Multi-quantum bit reading result correction method and device and medium

Abstract

The invention discloses a multi-quantum-bit reading result correction method and device and a medium, relates to the technical field of quantum computing, and is used for optimizing a multi-bit reading result in a quantum computer. Aiming at the problem of poor effect of a traditional optimization scheme, the invention provides a multi-quantum-bit reading result correction method, and the method comprises the steps: carrying out the iterative optimization of an ideal probability distribution vector pideal through setting a constraint condition that the deviation between a noise-containing distribution vector corrected by a reading error response matrix and an ideal distribution vector is the lowest; therefore, the ideal probability distribution vector pideal obtained subsequently is closer to the real situation of a multi-quantum bit reading result in a quantum computer. Furthermore, when the ideal probability distribution vector pideal obtained by the method is used for correcting the multi-bit reading result in the quantum computer, the fidelity of the corrected reading result can be further improved, and the requirement on the accuracy of quantum calculation in a more harsh scene can be met.

Description

Technical Field

[0001] The present invention relates to the field of quantum computing, and in particular to a method, device and medium for correcting multi-qubit reading results. Background Art

[0002] In quantum computing applications, due to the presence of read noise, there is a certain probability that the wrong state will be read when reading the state of the quantum bit. Moreover, the read error rate increases exponentially with the increase in the number of quantum bits. For example, assuming that the probability of correctly reading a single quantum bit is 95%, when reading the binary string corresponding to 20 quantum bits, the probability of correctly reading is only 0.95. 20 =35.85%, which will obviously have a serious adverse impact on the fidelity of quantum computing results and needs to be optimized.

[0003] Currently, the most widely used read error mitigation strategy is to calibrate the read error response matrix R and obtain the read probability distribution vector p containing noise. noise After that, R -1 p noise To obtain the ideal probability distribution vector p ideal .

[0004] While the above solution can correct quantum reading results and improve the fidelity of the reading results, it also has some shortcomings. For example, in some scenarios where higher fidelity of the reading results is required, the above solution still cannot meet the needs.

[0005] Therefore, technicians in this field are in urgent need of a multi-qubit reading result correction method to further improve the fidelity of the corrected reading results based on the original solution of correcting the reading results by reading the error response matrix. Summary of the Invention

[0006] The purpose of the present invention is to provide a method, device and medium for correcting multi-qubit reading results, so as to further improve the fidelity of the corrected multi-qubit reading results to meet the quantum computing accuracy requirements in more demanding scenarios.

[0007] To solve the above technical problems, the present invention provides a multi-qubit reading result correction method, comprising: Obtaining a noisy multi-bit read result in a quantum computer, and determining a noisy distribution vector and a read error response matrix corresponding to the multi-bit read result; Initialize the ideal distribution vector to a vector with the same length as the noisy distribution vector but with values of 0; Iterating the ideal distribution vector with the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, and obtaining the iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector; The ideal distribution vector is used to correct the noisy multi-bit reading result in the quantum computer.

[0008] In an optional embodiment, taking the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint, iterating the ideal distribution vector, and obtaining the iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector includes: Iteratively determining the minimum value of the objective function using a gradient or non-gradient iterative method under a preset cutoff condition, and determining the value of the ideal distribution vector when the objective function takes the minimum value as the final ideal distribution vector; Wherein, the objective function is: ; R represents the read error response matrix; represents the ideal distribution vector; represents the noisy distribution vector; represents the Euclidean norm.

[0009] In an optional embodiment, the preset cutoff condition includes: The result values of the objective function in two consecutive iterations are both less than the first threshold, or the number of iterations reaches the second threshold.

[0010] In an optional embodiment, when iterating the ideal distribution vector, the method further includes: The ideal distribution vector is limited to have a minimum value of 0 and a maximum value of 1.

[0011] In an optional embodiment, determining a read error response matrix corresponding to the multi-bit read result includes: Obtaining a single-bit read fidelity of a corresponding quantum bit in the multi-bit read result, and determining a matrix element in the error response matrix using an error response matrix element calculation formula to obtain the error response matrix; The error response matrix element calculation formula is: ; Both row and col are binary strings, row is the row index of the matrix, indicating the reading result of the multi-qubit, and col is the column index of the matrix, indicating the real state of the multi-qubit; R row,colrepresents the matrix element at row th row and column col th in the error response matrix; k represents the number of quantum bits contained in the multi-bit read result; Represents the read fidelity of row th row and column col th column in the single-bit read fidelity matrix of the i-th quantum bit.

