A frequency calibration method, device, equipment and readable storage medium

Abstract

The application discloses a kind of reading frequency calibration method, device, equipment and readable storage medium, applied to quantum field, comprising: frequency scanning is carried out to the reading cavity on reading line, and scanning data is obtained;Based on scanning data, adaptive peak searching is handled, and the number of frequency obtained by peak searching is consistent with the number of reading cavity by parameter adjustment, and reading frequency candidate list is generated;Actual reading frequency corresponding to each peak value is contained in reading frequency candidate list;Based on reading frequency candidate list, to be verified reading frequency is allocated for each quantum bit, frequency scanning is carried out by changing the signal bias of quantum bit, determines the reading cavity bound to each quantum bit, and the final corresponding reading frequency.The application can automatically calibrate the reading frequency of all reading cavities on a reading line and confirm its connection relationship with quantum bit, guarantee the accuracy of subsequent quantum bit state reading, and reduce the resource consumption of manpower and time.

Description

Technical Field

[0001] This invention relates to the quantum field, and in particular to a method, apparatus, device, and readable storage medium for reading frequency calibration. Background Technology

[0002] In the research and application of superconducting quantum chips, although the one-to-one binding relationship between qubits and the readout cavity is initially set by the design parameters, and the readout frequency of the readout cavity also has a corresponding design benchmark value, two core problems easily occur simultaneously in practical scenarios due to factors such as chip fabrication process errors, microwave link interference, and device operating condition drift: First, the preset binding relationship between qubits and the readout cavity may be incorrectly mapped, resulting in a failure of their physical association; second, the actual readout frequency of the readout cavity may deviate from the design value, requiring precise recalibration. These problems affect the effectiveness and accuracy of qubit state reading. Currently, manual calibration is generally used, but this method is inefficient for quantum readout frequency calibration and is resource-intensive for chips containing a large number of qubits.

[0003] Therefore, how to achieve accurate calibration of automated qubit readout frequency in order to reduce human resource consumption and improve calibration efficiency is a technical problem that urgently needs to be solved. Summary of the Invention

[0004] In view of this, the purpose of the present invention is to provide a reading frequency calibration method, apparatus, device and readable storage medium, which solves the problems of low calibration efficiency and difficulty in guaranteeing accuracy of quantum bit reading frequency in the prior art.

[0005] To solve the above-mentioned technical problems, the present invention provides a reading frequency calibration method, comprising: Frequency scanning is performed on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude. Based on the scan data, adaptive peak finding processing is performed, and the number of frequencies obtained by peak finding is consistent with the number of reading cavities by parameter adjustment, thereby generating a reading frequency candidate list; the reading frequency candidate list contains the actual reading frequency corresponding to each peak. Based on the candidate list of readout frequencies, a readout frequency to be verified is assigned to each qubit. By changing the signal bias of the qubit, a frequency scan is performed to determine the readout cavity bound to each qubit and the final corresponding readout frequency.

[0006] On the one hand, adaptive peak finding processing is performed based on the scan data, and the number of frequencies obtained by peak finding is made consistent with the number of readout cavities through parameter adjustment, generating a candidate list of readout frequencies, including: Calculate the adaptive peak height threshold and identify valid peaks from the scan data; By dynamically adjusting the noise level parameter in the peak height threshold, the number of actual read frequencies corresponding to the effective peaks is made consistent with the number of read cavities; Extract the actual reading frequencies corresponding to all the valid peaks to generate the candidate list of reading frequencies.

[0007] On the one hand, calculating the adaptive peak height threshold and identifying valid peaks from the scan data includes: Calculate the amplitude difference between the largest and smallest amplitude values ​​in the scanned data, and divide all amplitude values ​​in the scanned data by the amplitude difference to obtain the normalized amplitude value; The normalized amplitude is inverted to obtain the preprocessed scan data; the preprocessed scan data is a two-dimensional dataset of frequency and inverted normalized amplitude. The peak height threshold is calculated based on the average value of the inverted normalized amplitude, the noise level parameter, and the standard deviation of the inverted normalized amplitude. Peaks in the preprocessed scan data whose inverted normalized amplitude exceeds the peak height threshold are identified as valid peaks.

[0008] On the one hand, by dynamically adjusting the noise level parameter in the peak height threshold, the number of actual read frequencies corresponding to the effective peaks is made consistent with the number of read cavities, including: The peak height threshold is calculated by combining the preset initial noise level with the average value and the standard deviation. Based on the peak height threshold, the amplitude values ​​after inversion and normalization in the preprocessed scan data are compared with the threshold to identify the effective peaks. The number of actual read frequencies corresponding to the effective peaks is counted. If the number of actual read frequencies is less than the number of read cavities, the noise level is reduced by a preset step size, and the peak height threshold is recalculated. If the number of actual reading frequencies is greater than the number of reading cavities, the noise level is increased by a preset step size, and the peak height threshold is recalculated. The peak height threshold is iteratively updated and valid peaks are re-identified until the number of actual frequencies corresponding to the valid peaks is consistent with the number of read cavities.

