the IQ signal center distances of the |0> and |1> states within a preset range of the estimated read frequency; the read frequency corresponding to the maximum value of the center distance is determined as the read frequency of the quantum bit to be calibrated. Figure 9 As shown, around the estimated read frequency, different read frequencies are used to measure the distance between the IQ signal centers of the |0> state and the |1> state. The read frequency corresponding to the maximum distance between the IQ signal centers of the |0> state and the |1> state is selected as the read frequency of the quantum bit to be calibrated.

[0083] In an optional embodiment, each step and result of the above optimization process can be returned in the form of a list to complete the automated calibration of a single bit.

[0084] Based on the techniques described above, according to one aspect of this application, a method for calibrating superconducting qubits is provided. Figure 10 This is a flowchart of a method for calibrating superconducting qubits according to the first embodiment of this application. Figure 10 As shown, the method includes the following steps:

[0085] Step S1001: At the first sideband frequency and the second sideband frequency, the quantum bits to be calibrated are scanned using microwave driving frequency to obtain the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency, respectively.

[0086] Step S1002: Process the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency respectively, and determine the processed phase spectrum and the processed amplitude spectrum.

[0087] Step S1003: Perform double Gaussian fitting on the processed phase spectrum and the processed amplitude spectrum respectively, and calculate the phase characteristic frequency and amplitude characteristic frequency corresponding to the processed phase spectrum and the processed amplitude spectrum respectively; and

[0088] Step S1004: Determine the excitation frequency of the quantum bit to be calibrated based on the phase characteristic frequency and the amplitude characteristic frequency.

[0089] In an optional embodiment, step S1004 may include:

[0090] If the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency is not greater than a preset threshold, the arithmetic mean of the phase characteristic frequency and the amplitude characteristic frequency is determined as the excitation frequency of the quantum bit to be calibrated.

[0091] In an optional embodiment, step S1004 may include:

[0092] If the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency is greater than the preset threshold, the first confidence level corresponding to the processed phase spectrum and the second confidence level corresponding to the processed amplitude spectrum are calculated according to the double Gaussian fitting equation and the corresponding error function, respectively.

[0093] If the ratio of the first confidence level to the second confidence level is not within a preset range, the larger confidence level between the first and second confidence levels is determined, and the frequency corresponding to the larger confidence level is determined as the excitation frequency of the quantum bit to be calibrated, between the phase characteristic frequency and the amplitude characteristic frequency; and

[0094] If the ratio of the first confidence level to the second confidence level is within a preset range, adjust the range of the microwave driving frequency and the scanning intensity, and return to step S1001.

[0095] Figure 11 This is a flowchart of a method for calibrating superconducting qubits according to a second embodiment of this application. Figure 10 compared to, Figure 11Steps S1101 to S1104 of the method shown are Figure 10 Steps S1001 to S1004 are the same, the difference is that... Figure 11 The method shown may also include:

[0096] Step S1105: The excitation amplitude of the quantum bit to be calibrated is determined by Rabi oscillation experiment.

[0097] Figure 12 This is a flowchart of a method for calibrating superconducting qubits according to a third embodiment of this application. Figure 11 compared to, Figure 12 Steps S1201 to S1205 of the method shown are Figure 11 Steps S1101 to S1105 are the same, the difference is that... Figure 12 The method shown may also include (to highlight the difference, Figure 12 Show only Figure 11 Different steps):

[0098] Step S1206: Perform IQ signal testing on the quantum bit to be calibrated based on its excitation frequency and excitation amplitude to determine the first distinguishability between the ground state and excited state of the quantum bit to be calibrated; and

[0099] In step S1207, in response to the first discrimination being less than a first preset value, the range of the microwave driving frequency and the scanning intensity are adjusted, and the process returns to step S1201.

[0100] Figure 13 This is a flowchart of a method for calibrating superconducting qubits according to a fourth embodiment of this application. Figure 12 compared to, Figure 13 Steps S1301 to S1307 of the method shown are Figure 12 Steps S1201 to S1207 are the same, the difference is that... Figure 13 The method shown may also include (to highlight the difference, Figure 13 Show only Figure 12 Different steps):

[0101] Step S1308: In response to the first discrimination index being not less than the first preset value, adjust the excitation frequency and excitation amplitude of the quantum bit to be calibrated to obtain the optimized excitation frequency and optimized excitation amplitude.