[0012] In an optional embodiment, when calculating the matrix elements in the error response matrix, the method further includes: If the Hamming distance of the matrix element is greater than a third threshold, setting the matrix element to 0; The Hamming distance is the number of quantum bits of different positions contained in the row index and column index of the matrix element.

[0013] In an optional embodiment, obtaining a single-bit read fidelity of a corresponding quantum bit in the multi-bit read result includes: From the pre-established index dictionary, the corresponding single-bit read fidelity is called by the index of the corresponding quantum bit; The index dictionary stores various single-bit reading fidelities corresponding to any quantum bit in the quantum computer.

[0014] In an optional embodiment, the establishment of the index dictionary includes: Encode all qubits contained in the quantum computer to obtain the index corresponding to each qubit in the quantum computer, and add the corresponding index item to the pre-established dictionary according to the index of each qubit; Obtaining a single-bit read fidelity matrix for each of the quantum bits; Saving the first single-bit read fidelity and the second single-bit read fidelity in the single-bit read fidelity matrix under corresponding index items in the dictionary; Among them, the first single-bit read fidelity is the read fidelity when the current quantum bit’s true state is the |0> state and the |0> state is read; the second single-bit read fidelity is the read fidelity when the current quantum bit’s true state is the |1> state and the |1> state is read.

[0015] In an optional embodiment, obtaining the single-bit read fidelity matrix includes: Prepare the current quantum bit into the |0> state and repeatedly read it multiple times; Determining a first single-bit read fidelity based on the number of times the |0> state is read in the repeated read results; and determining a third single-bit read fidelity based on the difference between 1 and the first single-bit read fidelity; wherein the third single-bit read fidelity is the read fidelity when the actual state of the current qubit is the |0> state but the |1> state is read; Prepare the current quantum bit into the |1> state and repeatedly read it multiple times; The second single-bit read fidelity is determined based on the number of times the |1> state is read in the repeated reading results; and the fourth single-bit read fidelity is determined based on the difference between 1 and the second single-bit read fidelity; wherein the fourth single-bit read fidelity is the reading fidelity when the true state of the current quantum bit is the |1> state but the |0> state is read.

[0016] In an optional embodiment, determining the noise distribution vector corresponding to the multi-bit read result includes: Repeating multiple readings of the quantum circuit corresponding to the multi-bit reading result in the quantum computer, and obtaining a binary result string obtained each time; Counting the number of occurrences of different binary result strings in each binary result string to determine the occurrence probability of each binary result string; The noise distribution vector is determined according to the occurrence probabilities of various binary result strings.

[0017] In an optional embodiment, after repeatedly reading the quantum circuit corresponding to the multi-bit reading result in the quantum computer for multiple times and obtaining the binary result string read each time, the method further includes: Completing the binary result string according to the theoretical reading result of the multi-bit reading result; wherein the number of occurrences of the completed binary result string is 0; Sort all binary result strings.

[0018] In order to solve the above technical problems, the present invention also provides a multi-qubit reading result correction device, comprising: an acquisition module, configured to acquire a noisy multi-bit read result in a quantum computer and determine a noisy distribution vector and a read error response matrix corresponding to the multi-bit read result; an initialization module, configured to initialize the ideal distribution vector to a vector having the same length as the noise distribution vector but with values of 0; an iterative module, configured to iterate the ideal distribution vector with a minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, and obtain an iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector; A correction module is used to correct the noisy multi-bit reading result in the quantum computer by using the ideal distribution vector.

[0019] In order to solve the above technical problems, 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 multi-qubit reading result correction method as described above.

[0020] In order to solve the above technical problems, the present invention also provides a multi-qubit reading result correction device, comprising: Memory for storing computer programs; A processor is used to implement the steps of the multi-qubit reading result correction method as described above when executing the computer program.

[0021] In order to solve the above technical problems, the present invention also provides a non-volatile storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the multi-qubit reading result correction method as described above are implemented.

[0022] The present invention provides a multi-qubit reading result correction method, which obtains the noise distribution vector p noise After reading the error response matrix R, it is no longer necessary to directly calculate R -1 p noise To obtain the ideal probability distribution vector p ideal Instead, the ideal probability distribution vector p is constrained by setting the constraint condition that “the deviation between the noise distribution vector corrected by the read error response matrix and the ideal distribution vector is the lowest”. ideal Iterate so that the ideal probability distribution vector p obtained later is ideal It is closer to the actual situation of multi-qubit reading results in quantum computers. Furthermore, in the ideal probability distribution vector p obtained by this method, ideal When correcting multi-bit read results in a quantum computer, the fidelity of the corrected read results can be further improved, meeting the requirements for quantum computing accuracy in more demanding scenarios.