[0009] On the one hand, based on the candidate list of readout frequencies, a readout frequency to be verified is assigned to each qubit. Frequency scanning is performed by changing the signal bias of the qubit to determine the readout cavity bound to each qubit and the final corresponding readout frequency, including: A readout frequency candidate list is generated for each of the qubits, and the initial readout frequency of each qubit is placed at the beginning of the readout frequency candidate list corresponding to each qubit. The actual read frequencies in the candidate read frequency list are sequentially traversed and set as the read frequencies to be verified. For each read frequency to be verified, the frequency rescan is performed on the read cavity on the read line by changing the signal bias of the corresponding qubit to detect the shift state of the effective peak; Based on the movement state of the effective peak, determine the matching relationship between the current read frequency to be verified and the read cavity, and lock the read cavity bound to each of the qubits one by one, as well as the read frequency corresponding to the read cavity.

[0010] On the one hand, before generating the readout frequency candidate list for each of the qubits and placing the initial readout frequency of each qubit at the beginning of the readout frequency candidate list corresponding to each qubit, the method further includes: Sort the actual read frequencies in the candidate read frequency list in descending order to obtain the sorted frequencies; The qubits on the read line are sorted according to the design intrinsic frequencies and rules to obtain the sorted qubits; The sorted frequencies are matched one-to-one with the sorted qubits to obtain the initial readout frequency assigned to each qubit.

[0011] On the one hand, the matching relationship between the current read frequency to be verified and the read cavity is determined based on the shift state of the effective peak, and the read cavity bound to each of the qubits and the read frequency corresponding to the read cavity are locked one by one, including: If the effective peak shifts, the reading cavity corresponding to the current reading frequency to be verified is determined to be the reading cavity bound to the current qubit, the current reading frequency to be verified is determined to be the reading frequency corresponding to the bound reading cavity, and the reading frequency to be verified is removed from the reading frequency candidate list of all other qubits. If the effective peak does not shift, the read frequency to be verified is removed from the candidate list of read frequencies for the current qubit and the process continues to traverse the next candidate frequency until a binding read cavity and corresponding read frequency are locked for the current qubit.

[0012] The present invention also provides a frequency calibration device, comprising: The frequency scanning module is used to perform frequency scanning on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude. An adaptive peak finding module is used to perform adaptive peak finding processing based on the scan data, and adjust parameters to make the number of frequencies obtained by peak finding consistent with the number of read chambers, thereby generating a candidate list of read frequencies; the candidate list of read frequencies contains the actual read frequencies corresponding to each peak. The mapping update module is used to assign a read frequency to be verified to each qubit based on the read frequency candidate list, and to perform frequency scanning by changing the signal bias of the qubit to determine the read cavity bound to each qubit and the final corresponding read frequency.

[0013] The present invention also provides a frequency calibration reading device, comprising: Memory, used to store computer programs; A processor, used to implement the read frequency calibration method as described above when executing the computer program.

[0014] The present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the read frequency calibration method described above.

[0015] The present invention also provides a computer program product, including a computer program / instruction, which, when executed by a processor, implements the steps of the above-described frequency calibration method.

[0016] As can be seen from the above technical solution, the present invention obtains scan data by performing frequency scanning on the readout cavities on the readout line; the scan data is a two-dimensional dataset of frequency and amplitude; adaptive peak finding processing is performed based on the scan data, and the number of frequencies obtained by peak finding is consistent with the number of readout cavities by adjusting parameters, thereby generating a readout frequency candidate list; the readout frequency candidate list contains the actual readout frequency corresponding to each peak; a readout frequency to be verified is assigned to each qubit based on the readout frequency candidate list, and frequency scanning is performed by changing the signal bias of the qubit to determine the readout cavity bound to each qubit and the final corresponding readout frequency.

[0017] The beneficial effects of this invention are as follows: By frequency scanning and adaptive peak finding and matching the number of frequencies, the actual reading frequency of each readout cavity is accurately obtained, providing a precise basis for reading frequency calibration that fits the actual chip, thus solving the problem of lacking a precise calibration benchmark for reading frequency; after allocating the readout frequencies to be verified based on the candidate list, the weak coupling characteristics between the qubit and the bound readout cavity are utilized, and the actual binding relationship between the qubit and the readout cavity can be accurately determined by changing the signal bias rescan and based on the peak shift state, solving the problem of easy mapping errors in the preset binding relationship between the two; the precise calibration of the reading frequency achieves precise matching between the reading frequency and the actual reading frequency of the qubit-bound readout cavity, ensuring that the microwave signal corresponding to the reading frequency can accurately capture the cavity response signal modulated by the qubit state. From the two core dimensions of frequency parameter matching and physical binding correspondence, the key obstacles affecting qubit state reading are eliminated, ultimately effectively ensuring the effectiveness and accuracy of qubit state reading.

[0018] In addition, the present invention also provides a frequency calibration device, equipment and readable storage medium, which also have the above-mentioned beneficial effects. Attached Figure Description

[0019] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0020] Figure 1 A flowchart of a frequency reading method provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the structure of a frequency reading device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of a frequency reading device provided in an embodiment of the present invention. Detailed Implementation

[0021] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0022] Quantum computing is a novel computing technology that promises to surpass classical computing in solving some complex problems. Superconducting qubits (qubits) are one of the mainstream approaches to realizing quantum computers. Describing the state of a qubit in this system often requires a large number of parameters, which the quantum computer needs to adjust to a suitable operating state before performing calculations—a process known as qubit calibration. Due to the instability of qubit performance, qubit calibration is often complex and is generally performed manually. However, with the increasing scale of quantum chips and the growing number of qubits, this manual calibration becomes too time-consuming and labor-intensive, thus requiring an automated method for qubit parameter calibration. The first step in automated calibration is to confirm the presence of the qubit, which is typically detected through a connected readout cavity. Reading from the readout cavity requires applying microwave pulses of a specific frequency to the readout line; generally, multiple readout cavities are connected to a single readout line. Current technology involves manually identifying the readout frequency and adjusting the bit frequency to confirm the connection between the qubit and the cavity. Manually calibrating the quantum readout frequency is inefficient and resource-intensive, especially for chips containing a large number of qubits.