[0102] Step S1309: Perform IQ signal testing based on the optimized excitation frequency and the optimized excitation amplitude to determine the second distinguishing factor between the ground state and the excited state of the quantum bit to be calibrated; and

[0103] In step S1310, in response to the second discrimination being less than the second preset value, the scanning intensity of the microwave driving frequency is adjusted, and the process returns to step S1301.

[0104] Figure 14 This is a flowchart of a method for calibrating superconducting qubits according to the fifth embodiment of this application. Figure 13 compared to, Figure 14 Steps S1401 to S1410 of the method shown are Figure 13 Steps S1301 to S1310 are the same, the difference is that... Figure 14 The method shown may also include (to highlight the difference, Figure 14 Show only Figure 13 Different steps):

[0105] Step S1411: In response to the second discrimination degree being not less than the second preset value, perform IQ signal testing based on the optimized excitation frequency and the optimized excitation amplitude to determine a third discrimination degree for the ground state and excited state of the quantum bit to be calibrated within a preset range of the estimated readout power; and

[0106] Step S1412: The reading power corresponding to the maximum value in the third discrimination index is determined as the reading power of the quantum bit to be calibrated.

[0107] Figure 15 This is a flowchart of a method for calibrating superconducting qubits according to the sixth embodiment of this application. Figure 14 compared to, Figure 15 Steps S1501 to S1512 of the method shown are Figure 14 Steps S1401 to S1412 are the same, the difference is that... Figure 15 The method shown may also include (to highlight the difference, Figure 15 Show only Figure 14 Different steps):

[0108] Step S1513: Perform IQ signal testing based on the optimized excitation frequency, the optimized excitation amplitude, and the readout power of the quantum bit to be calibrated, to determine the fourth discrimination of the ground state and excited state of the quantum bit to be calibrated within a preset range of the readout Z pulse amplitude; and

[0109] Step S1514: The reading power corresponding to the maximum value in the fourth discrimination is determined as the reading Z pulse amplitude of the quantum bit to be calibrated.

[0110] Figure 16 This is a flowchart of a method for calibrating superconducting qubits according to the seventh embodiment of this application. Figure 15 compared to, Figure 16Steps S1601 to S1614 of the method shown are Figure 15 Steps S1501 to S1514 are the same, the difference is that... Figure 16 The method shown may also include (to highlight the difference, Figure 16 Show only Figure 15 Different steps):

[0111] Step S1615: Perform IQ signal testing based on the optimized excitation frequency and the optimized excitation amplitude, the readout power of the quantum bit to be calibrated, and the readout Z-pulse amplitude of the quantum bit to be calibrated, to determine the IQ signal center distance between the ground state and the excited state within a preset range of the estimated readout frequency; and

[0112] Step S1616: Determine the reading frequency corresponding to the maximum value in the center distance as the reading frequency of the quantum bit to be calibrated.

[0113] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0114] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily essential to this application.

[0115] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between devices or units may be an electrical connection or other forms.

[0116] See Figure 17 , Figure 17 An electronic device is provided, including a processor and a memory. The memory stores computer instructions or one or more programs, which, when executed by the processor, cause the processor to execute the computer instructions to achieve the following: Figures 10 to 16 The method and its detailed scheme are shown.

[0117] It should be understood that the above-described device embodiments are merely illustrative, and the device disclosed in this invention can be implemented in other ways. For example, the division of units / modules described in the above embodiments is only a logical functional division, and there may be other division methods in actual implementation. For example, multiple units, modules, or components may be combined, integrated into another system, or some features may be ignored or not executed.

[0118] Furthermore, unless otherwise specified, the functional units / modules in the various embodiments of the present invention can be integrated into one unit / module, or each unit / module can exist physically separately, or two or more units / modules can be integrated together. The integrated units / modules described above can be implemented in hardware or as software program modules.