[0023] The multi-qubit reading result correction device and non-volatile storage medium provided by the present invention correspond to the above method and have the same effect as above. BRIEF DESCRIPTION OF THE DRAWINGS

[0024] In order to more clearly illustrate the embodiments of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0025] Figure 1 A flowchart of a multi-qubit reading result correction method provided by an embodiment of the present invention; Figure 2 A schematic diagram of the frequency distribution of a noisy sampling result provided by an embodiment of the present invention; Figure 3 An iterative schematic diagram of minimizing an objective function provided by an embodiment of the present invention; Figure 4 A schematic diagram of an optimized frequency distribution provided by an embodiment of the present invention; Figure 5 A single-bit |0> state read fidelity measurement circuit diagram provided by an embodiment of the present invention; Figure 6 A single-bit |1> state read fidelity measurement circuit diagram provided by an embodiment of the present invention; Figure 7 A structural diagram of a multi-qubit reading result correction device provided by an embodiment of the present invention; Figure 8 A structural diagram of another multi-qubit reading result correction device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0026] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0027] The core of the present invention is to provide a method, device and medium for correcting multi-qubit reading results.

[0028] In order to enable those skilled in the art to better understand the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific implementation methods.

[0029] Quantum computing development is still in the research phase, and mitigating read noise remains a major challenge for quantum computers. Read noise refers to the probability that, for any single qubit in the |0> state (|1> state), it will incorrectly read the |1> state (|0> state) during actual sampling. For multiple qubits, the probability of correctly reading a multi-bit binary string can be simply considered the product of the probabilities of correctly reading each qubit. In other words, if the read fidelity of a single qubit is similar, the read fidelity of multiple qubits decreases exponentially with the number of qubits.

[0030] For example, assuming that the probability of a single quantum bit correctly reading |0> or correctly reading |1> is 95%, and the result of a calculation in a quantum computer is a binary string |11101000010001000010> composed of 20 quantum bits, then the probability of correctly reading the binary string state is only 0.95. 20 =35.85%. It's easy to see that increasing the number of qubits significantly impacts the fidelity of quantum computing results. Therefore, optimization of multi-bit readouts is necessary.

[0031] Currently, the most widely used read error optimization strategy is to optimize the multi-bit read results through the read error response matrix R. Specifically, first calibrate the read error response matrix R; then obtain the read probability distribution p containing noise. noise Then we can calculate R -1 p noise To obtain the true probability distribution p ideal ; Finally, through the true probability distribution p ideal Implement correction and optimization of multi-bit reading results.

[0032] For example, for two qubits q0q1, the read error response matrix is obtained by preparing the two qubits q0q1 to the |00> state and obtaining the probabilities of the read results being |00>, |01>, |10>, and |11>, respectively. Subsequently, similarly, the two qubits q0q1 are prepared to the |01>, |10>, and |11> states, respectively, and obtaining the probabilities of the read results being |00>, |01>, |10>, and |11>, respectively, in each prepared state. Finally, the read error response matrix R can be constructed as: ; In the above formula, It represents the probability that the quantum bit is in state j but the reading result is state i. In addition, it can be clearly seen from the above formula that there is a normalized relationship: ; And the actual reading result can be calculated by the following formula: (1); However, the above solution also has many problems. The first one is the true probability distribution p obtained by the above formula ideal It is only a calculated value, not a real value. If the determined read error response matrix R and the sampled read probability distribution p containing noise are noise If there is a deviation from its true value, the calculated p idealIt is not a true formal probability distribution. Therefore, its optimization effect on multi-bit readout results needs to be further improved, and it cannot meet the fidelity requirements of multi-bit readout results in more and more demanding quantum computing scenarios.

[0033] In order to solve the above problems, the present invention provides a multi-qubit reading result correction method, such as Figure 1 As shown, the method includes: S11: Obtain a noisy multi-bit read result in the quantum computer, and determine a noisy distribution vector and a read error response matrix corresponding to the multi-bit read result.

[0034] S12: Initialize the ideal distribution vector to a vector with the same length as the noisy distribution vector but with values of 0.