[0023] This invention provides an automated method for calibrating the readout frequency of quantum bits. This method can automatically calibrate the readout frequency of all readout cavities on a readout line and confirm their connection relationship with the quantum bits. Please refer to [link / reference needed] for details. Figure 1 , Figure 1 A flowchart illustrating a frequency reading method provided in an embodiment of the present invention. The method may include: S101: Perform frequency scanning on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude.

[0024] The execution entity in this embodiment is the terminal. It should be noted that multiple readout cavities are connected in series on a single readout line, each readout cavity uniquely binds to one qubit, and one qubit corresponds to only one readout cavity. This embodiment can automatically calibrate / calibrate the readout frequency according to the readout line. This embodiment does not limit the frequency scanning range; for example, it can be a large, undefined range, or it can be a preset, smaller range, as long as it includes the designed frequency of the readout cavities on the readout line. The scan data can be understood as a graph, i.e., an amplitude-frequency response graph, with frequency on the horizontal axis and amplitude on the vertical axis; or the scan data can also be a two-dimensional dataset, with a one-to-one correspondence between frequency and amplitude.

[0025] Furthermore, the aforementioned frequency scanning of the reading cavities on the reading line to obtain scanning data can specifically include: outputting microwave scanning signals to the reading line within a preset frequency band with a preset step size, and simultaneously acquiring the amplitude response data of each reading cavity on the reading line to the microwave signal at each frequency point, forming a two-dimensional scanning dataset with a one-to-one correspondence between frequency and amplitude; wherein, the preset frequency band is a scanning frequency band that can cover the design frequencies of all reading cavities on the reading line. For example, when performing frequency scanning on all reading cavities on a reading line, the scanning range should include the frequencies of all designed reading cavities. For instance, if a reading line has three reading cavities with design frequencies of 6.2GHz, 6.5GHz, and 6.8GHz, its frequency scanning range (preset frequency band) can be set to 6.0~7.0GHz.

[0026] S102: Perform adaptive peak finding processing based on the scan data, and adjust the parameters to make the number of frequencies obtained by peak finding consistent with the number of reading cavities, generating a candidate list of reading frequencies; the candidate list of reading frequencies contains the actual reading frequencies corresponding to each peak.

[0027] In this embodiment, to further improve the success rate and accuracy of peak finding, an adaptive peak finding algorithm based on parameter adjustment is provided. This embodiment does not limit the parameters. For example, it could be a noise level parameter, or it could be a peak significance parameter. Because there is a one-to-one correspondence between the readout cavity and the readout frequency, the frequency data obtained through adaptive peak finding should be consistent with the number of readout cavities. This generates a candidate readout frequency list, where the number of readout frequencies matches the number of readout cavities. In other words, the number of peaks should be consistent with the number of readout cavities.

[0028] Furthermore, adaptive peak finding processing is performed based on the scanned data, and the number of frequencies obtained from peak finding is made consistent with the number of read cavities through parameter adjustment, generating a candidate list of read frequencies. Specifically, this may include: calculating an adaptive peak height threshold and identifying valid peaks from the scanned data; dynamically adjusting the noise level parameter in the peak height threshold to make the number of actual read frequencies corresponding to valid peaks consistent with the number of read cavities; and extracting the actual read frequencies corresponding to all valid peaks to generate a candidate list of read frequencies. In this embodiment, background noise (such as circuit noise and electromagnetic interference) exists in the frequency scanned data. If peak finding is performed directly, noise may be misjudged as valid peaks of the read cavities. Therefore, the required peak height threshold for peak finding is dynamically adjusted according to the noise level parameter, and valid peaks are determined based on the peak height threshold. This achieves the purpose of noise reduction and accurate peak finding.

[0029] Further, calculating the adaptive peak height threshold and identifying valid peaks from the scan data can specifically include: calculating the amplitude difference between the largest and smallest amplitudes in the scan data, dividing all amplitudes in the scan data by the amplitude difference to obtain the normalized amplitude; inverting the normalized amplitude to obtain the preprocessed scan data; the preprocessed scan data is a two-dimensional dataset of frequency and inverted normalized amplitude; calculating the peak height threshold based on the average value of the inverted normalized amplitude, the noise level parameter, and the standard deviation of the inverted normalized amplitude; identifying peaks in the preprocessed scan data whose inverted normalized amplitude exceeds the peak height threshold as valid peaks. In this embodiment, for the reading cavity, valley finding is generally used. Therefore, the data is first preprocessed: (1) the amplitude difference between the largest and smallest amplitudes is calculated, and then all amplitude data are divided by the amplitude difference to perform amplitude normalization. (2) the normalized amplitude data is inverted to facilitate valley finding. That is, data2 = -data1 / (max(data) - min(data). Where max(data) is the maximum amplitude, min(data) is the minimum amplitude, data1 is all amplitudes, and data2 is the normalized amplitude. (3) The relationship between the peak height threshold and the noise level parameter is: height = mean(data2) + noise_level std(data2). Where height is the peak height threshold, mean(data2) is the average of the inverse normalized amplitude, noise_level is the noise level parameter, and std(data2) is the standard deviation of the inverse normalized amplitude.