[0119] If the integrated unit / module is implemented in hardware, the hardware can be digital circuits, analog circuits, etc. The physical implementation of the hardware structure includes, but is not limited to, transistors, memristors, etc. Unless otherwise specified, the processor or chip can be any suitable hardware processor, such as a CPU, GPU, FPGA, DSP, and ASIC, etc. Unless otherwise specified, the on-chip cache, off-chip memory, and storage can be any suitable magnetic or magneto-optical storage medium, such as resistive random access memory (RRAM), dynamic random access memory (DRAM), static random access memory (SRAM), enhanced dynamic random access memory (EDRAM), high-bandwidth memory (HBM), hybrid memory cube (HMC), etc.

[0120] If the integrated unit / module is implemented as a software program module and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer electronic device (which may be a personal computer, server, or network electronic device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this disclosure. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0121] This application also provides a computer-readable storage medium storing one or more computer programs, which, when executed by multiple processors, cause the processors to perform the following actions: Figures 10 to 16 The method and its detailed scheme are shown.

[0122] This application also provides a computer program product, which includes a computer program that, when run on a computer, causes the computer to perform the methods of any of the above embodiments.

[0123] According to the superconducting qubit calibration method, electronic device, and computer-readable storage medium provided in this application, the problem of energy spectrum clutter interference caused by AWG carrier leakage in the mixing frequency is solved by using dynamic processing of sideband frequencies (e.g., steps 11-12) and an antisymmetric double Gaussian fitting algorithm (e.g., step 13). This achieves automated calibration of the qubit excitation frequency, reduces reliance on highly skilled operators, lowers labor costs, and avoids the inefficient traditional manual parameter-by-parameter adjustment mode. This application utilizes differential processing of double-sideband frequency data (e.g., step 12) to effectively suppress eigenvalue clutter, and combined with confidence criteria (e.g., step 13), significantly improves the noise resistance of excitation frequency extraction. By employing parameter correlation optimization logic, through a cross-optimization process (e.g., step 16) and a dynamic parameter adjustment sequence (e.g., steps 17 to 20), the accuracy of qubit system calibration is improved; for example, the error can be reduced to 0.1MHz.

[0124] Furthermore, this application, based on experimental measurement data, achieves calibration through dynamic parameter correlation (e.g., steps 16 to 20), thus eliminating the dependence of existing automated solutions on theoretical values. It is particularly suitable for scenarios where process fluctuations cause parameters to deviate from expectations and where parameters do not have fixed theoretical values. Compared to existing neural network models, this application does not require training with massive amounts of real data and only requires a small number of experimental scans to complete the calibration, significantly saving time and computing resources and breaking through the bottleneck of data demand.

[0125] This application's solution achieves highly efficient, highly accurate, and highly robust fully automated calibration through parameter correlation optimization logic and feedback mechanism, providing key technical support for the engineering deployment of large-scale quantum computing systems. It is of great significance for promoting the practical application of quantum computing technology and further scientific research.

[0126] References to features, advantages, or similar language in this specification do not imply that all features and advantages achievable with this solution should be included or included in any single implementation thereof. Rather, references to features and advantages are understood to mean that a particular feature, advantage, or characteristic described in connection with an embodiment is included in at least one embodiment of this solution. Therefore, discussions of features, advantages, and similar language throughout this specification may, but do not necessarily, refer to the same embodiments.

[0127] Furthermore, the features, advantages, and characteristics described herein can be combined in any suitable manner in one or more embodiments. Based on the description herein, those skilled in the art will recognize that this solution can be implemented without one or more specific features or advantages of a particular embodiment. In other instances, additional features and advantages can be appreciated in specific embodiments not presented in all embodiments of this solution.

[0128] The embodiments of this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of this application. Furthermore, any changes or modifications made by those skilled in the art based on the ideas of this application, and on the specific implementation methods and application scope of this application, are all within the scope of protection of this application. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A method for calibrating superconducting qubits, characterized in that: (a) At the first sideband frequency and the second sideband frequency, the quantum bits to be calibrated are scanned by microwave driving frequency to obtain the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency, respectively. (b) Process the phase spectrum and amplitude spectrum corresponding to the first sideband frequency and the second sideband frequency respectively, and determine the processed phase spectrum and the processed amplitude spectrum; (c) Perform double Gaussian fitting on the processed phase spectrum and the processed amplitude spectrum respectively, and calculate the phase characteristic frequency and amplitude characteristic frequency corresponding to the processed phase spectrum and the processed amplitude spectrum respectively; as well as (d) Determine the excitation frequency of the quantum bit to be calibrated based on the phase characteristic frequency and the amplitude characteristic frequency.