[0035] S13: Taking the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, iterate the ideal distribution vector, and obtain the ideal distribution vector iteration result with the minimum deviation as the final ideal distribution vector.

[0036] S14: Correcting noisy multi-bit readouts in quantum computers using ideal distribution vectors.

[0037] For steps S11 and S14, the noise distribution vector is also the noise reading probability distribution p in the related art. noise , but exists in the form of a vector to facilitate subsequent calculations. This embodiment does not limit the acquisition of the noise distribution vector p noise By reading the error response matrix R, the noise distribution vector p can be obtained in the same way as in the related art. noise And read the error response matrix R. Similarly, after determining the ideal distribution vector (ie, the true probability distribution) p ideal After that, how to correct the multi-bit reading results in the quantum computer can also be achieved by using the same method in the related art, and this embodiment does not limit this. The focus of this method is how to optimize the real probability distribution to obtain an ideal distribution vector p that is more consistent with the real situation of multi-bit reading. ideal .

[0038] As for steps S12 and S13, it can be seen from the above description of the related art that in the related art, by calculating R -1 p noise To obtain the true probability distribution p ideal . The true probability distribution p ideal That is, the parameter used to correct the multi-bit reading result is also the ideal distribution vector in step S12. However, unlike the related art, the ideal distribution vector p in this method is idealNot directly by calculating R -1 p noise Instead, we get the ideal distribution vector p ideal , noise distribution vector p noise Specifically, in this method, the noise distribution vector (i.e., R) corrected by the read error response matrix is used. -1 p noise ) and the ideal distribution vector p ideal The minimum deviation between them is the constraint condition to achieve iteration of the ideal distribution vector. The noisy distribution vector corrected by the read error response matrix represents the new probability distribution of the noisy read probability distribution after the read error response matrix R is corrected. The closer it is to the actual true probability distribution p ideal That is, the better the correction effect, the better the effect of improving the reading fidelity. Therefore, this method continuously approaches the true probability distribution p through iteration. ideal , in order to obtain better optimization effect of multi-bit reading results. That is, to determine the corresponding ideal distribution vector p when the deviation is minimum ideal As the true probability distribution of the multi-bit reading result of the quantum computer finally used to correct it in step S4.

[0039] In an optional implementation, this embodiment provides a method for quantizing the noise distribution vector corrected by the read error response matrix and the ideal distribution vector p ideal The size of the deviation between them, and the ideal distribution vector p ideal The specific scheme for iterative optimization is as follows. That is, the above-mentioned step S13 specifically includes: The minimum value of the objective function is iteratively determined using a gradient or non-gradient iterative method under a preset cutoff condition, and the value of the ideal distribution vector when the objective function takes the minimum value is determined as the final ideal distribution vector.

[0040] Among them, the objective function is: (2); R represents the read error response matrix; represents the ideal distribution vector; represents a noisy distribution vector; represents the Euclidean norm.

[0041] In this method, the vector is calculated by the Euclidean norm (L2 norm) The modulus of is the square root of the sum of the squares of the components. It is not difficult to see from formula (1) that It is a variant of formula (1) and is used to measure the ideal distribution vector p after the error response matrix R transformation. idealThe Euclidean distance between the original noise and the noise distribution vector (R -1 p noise ) and the ideal distribution vector p ideal Furthermore, the constraint condition in step S3 is to perform gradient or non-gradient iterative optimization with the minimum result value of the objective function as the goal, so as to obtain an ideal distribution vector p that is closer to the true value. ideal .

[0042] Furthermore, this embodiment does not limit the preset cutoff condition in the above-mentioned iterative process. In a general embodiment, a maximum number of iterations can be set, and the iteration is stopped when the number of iterations reaches this maximum value to avoid problems such as entering an infinite loop, overfitting, or local optimum.

[0043] However, this embodiment also provides another optional implementation scheme of the preset cutoff condition, and the above-mentioned preset cutoff condition specifically includes: The result value of the objective function in two consecutive iterations is less than the first threshold, or the number of iterations reaches the second threshold.