[0030] Furthermore, the above-mentioned method of dynamically adjusting the noise level parameter in the peak height threshold to ensure that the number of actual read frequencies corresponding to effective peaks matches the number of read cavities can specifically include: calculating the peak height threshold based on a preset initial noise level, combined with the average value and standard deviation; comparing the amplitude values ​​after inversion and normalization in the preprocessed scan data based on the peak height threshold to identify effective peaks; counting the number of actual read frequencies corresponding to effective peaks; if the number of actual read frequencies is less than the number of read cavities, decreasing the noise level by a preset step size and recalculating the peak height threshold; if the number of actual read frequencies is greater than the number of read cavities, increasing the noise level by a preset step size and recalculating the peak height threshold; iteratively updating the peak height threshold and re-identifying effective peaks until the number of actual frequencies corresponding to effective peaks matches the number of read cavities. This embodiment does not limit the preset initial noise level; for example, it can be a high level, such as 3. When the peaks obtained from the scan are less than the number of read cavities on the read line, the noise level is decreased by a certain step size, for example, decreased by 1 or 0.5 at a time; if the peaks obtained from the scan are greater than the number of read cavities on the read line, the noise level is increased by a certain step size. If the number of peaks obtained from the scan is the same as the number of read cavities on the read line, the actual read frequencies corresponding to the scanned peaks (i.e., valid peaks) are stored in the experimental database as a read frequency candidate list [f1, f2, ..., fn], where n represents the total number of peaks, i.e., the total number of read cavities. The experimental database is used to store intermediate information during the execution process, such as the read frequency candidate list and the mapping relationship between qubits and read frequencies.

[0031] Furthermore, the previous scan result should be recorded during parameter adjustment. If the same result is obtained after lowering and then raising the noise level, it proves that the strategy of repeatedly adjusting the noise level has failed. In this case, other fitting parameter attributes (such as peak significance) can be modified. If the number of reading cavities is still not matched within the number of adjustment attempts, an error message is thrown and the parameters are manually set.

[0032] S103: Assign a readout frequency to be verified to each qubit based on the candidate readout frequency list, perform frequency scanning by changing the signal bias of the qubit, determine the readout cavity bound to each qubit, and the final corresponding readout frequency.

[0033] The purpose of this step is to verify and update the correspondence between the qubit and the readout frequency of the readout cavity. In this embodiment, the readout frequency to be verified is any frequency in the candidate readout frequency list. This embodiment does not limit the verification order; for example, the frequencies in the candidate readout frequency list can be verified sequentially, or the frequencies in the candidate readout frequency list can be verified out of order. This embodiment does not limit the verification end point; for example, the verification can end when one readout frequency is successfully verified, or the verification can end after all frequencies in the candidate readout frequency list have been verified. This embodiment uses the readout frequency as an intermediate carrier to achieve precise binding of the qubit, readout frequency, and readout cavity. While completing the final calibration of the readout frequency, it simultaneously verifies the actual binding relationship between the qubit and the readout cavity. This solves the problem of mapping errors that easily occur in the preset binding relationship and ensures the precise matching between the readout frequency and the actual frequency of the bound readout cavity. From the two key levels of physical binding relationship and frequency parameter matching, it effectively improves the effectiveness and accuracy of qubit state reading.

[0034] Furthermore, the above-mentioned allocation of a readout frequency to be verified for each qubit based on the readout frequency candidate list, and frequency scanning by changing the signal bias of the qubit to determine the readout cavity bound to each qubit and the final corresponding readout frequency, can specifically include: generating a readout frequency candidate list for each qubit and placing the initial readout frequency of each qubit at the beginning of the readout frequency candidate list corresponding to each qubit; sequentially traversing the actual readout frequencies in the readout frequency candidate list and setting them as the readout frequencies to be verified; for each readout frequency to be verified, performing frequency rescanning on the readout cavity on the readout line by changing the signal bias of the corresponding qubit to detect the shift state of the effective peak; determining the matching relationship between the current readout frequency to be verified and the readout cavity based on the shift state of the effective peak, and locking the readout cavity bound to each qubit one by one, as well as the readout frequency corresponding to the readout cavity.

[0035] In this embodiment, for each qubit, a copy of the candidate readout frequency list [f1, f2, ..., n] is made as its corresponding candidate readout frequency. The initial readout frequency of each qubit is moved to the front of the copied candidate frequency list, as it is highly likely to be correct. If successful, it avoids scanning other frequencies, thus improving calibration efficiency. This method improves the efficiency of binding matching by configuring a dedicated candidate list for each qubit and prioritizing the verification of the initial readout frequency. Simultaneously, it uses signal bias changes triggering coupling modulation and the effective peak shift state as core judgment criteria. Relying on the weak coupling physical characteristics of the qubit and the bound readout cavity, it achieves accurate determination of the binding relationship between the qubit and the readout cavity. Furthermore, it completes the final calibration of the readout frequency while determining the binding relationship, realizing an integrated operation of binding relationship verification and readout frequency calibration. This effectively solves the problem of incorrect mapping of the preset binding relationship between the qubit and the readout cavity, and ensures accurate matching between the readout frequency and the actual frequency of the bound readout cavity. From the two core dimensions of matching relationship and frequency parameters, it improves the effectiveness and accuracy of qubit state reading.