2. The method as described in claim 1, characterized in that, Also includes: The excitation amplitude of the quantum qubit to be calibrated was determined using a Rabi oscillation experiment.

3. The method as described in claim 2, characterized in that, Also includes: Based on the excitation frequency and excitation amplitude of the quantum bit to be calibrated, perform IQ signal testing on the quantum bit to be calibrated to determine the first distinguishability between the ground state and the excited state of the quantum bit to be calibrated; as well as In response to the first discrimination being less than a first preset value, the range of the microwave driving frequency and the scanning intensity are adjusted, and the process returns to step (a).

4. The method as described in claim 3, characterized in that, After determining the first distinguishability of the ground state and excited state of the quantum bit to be calibrated, the method further includes: In response to the first discrimination index being not less than the first preset value, the excitation frequency and excitation amplitude of the quantum bits to be calibrated are adjusted to obtain the optimized excitation frequency and optimized excitation amplitude. Based on the optimized excitation frequency and the optimized excitation amplitude, IQ signal testing is performed to determine the second distinguishing factor between the ground state and the excited state of the quantum bit to be calibrated; and In response to the second discrimination being less than the second preset value, the scanning intensity of the microwave driving frequency is adjusted, and the process returns to step (a).

5. The method as described in claim 4, characterized in that, Prior to step (a), the method further includes: Within the design microwave frequency band corresponding to the quantum bit to be calibrated, the quantum bit to be calibrated is scanned to determine the estimated readout power and the estimated readout frequency; The method further includes, after determining the second distinguishability of the ground state and excited state of the quantum bit to be calibrated: In response to the second discrimination index being not less than the second preset value, an IQ signal test is performed based on the optimized excitation frequency and the optimized excitation amplitude to determine a third discrimination index of the ground state and excited state of the quantum bit to be calibrated within the preset range of the estimated readout power; and The read power corresponding to the maximum value in the third discrimination index is determined as the read power of the quantum bit to be calibrated.

6. The method as described in claim 5, characterized in that, Also includes: Based on the optimized excitation frequency, the optimized excitation amplitude, and the read power of the quantum bit to be calibrated, perform IQ signal testing to determine the fourth discrimination of the ground state and excited state of the quantum bit to be calibrated within a preset range of the read Z pulse amplitude. as well as The reading power corresponding to the maximum value in the fourth discrimination is determined as the reading Z-pulse amplitude of the quantum bit to be calibrated.

7. The method as described in claim 6, characterized in that, Also includes: Based on the optimized excitation frequency and the optimized excitation amplitude, the read power of the quantum bit to be calibrated and the read Z pulse amplitude of the quantum bit to be calibrated, perform IQ signal testing to determine the IQ signal center distance between the ground state and the excited state within the preset range of the estimated read frequency; as well as The reading frequency corresponding to the maximum value in the center distance is determined as the reading frequency of the quantum bit to be calibrated.

8. The method according to any one of claims 1 to 6, characterized in that, Step (d) includes: If the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency is not greater than a preset threshold, the arithmetic mean of the phase characteristic frequency and the amplitude characteristic frequency is determined as the excitation frequency of the quantum bit to be calibrated.

9. The method according to any one of claims 1 to 6, characterized in that, Step (d) includes: If the absolute value of the difference between the phase characteristic frequency and the amplitude characteristic frequency is greater than the preset threshold, the first confidence level corresponding to the processed phase spectrum and the second confidence level corresponding to the processed amplitude spectrum are calculated according to the double Gaussian fitting equation and the corresponding error function, respectively. If the ratio of the first confidence level to the second confidence level is not within a preset range, the larger confidence level between the first and second confidence levels is determined, and the frequency corresponding to the larger confidence level is determined as the excitation frequency of the quantum bit to be calibrated, between the phase characteristic frequency and the amplitude characteristic frequency; and If the ratio of the first confidence level to the second confidence level is within the preset range, adjust the range of the microwave driving frequency and the scanning intensity, and return to step (a).

10. An electronic device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and the processor, when executing the computer program in the memory, implements the method of any one of claims 1 to 9.

11. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method of any one of claims 1 to 9.

Images