[0044] The present embodiment is not limited to a specific value of the first threshold, but the first threshold should be a relatively small value. That is, when the result value of the objective function is less than the first threshold, it can be considered to be close to 0, that is, the ideal distribution vector p after iteration ideal Close to the true probability distribution. In addition, this embodiment also requires that the iteration is stopped only when the result value of the objective function in two consecutive iterations is less than the first threshold. The purpose is to prevent the occurrence of problems such as local optimality. In addition, in addition to the sub-condition that the result value of the objective function in two consecutive iterations is less than the first threshold, the preset cutoff condition provided by this embodiment also includes another sub-condition that the number of iterations reaches the second threshold. The iteration is stopped when either of the two sub-conditions is met. The second sub-condition also sets the maximum number of iterations to avoid problems such as entering an infinite loop or overfitting.

[0045] Furthermore, the multi-bit reading result correction scheme proposed in the related art has another problem, that is, since the number of sampling times in actual applications is not infinite, the sampling results obtained by sampling are different from the actual noisy reading probability distribution p noise There is also a certain deviation between them. This deviation may cause the probabilities corresponding to certain quantum states to be negative when subsequently calculating the true probability distribution, which is obviously not in line with the actual situation.

[0046] Therefore, based on this principle, this embodiment also aims at the ideal distribution vector p ideal The acquisition of the ideal distribution vector p provides a further embodiment. The above step S13 idealWhen performing iterative optimization, it also includes: The ideal distribution vector is restricted to have a minimum value of 0 and a maximum value of 1.

[0047] From the above, we can see that the ideal distribution vector p ideal The value of should not be negative. If it exists, it may be due to the difference between the sampling result and the actual reading probability distribution p containing noise. noise This is caused by the deviation between the two, which will inevitably affect the subsequent optimization effect of the multi-bit reading results. ideal When performing iterative optimization, the value is directly limited to [0,1] to avoid negative numbers, which can reduce the difference between the sampling result and the actual noisy reading probability distribution p to a certain extent. noise The deviation between them has an adverse effect on the optimization effect of multi-bit reading results.

[0048] To further illustrate the improvement of the fidelity of multi-bit reading results by this method, this embodiment also provides a possible test example: Assume that the multi-bit reading result is a quantum bit string composed of 10 quantum bits, and the distribution of the noisy sampling results obtained by repeated reading 10,000 times is as follows Figure 2 As shown; Based on this method, iterative optimization of the ideal distribution vector p ideal The process is as follows Figure 3 As shown; based on the ideal distribution vector p obtained after iterative optimization ideal After optimizing the multi-bit reading results, Figure 4 As shown. Figures 2 to 4 It is not difficult to see that Figure 4 After optimization, the number of times the true state of the quantum bit string has been read has reached nearly 10,000 times, which has significantly improved the assurance of multi-bit reading results.

[0049] In summary, the present invention provides a multi-qubit reading result correction method, which sets the constraint condition of "the deviation between the noise distribution vector corrected by the read error response matrix and the ideal distribution vector is the lowest" to correct the ideal probability distribution vector p. ideal Perform iterative optimization so that the ideal probability distribution vector p obtained later is ideal It is closer to the actual situation of multi-qubit reading results in quantum computers. Furthermore, in the ideal probability distribution vector p obtained by this method, ideal When correcting multi-bit read results in a quantum computer, the fidelity of the corrected read results can be further improved, meeting the requirements for quantum computing accuracy in more demanding scenarios.

[0050] On the other hand, as can be seen from the above embodiments, this method does not place excessive restrictions on the method for obtaining the read error response matrix R, and methods known in related arts can be used. Specifically, the target qubit string is prepared in each possible state, and multiple readings are performed repeatedly in each possible preparation state. The number of times each different read result is obtained is counted to determine the corresponding read probability.

[0051] However, this solution also reflects another problem with related technologies: as the number of quantum bits k increases, the number of possible quantum states increases exponentially (i.e., 2 k ). At this time, when obtaining the read error response matrix R, it is necessary to prepare the k-bit quantum bit string to 2 k possible quantum states, and then judge whether 2 k This method of acquisition is obviously unfeasible for large-scale quantum bit reading.

[0052] To address this, this embodiment further provides another solution for obtaining the read error response matrix R. The process of obtaining the read error response matrix R in step S11 includes: S11-A: Obtain the single-bit read fidelity of the corresponding quantum bit in the multi-bit read result, and determine the matrix elements in the error response matrix through the error response matrix element calculation formula to obtain the error response matrix.