[0036] Furthermore, the above-mentioned determination of the matching relationship between the current read frequency to be verified and the read cavity based on the movement state of the effective peak, and the locking of the read cavity bound to each qubit and the read frequency corresponding to the read cavity, can specifically include: if the effective peak moves, then the read cavity corresponding to the current read frequency to be verified is determined to be the read cavity bound to the current qubit, the current read frequency to be verified is determined to be the read frequency corresponding to the bound read cavity, and the read frequency to be verified is removed from the read frequency candidate list of all other qubits; if the effective peak does not move, then the read frequency to be verified is removed from the read frequency candidate list of the current qubit and the next candidate frequency is traversed until the bound read cavity and the corresponding read frequency locked for the current qubit are determined.

[0037] It should be noted that in this embodiment, the effective peak movement refers not to any peak on the readout line, but to the effective peak corresponding to the current readout frequency to be verified. For each qubit, its corresponding readout frequency candidate list is traversed and set as the readout frequency to be verified. By changing the Z signal bias of the qubit, a scan is performed near the current readout frequency fi, and a peak-finding algorithm is used to find the peak. If the obtained effective peak moves, it means that the qubit corresponds to the current readout frequency to be verified, and the current readout frequency to be verified is removed from the readout frequency candidate list of other qubits. The final readout frequency candidate list of the qubit is set to the current readout frequency [fi], and the frequency traversal stops. If the position of the effective peak does not move, it means that the qubit is not connected to the current readout cavity, and the current readout frequency to be verified is removed from the readout frequency candidate list of the current qubit. This step is repeated to traverse all qubits. At this time, the final readout frequency candidate list [fi] corresponding to each qubit is detected. If there is one and only one value, it proves that the correspondence between the qubit and the readout frequency has been successfully updated. If an empty list or a multi-valued list exists, it indicates that some qubits have not found a corresponding readout cavity. In this case, a diagnostic procedure can be triggered, or an error can be thrown for manual handling.

[0038] Furthermore, during frequency rescanning of the read cavity on the read line, the same scan frequency range and scan step size as the first frequency scan are used. During the rescanning process, the peak position offset of the effective peak is extracted in real time and recorded as an offset feature value. If the offset feature value is within the preset effective coupling threshold range, the effective peak is determined to have shifted. In this way, the frequency range and step size used during rescanning are consistent with the first scan, eliminating peak position monitoring errors caused by differences in scan parameters and ensuring the consistency of the peak shift determination benchmark. Simultaneously, by using a preset effective coupling threshold and quantifying the peak shift validity with the offset feature value, rather than simply making a qualitative judgment on the presence or absence of peak shift, misjudgments caused by minor pseudo-offsets due to environmental noise and equipment jitter are avoided, significantly improving the accuracy and anti-interference capability of determining the binding relationship between the qubit and the read cavity. This design adds a quantitative verification dimension to the peak shift determination, making the results of binding relationship verification and read frequency calibration more objective and reliable, further enhancing the robustness and applicability of the entire method.

[0039] Furthermore, the above-mentioned method of generating a candidate list of readout frequencies for each qubit and placing the initial readout frequency of each qubit before the first position in the candidate list of readout frequencies for each qubit may further include: sorting the actual readout frequencies in the candidate list in descending order to obtain sorted frequencies; sorting the qubits on the readout line according to the same rules as the designed intrinsic frequencies to obtain sorted qubits; and matching the sorted frequencies with the sorted qubits one by one to obtain the initial readout frequency assigned to each qubit.

[0040] In this embodiment, the initial readout frequency for each qubit is determined by the magnitude of its designed frequency and a sorted frequency list. For example, [f1, f2, ..., fn] is mapped to [q1, q2, ..., qn], where f represents the frequency and q represents the qubit. The readout cavity and qubit are physically bound one-to-one. This frequency-based sorting method quickly assigns a unique initial readout frequency to each qubit, ensuring uniqueness and avoiding confusion. Furthermore, during the chip design phase, the order of the qubit's designed frequency is matched to the order of the bound readout cavity's designed frequency. Therefore, this sorted allocation matches the chip's physical design, preventing allocation errors.

[0041] Applying the read frequency calibration method provided in this embodiment of the invention, S101: the read cavities on the read line are frequency scanned to obtain scan data; the scan data is a two-dimensional dataset of frequency and amplitude; S102: adaptive peak finding processing is performed based on the scan data, and the number of frequencies obtained by peak finding is consistent with the number of read cavities by parameter adjustment, generating a read frequency candidate list; the read frequency candidate list contains the actual read frequency corresponding to each peak; S103: a read frequency to be verified is assigned to each qubit based on the read frequency candidate list, and frequency scanning is performed by changing the signal bias of the qubit to determine the read cavity bound to each qubit and the final corresponding read frequency. This method accurately obtains the actual readout frequency of each readout cavity through frequency scanning and adaptive peak finding and frequency matching, providing a precise basis for readout frequency calibration that closely matches the actual chip, thus solving the problem of lacking a precise calibration benchmark for readout frequency. After allocating readout frequencies to be verified based on the candidate list, the actual binding relationship between the qubit and the bound readout cavity can be accurately determined by changing the signal bias rescan and based on the peak shift state, solving the problem of easy mapping errors in the preset binding relationship. The precise calibration of the readout frequency achieves a precise match between the readout frequency and the actual readout frequency of the qubit-bound readout cavity, ensuring that the microwave signal corresponding to the readout frequency can accurately capture the cavity response signal modulated by the qubit state. From the two core dimensions of frequency parameter matching and physical binding correspondence, the key obstacles affecting qubit state reading are eliminated, ultimately effectively ensuring the effectiveness and accuracy of qubit state reading.