[0053] Among them, the calculation formula of the error response matrix element is: (3); Both row and col are binary strings; row is the row index of the matrix, indicating the result of reading multiple quantum bits; col is the column index of the matrix, indicating the true state of multiple quantum bits; for example, assuming row is 110 and col is 010, it means the probability that the true state of a certain 3-bit quantum bit string is 010, but the result read is 110. row,col represents the matrix element at row th row and column col th in the error response matrix; k represents the number of qubits contained in the multi-bit read result; Represents the read fidelity of row th row and column col th column in the single-bit read fidelity matrix of the i-th quantum bit.

[0054] From the above, it is not difficult to see that this method determines the read error response matrix R corresponding to the k-bit quantum bit by obtaining each matrix element in the matrix through the above formula (3). In the process of determining each matrix element, it is obtained by performing a tensor product calculation on the single-bit read fidelity of the relevant quantum bit, providing another way to obtain the read error response matrix R.

[0055] Furthermore, based on the above embodiment's method for obtaining the read error response matrix R, this embodiment also provides a further implementation scheme to simplify the computational complexity. When calculating the matrix elements of the read error response matrix R using the above embodiment, the method further includes: If the Hamming distance of a matrix element is greater than the third threshold, the value of the matrix element is set to 0.

[0056] Among them, the Hamming distance is the number of different qubits in the row index and column index of the matrix element. From the above embodiment, it can be seen that the row index represents the result read by the current qubit string, and the column index represents the actual state of the current qubit string. For example, assuming that row is 110 and col is 010, since only the state of the first qubit in the row index and column index is different, the matrix element R 110,010 The Hamming distance of is 1.

[0057] It should be noted that the specific value of the third threshold value is not limited in this embodiment, and an appropriate value can be freely selected according to actual needs. It is easy to know that the larger the value of the third threshold value, the more matrix elements retained in the read error response matrix R, and the better the optimization effect on the fidelity of the multi-bit read result, but the greater the computational complexity. The smaller the value of the third threshold value, the fewer matrix elements retained in the read error response matrix R, and the slightly worse optimization effect on the fidelity of the multi-bit read result, but the computational complexity is also smaller. In practical applications, the third threshold value can be set to 5 to ensure the optimization effect on the multi-bit read result. However, in demonstration or simulation testing, the third threshold value can be set to 1 or 2 to improve the optimization efficiency of the multi-bit read result.

[0058] As can be seen from the above, in this embodiment, for matrix elements whose Hamming distance is greater than the third threshold, there is no need to further calculate them using Equation (3). Instead, they are directly assigned a value of 0, significantly simplifying the calculation process of the matrix elements. Furthermore, for the read error response matrix R itself, the matrix elements that are 0 are also excluded from the subsequent calculation of the true probability distribution, further reducing the computational difficulty of the entire process of optimizing multi-bit read results in this method.

[0059] On the other hand, the above embodiment provides a matrix element calculation method corresponding to Equation (3), which requires obtaining the single-bit read fidelity of the quantum bit corresponding to the multi-bit read result to complete the calculation. As for how to obtain the single-bit read fidelity, in addition to the preparation and re-reading mentioned in the above related technologies, this embodiment also provides another optional implementation scheme: From the pre-established index dictionary, the corresponding single-bit read fidelity is called by the index of the corresponding quantum bit.

[0060] Among them, the index dictionary stores various single-bit reading fidelity corresponding to any quantum bit in the quantum computer.

[0061] It's important to note that an indexed dictionary is also known as a dict. A dictionary is a common structure in operating systems using Python (an object-oriented programming language). It stores data using key-value pairs and is essentially a hash table implementation. Therefore, the index mentioned above is the key in the key-value pair in the dictionary, and the single-bit read fidelity is the value corresponding to the index key.

[0062] In this embodiment, as long as the index dictionary establishment process is completed once in advance, the single-bit read result can be corrected by calling the corresponding single-bit read fidelity in the index dictionary when optimizing the read result of the quantum computer any number of times. Or, when correcting the multi-bit read result, it can be used to calculate the matrix elements of the read error response matrix R based on formula (3). There is no need to repeatedly prepare quantum bits and read them multiple times, which greatly improves the optimization efficiency.

[0063] In the above embodiment, an index dictionary is pre-established, storing the various (four in total) single-bit read fidelities for all qubits in the quantum computer. During index dictionary establishment, the single-bit read fidelity can be obtained by referring to the method for obtaining the read error response matrix R in related art. This involves preparing all possible quantum states and performing repeated reads to statistically calculate the probability of each read quantum state, thereby obtaining the single-bit read fidelity matrix.

[0064] In an optional implementation, the process of establishing the index dictionary includes: S21: Encode all quantum bits contained in the quantum computer to obtain an index corresponding to each quantum bit in the quantum computer, and add a corresponding index item to a pre-established dictionary according to the index of each quantum bit.

[0065] Among them, the index can be used [i] For example, if a quantum computer contains 20 bits, then the 20 quantum bits can be indexed {q1, q2, …, q 20}.

[0066] S22: Obtain the single-bit read fidelity matrix of each quantum bit.

[0067] S23: Save the first single-bit read fidelity and the second single-bit read fidelity in the single-bit read fidelity matrix under corresponding index items in the dictionary.

[0068] Among them, the first single-bit read fidelity f 00is the reading fidelity when the current quantum bit’s true state is |0> and the |0> state is read; the second single-bit reading fidelity f 11 is the reading fidelity when the true state of the current quantum bit is the |1> state and the |1> state is read.

[0069] It should be noted that a complete single-bit read fidelity matrix excludes the first single-bit read fidelity f 00 and the second single-bit read fidelity f 11 In addition, the third single-bit read fidelity f 10 and the fourth single-bit read fidelity f 01 Among them, the third single-bit read fidelity f 10 is the reading fidelity when the actual state of the current quantum bit is |0> but the state is read as |1>. The fourth single-bit reading fidelity f 01 is the reading fidelity when the actual state of the current quantum bit is |1> but the state read is |0>.

[0070] However, due to f 10 =1-f 00 , f 01 =1-f 11 So the third single-bit read fidelity f 10 The fidelity f can be read from the first single bit 00 Fast determination, fourth-order single-bit read fidelity f 01 The fidelity f can be read from the second single bit 11 Quick determination without re-preparation and multiple sampling. Therefore, in order to further reduce the size of the data stored in the index dictionary, each quantum bit in the index dictionary only stores the first single bit read fidelity f 00 and the second single-bit read fidelity f 11 That reduces the amount of data by half.

[0071] Assuming the first single-bit read fidelity f 00 is the ith qubit among all qubits in the quantum computer, then its first single bit read fidelity is Represents. Taking the example of a quantum computer containing 20 bits, the index dictionary established in this embodiment is { q1:( ), q2:( ), …, q 20 :( )}.

[0072] Furthermore, to better illustrate how the formula (3) provided in the above embodiment implements the calculation of matrix elements under the index dictionary provided in this embodiment, this embodiment also provides a possible example: Assume that this quantum computer needs to use three qubits, and these three qubits are the 1st, 3rd and 4th of all 20 qubits in the quantum computer, and ]. If the read error response matrix element to be calculated is , then the corresponding calculation formula based on the above formula (3) is: ; Furthermore, regarding how to obtain the single-bit read fidelity matrix in the above step S22, this embodiment also provides an optional implementation scheme, where step S22 further includes: S221: Prepare the current quantum bit to the |0> state and repeat the reading multiple times.

[0073] S222: Determine a first single-bit read fidelity based on the number of times the |0> state is read in the repeated read results; and determine a third single-bit read fidelity based on the difference between 1 and the first single-bit read fidelity.

[0074] S223: Prepare the current quantum bit to the |1> state and repeat the reading multiple times.

[0075] S224: Determine a second single-bit read fidelity based on the number of times the |1> state is read in the repeated reading results; and determine a fourth single-bit read fidelity based on the difference between 1 and the second single-bit read fidelity.

[0076] It should be noted that since the index dictionary is pre-established, an optional implementation scheme is to index the dictionary at the beginning of the quantum computer. At this time, it is assumed that all quantum bits in the quantum computer are initially in the |0> state. At this time, the multiple readings in step S221 are also Figure 5 The multiple readings in step S223 are performed on the circuit shown in FIG. Figure 6 The circuit shown performs multiple readings, preparing the quantum bit from the initial state |0> to the |1> state through a quantum NOT gate and then reading it.

[0077] In summary, the present invention also provides a solution for improving the efficiency of optimizing quantum computer readout results using an index dictionary. By pre-obtaining the single-bit readout fidelity for all qubits in a quantum computer and storing it in an index dictionary, subsequent optimization of qubit readout results (applicable to both single and multi-bit qubits) can be performed directly from the index dictionary based on the corresponding qubit's index, eliminating the need for re-preparation and sampling. This significantly improves optimization efficiency and offers improved performance at large qubit scales.