[0042] The reading frequency calibration device provided in the embodiments of the present invention will be described below. The reading frequency calibration device described below can be referred to in correspondence with the reading frequency calibration method described above.

[0043] Please refer to the details. Figure 2 , Figure 2 A schematic diagram of a reading frequency calibration device provided in an embodiment of the present invention may include: The frequency scanning module 100 is used to perform frequency scanning on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude. The adaptive peak finding module 200 is used to perform adaptive peak finding processing based on the scan data, and adjust the parameters to make the number of frequencies obtained by peak finding consistent with the number of reading cavities, thereby generating a reading frequency candidate list; the reading frequency candidate list contains the actual reading frequency corresponding to each peak. The mapping update module 300 is used to assign a read frequency to be verified to each qubit based on the read frequency candidate list, and to perform frequency scanning by changing the signal bias of the qubit to determine the read cavity bound to each qubit and the final corresponding read frequency.

[0044] Furthermore, based on the above embodiments, the adaptive peak finding module 200 may include: An identification unit is used to calculate an adaptive peak height threshold and identify valid peaks from the scan data; The adjustment unit is used to dynamically adjust the noise level parameter in the peak height threshold so that the number of actual reading frequencies corresponding to the effective peaks is consistent with the number of reading cavities; The extraction unit is used to extract the actual reading frequencies corresponding to all the valid peaks and generate the candidate list of reading frequencies.

[0045] Furthermore, based on the above embodiments, the identification unit may specifically include: The normalization subunit is used to calculate the amplitude difference between the largest and smallest amplitude values ​​in the scanned data, and to divide all amplitude values ​​in the scanned data by the amplitude difference to obtain the normalized amplitude value. The preprocessing subunit is used to invert the normalized amplitude to obtain preprocessed scan data; the preprocessed scan data is a two-dimensional dataset of frequency and inverted normalized amplitude. The calculation subunit is used to calculate the peak height threshold based on the average value of the inverted normalized amplitude, the noise level parameter, and the standard deviation of the inverted normalized amplitude; The effective peak identification subunit is used to identify the peaks in the preprocessed scan data whose inverted normalized amplitude exceeds the peak height threshold as the effective peaks.

[0046] Furthermore, based on the above embodiments, the adjustment unit may include: An initial calculation subunit is used to calculate the peak height threshold based on a preset initial noise level, combined with the average value and the standard deviation. The threshold comparison subunit is used to perform threshold comparison on the amplitude values ​​after inversion and normalization in the preprocessed scan data based on the peak height threshold, and to identify the effective peak. The first threshold adjustment subunit is used to count the number of actual read frequencies corresponding to the effective peak. If the number of actual read frequencies is less than the number of read cavities, the noise level is reduced by a preset step size, and the peak height threshold is recalculated. The second threshold adjustment subunit is used to increase the noise level by a preset step size and recalculate the peak height threshold if the number of actual reading frequencies is greater than the number of reading cavities. An iterative update subunit is used to iteratively update the peak height threshold and re-identify valid peaks until the number of actual frequencies corresponding to the valid peaks is consistent with the number of read cavities.

[0047] Furthermore, based on any of the above embodiments, the mapping update module 300 may include: An adjustment unit is configured to generate a candidate list of read frequencies for each of the qubits and place the initial read frequency of each qubit at the beginning of the candidate list of read frequencies corresponding to each qubit. The traversal unit is used to sequentially traverse the actual reading frequencies in the candidate reading frequency list and set them as the reading frequencies to be verified. A frequency rescanning unit is used to perform frequency rescanning on the read cavity on the read line for each of the read frequencies to be verified by changing the signal bias of the corresponding qubit, and to detect the shift state of the effective peak. The determining unit is used to determine the matching relationship between the current read frequency to be verified and the read cavity based on the movement state of the effective peak, and to lock the read cavity bound to each of the qubits and the read frequency corresponding to the read cavity.

[0048] Furthermore, based on any of the above embodiments, the frequency calibration device may further include: The first sorting module is used to generate the read frequency candidate list for each of the qubits, place the initial read frequency of each qubit before the first position of the read frequency candidate list corresponding to each qubit, sort the actual read frequencies in the read frequency candidate list in descending order, and obtain the sorted frequencies. The second sorting module is used to sort the qubits on the read line according to the design intrinsic frequency and the same rules to obtain sorted qubits. The initial read frequency determination module is used to match the sorted frequencies with the sorted qubits one by one to obtain the initial read frequency assigned to each qubit.

[0049] Furthermore, based on the above embodiments, the determining unit may include: The first determining subunit is used to determine, if the effective peak shifts, that the reading cavity corresponding to the current reading frequency to be verified is the reading cavity bound to the current qubit, determine the current reading frequency to be verified as the reading frequency corresponding to the bound reading cavity, and remove the reading frequency to be verified from the reading frequency candidate list of all other qubits. The second determining subunit is used to remove the read frequency to be verified from the candidate list of read frequencies of the current qubit if the effective peak has not shifted, and continue to traverse the next candidate frequency until the binding read cavity and the corresponding read frequency are locked for the current qubit.

[0050] It should be noted that the order of the modules and units in the above-mentioned frequency calibration device can be changed without affecting the logic.

[0051] The reading frequency calibration device provided in this embodiment of the invention includes a frequency scanning module 100, which performs frequency scanning on the reading cavities on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude; an adaptive peak finding module 200, which performs adaptive peak finding processing based on the scanning data, and adjusts parameters to make the number of frequencies obtained by peak finding consistent with the number of reading cavities, generating a reading frequency candidate list; the reading frequency candidate list contains the actual reading frequency corresponding to each peak; and a mapping update module 300, which assigns a reading frequency to be verified to each qubit based on the reading frequency candidate list, performs frequency scanning by changing the signal bias of the qubit, determines the reading cavity bound to each qubit, and the final corresponding reading frequency. This device accurately acquires the actual readout frequency of each readout cavity through frequency scanning and adaptive peak finding and frequency matching, providing a precise basis for readout frequency calibration that closely matches the actual chip, thus solving the problem of lacking a precise calibration benchmark for readout frequency. After allocating readout frequencies to be verified based on the candidate list, it utilizes the weak coupling characteristics between the qubit and the bound readout cavity, and by changing the signal bias rescanning and based on the peak shift state, it can accurately determine and confirm the actual binding relationship between the qubit and the readout cavity, solving the problem of easy mapping errors in the preset binding relationship. The precise calibration of the readout frequency achieves a precise match between the readout frequency and the actual readout frequency of the qubit-bound readout cavity, ensuring that the microwave signal corresponding to the readout frequency can accurately capture the cavity response signal modulated by the qubit state. From the two core dimensions of frequency parameter matching and physical binding correspondence, the device eliminates the key obstacles affecting qubit state reading, ultimately effectively ensuring the effectiveness and accuracy of qubit state reading.

[0052] Figure 3 This is a schematic diagram of the structure of a frequency calibration device provided in an embodiment of the present invention, as shown below. Figure 3 As shown, the frequency calibration device includes: Memory 60 is used to store computer programs; The processor 61 is used to execute a computer program to implement the steps of the frequency calibration reading method as described in the above embodiment.

[0053] The frequency calibration device provided in this embodiment may include, but is not limited to, smartphones, tablets, laptops, or desktop computers.

[0054] The processor 61 may include one or more processing cores, such as a quad-core processor or an octa-core processor. The processor 61 may be implemented using at least one hardware form selected from Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), and Programmable Logic Array (PLA). The processor 61 may also include a main processor and a coprocessor. The main processor, also known as the Central Processing Unit (CPU), is used to process data in the wake-up state; the coprocessor is a low-power processor used to process data in the standby state. In some embodiments, the processor 61 may integrate a Graphics Processing Unit (GPU), which is responsible for rendering and drawing the content to be displayed on the screen. In some embodiments, the processor 61 may also include an Artificial Intelligence (AI) processor, which handles computational operations related to machine learning.

[0055] The memory 60 may include one or more computer-readable storage media, which may be non-transitory. The memory 60 may also include high-speed random access memory and non-volatile memory, such as one or more disk storage devices or flash memory devices. In this embodiment, the memory 60 is used to store at least the following computer program 601, which, after being loaded and executed by the processor 61, is capable of implementing the relevant steps of the frequency calibration method disclosed in any of the foregoing embodiments. In addition, the resources stored in the memory 60 may also include an operating system 602 and data 603, etc., and the storage method may be temporary storage or permanent storage. The operating system 602 may include Windows, Unix, Linux, etc. The data 603 may include, but is not limited to, data related to the frequency calibration method.

[0056] In some embodiments, the frequency calibration device may further include a display screen 62, an input / output interface 63, a communication interface 64, a power supply 65, and a communication bus 66.

[0057] Those skilled in the art will understand that Figure 3 The structure shown does not constitute a limitation on the reading frequency calibration device and may include more or fewer components than shown.

[0058] It is understood that if the reading frequency calibration method in the above embodiments is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the current technology, 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 storage medium and executes all or part of the steps of the methods in the various embodiments of the present invention. The aforementioned storage medium includes: USB flash drive, mobile hard drive, read-only memory (ROM), random access memory (RAM), electrically erasable programmable ROM, register, hard disk, removable disk, CD-ROM, magnetic disk or optical disk, and other media capable of storing program code.

[0059] Based on this, embodiments of the present invention also provide a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the steps of the above-described frequency calibration method.

[0060] The following describes a computer program product provided by an embodiment of this application. The computer program product described below can be referred to in conjunction with other embodiments described herein.

[0061] A computer program product includes a computer program / instructions that, when executed by a processor, implement the steps of the aforementioned disclosed read frequency calibration method.

[0062] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on its differences from other embodiments. Similar or identical parts between embodiments can be referred to interchangeably. For the apparatus disclosed in the embodiments, since it corresponds to the method disclosed in the embodiments, the description is relatively simple; relevant parts can be referred to in the method section.

[0063] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

[0064] Finally, it should be noted that in this document, relationships such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus.

[0065] The above provides a detailed description of a reading frequency calibration method, apparatus, device, and computer-readable storage medium provided by the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for calibrating reading frequency, characterized in that, include: Frequency scanning is performed on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude. Based on the scan data, adaptive peak finding processing is performed, and the number of frequencies obtained by peak finding is consistent with the number of reading cavities by parameter adjustment, thereby generating a reading frequency candidate list; the reading frequency candidate list contains the actual reading frequency corresponding to each peak. Based on the candidate list of readout frequencies, a readout frequency to be verified is assigned to each qubit. By changing the signal bias of the qubit, a frequency scan is performed to determine the readout cavity bound to each qubit and the final corresponding readout frequency.

2. The reading frequency calibration method according to claim 1, characterized in that, Based on the scan data, adaptive peak finding processing is performed, and the number of frequencies obtained by peak finding is consistent with the number of readout cavities through parameter adjustment, generating a candidate list of readout frequencies, including: Calculate the adaptive peak height threshold and identify valid peaks from the scan data; By dynamically adjusting the noise level parameter in the peak height threshold, the number of actual read frequencies corresponding to the effective peaks is made consistent with the number of read cavities; Extract the actual reading frequencies corresponding to all the valid peaks to generate the candidate list of reading frequencies.

3. The reading frequency calibration method according to claim 2, characterized in that, Calculating the adaptive peak height threshold and identifying valid peaks from the scan data includes: Calculate the amplitude difference between the largest and smallest amplitude values ​​in the scanned data, and divide all amplitude values ​​in the scanned data by the amplitude difference to obtain the normalized amplitude value; The normalized amplitude is inverted to obtain the preprocessed scan data; the preprocessed scan data is a two-dimensional dataset of frequency and inverted normalized amplitude. The peak height threshold is calculated based on the average value of the inverted normalized amplitude, the noise level parameter, and the standard deviation of the inverted normalized amplitude. Peaks in the preprocessed scan data whose inverted normalized amplitude exceeds the peak height threshold are identified as valid peaks.

4. The reading frequency calibration method according to claim 3, characterized in that, By dynamically adjusting the noise level parameter in the peak height threshold, the number of actual read frequencies corresponding to the effective peaks is made consistent with the number of read cavities, including: The peak height threshold is calculated by combining the preset initial noise level with the average value and the standard deviation. Based on the peak height threshold, the amplitude values ​​after inversion and normalization in the preprocessed scan data are compared with the threshold to identify the effective peaks. The number of actual read frequencies corresponding to the effective peaks is counted. If the number of actual read frequencies is less than the number of read cavities, the noise level is reduced by a preset step size, and the peak height threshold is recalculated. If the number of actual reading frequencies is greater than the number of reading cavities, the noise level is increased by a preset step size, and the peak height threshold is recalculated. The peak height threshold is iteratively updated and valid peaks are re-identified until the number of actual frequencies corresponding to the valid peaks is consistent with the number of read cavities.

5. The reading frequency calibration method according to any one of claims 1 to 4, characterized in that, Based on the candidate readout frequency list, a readout frequency to be verified is assigned to each qubit. Frequency scanning is performed by changing the signal bias of the qubit to determine the readout cavity bound to each qubit and the final corresponding readout frequency, including: A readout frequency candidate list is generated for each of the qubits, and the initial readout frequency of each qubit is placed at the beginning of the readout frequency candidate list corresponding to each qubit. The actual read frequencies in the candidate read frequency list are sequentially traversed and set as the read frequencies to be verified. For each read frequency to be verified, the frequency rescan is performed on the read cavity on the read line by changing the signal bias of the corresponding qubit to detect the shift state of the effective peak; Based on the movement state of the effective peak, determine the matching relationship between the current read frequency to be verified and the read cavity, and lock the read cavity bound to each of the qubits one by one, as well as the read frequency corresponding to the read cavity.

6. The reading frequency calibration method according to claim 5, characterized in that, Before generating the readout frequency candidate list for each of the qubits and placing the initial readout frequency of each qubit at the beginning of the readout frequency candidate list corresponding to each qubit, the method further includes: Sort the actual read frequencies in the candidate read frequency list in descending order to obtain the sorted frequencies; The qubits on the read line are sorted according to the design intrinsic frequencies and rules to obtain the sorted qubits; The sorted frequencies are matched one-to-one with the sorted qubits to obtain the initial readout frequency assigned to each qubit.

7. The reading frequency calibration method according to claim 6, characterized in that, Based on the shift state of the effective peak, the matching relationship between the current read frequency to be verified and the read cavity is determined, and the read cavity bound to each quantum bit is locked one by one, as well as the read frequency corresponding to the read cavity, including: If the effective peak shifts, the reading cavity corresponding to the current reading frequency to be verified is determined to be the reading cavity bound to the current qubit, the current reading frequency to be verified is determined to be the reading frequency corresponding to the bound reading cavity, and the reading frequency to be verified is removed from the reading frequency candidate list of all other qubits. If the effective peak does not shift, the read frequency to be verified is removed from the candidate list of read frequencies for the current qubit and the process continues to traverse the next candidate frequency until a binding read cavity and corresponding read frequency are locked for the current qubit.

8. A frequency calibration device, characterized in that, include: The frequency scanning module is used to perform frequency scanning on the reading cavity on the reading line to obtain scanning data; the scanning data is a two-dimensional dataset of frequency and amplitude. An adaptive peak finding module is used to perform adaptive peak finding processing based on the scan data, and adjust parameters to make the number of frequencies obtained by peak finding consistent with the number of read chambers, thereby generating a candidate list of read frequencies; the candidate list of read frequencies contains the actual read frequencies corresponding to each peak. The mapping update module is used to assign a read frequency to be verified to each qubit based on the read frequency candidate list, and to perform frequency scanning by changing the signal bias of the qubit to determine the read cavity bound to each qubit and the final corresponding read frequency.

9. A frequency calibration reading device, characterized in that, include: Memory, used to store computer programs; A processor, configured to implement the read frequency calibration method as described in any one of claims 1 to 7 when executing the computer program.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when loaded and executed by a processor, implement the read frequency calibration method as described in any one of claims 1 to 7.

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