[0078] On the other hand, the above embodiment also does not include the noise distribution vector p noise The acquisition of the multi-bit read result is restricted, but this embodiment provides an optional acquisition solution. The determination of the noise distribution vector corresponding to the multi-bit read result in the above step S11 specifically includes: S11-B1: Repeatedly read the quantum circuit corresponding to the multi-bit reading result in the quantum computer multiple times, and obtain the binary result string read each time.

[0079] S11-B2: Counting the number of occurrences of different binary result strings in each binary result string to determine the occurrence probability of each binary result string.

[0080] S11-B3: Determine a noise distribution vector based on the occurrence probabilities of various binary result strings.

[0081] Among them, for a quantum bit string composed of k quantum bits, there are a total of 2 binary results that can be read. k Although this embodiment does not limit the number of times a quantum circuit is repeatedly read, and any value can be set according to actual needs, in general, the number of times the same circuit is run in a common quantum cloud usually does not exceed 10,000 times, which raises a new question: When the number of qubits exceeds 14, the number of possible quantum states of the qubit string exceeds 10,000. At this point, it is impossible to obtain every possible quantum state through repeated sampling in practical applications.

[0082] To address this, this embodiment further provides a corresponding solution, which includes, after step S11-B1, the following steps: S11-B4: Completing the binary result string according to the theoretical reading result of the multi-bit reading result.

[0083] The number of occurrences of the completed binary result string is 0.

[0084] S11-B5: Sort all binary result strings.

[0085] That is, in this embodiment, the binary result string obtained by sampling is completed to avoid the loss of elements in the noise distribution vector. Moreover, for this part of the missing binary result string that needs to be completed, since it is not read in multiple repeated readings, it is indirectly explained that the read probability corresponding to this binary result string is very small and can be ignored. Therefore, in this embodiment, the statistical number of the completed binary result string can be directly assigned to 0, that is, its corresponding read probability is 0, simplifying the noise distribution vector p noise complexity, which reduces the difficulty of subsequent calculations.

[0086] Furthermore, after completing the binary result strings, all binary result strings are sorted (i.e., the probabilities of each binary result string obtained in steps S11-B2 are also sorted). This embodiment does not limit the order used for sorting; the sorting can be based on size, such as from largest to smallest or from smallest to largest. Alternatively, it can be based on bit pattern characteristics, such as the number of 1s, lexicographic order, etc., and can be freely selected based on actual needs. However, it should be noted that a primary purpose of sorting the binary result strings in this embodiment is to facilitate subsequent calculations of the read error response matrix R. Therefore, the sorting order can be based on the order of the matrix elements of the read error response matrix R.

[0087] In addition to the embodiments of the multi-qubit read result correction method provided in the above embodiments, the present invention also provides a corresponding embodiment of a computer program product. This computer program product includes a computer program / instructions that, when executed by a processor, implements the steps of the multi-qubit read result correction method described in any of the above embodiments.

[0088] Since the embodiments of the computer program product part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the computer program product part, and will not be repeated here.

[0089] In the above embodiments, a method for correcting multi-qubit read results is described in detail. The present invention also provides a corresponding embodiment of a multi-qubit read result correction device. It should be noted that the present invention describes the device embodiments from two perspectives: one from a functional module perspective and the other from a hardware perspective.

[0090] Based on the perspective of functional modules, such as Figure 7 As shown, this embodiment provides a multi-qubit reading result correction device, comprising: An acquisition module 11 is configured to acquire a noisy multi-bit read result in a quantum computer and determine a noise distribution vector and a read error response matrix corresponding to the multi-bit read result; Initialization module 12, used for initializing the ideal distribution vector to a vector having the same length as the noise distribution vector but with values of 0; An iterative module 13 is configured to iterate the ideal distribution vector with the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, and obtain the ideal distribution vector iteration result with the minimum deviation as the final ideal distribution vector; The correction module 14 is used to correct the noisy multi-bit reading result in the quantum computer through the ideal distribution vector.

[0091] Since the embodiments of the apparatus part correspond to the embodiments of the method part, please refer to the description of the embodiments of the method part for the embodiments of the apparatus part, and they will not be repeated here.

[0092] Figure 8 A structural diagram of a multi-qubit reading result correction device provided by another embodiment of the present invention is shown as follows: Figure 8 As shown, a multi-qubit reading result correction device includes: a memory 20 for storing computer programs.

[0093] The processor 21 is configured to implement the steps of a multi-qubit reading result correction method according to the above embodiment when executing a computer program.

[0094] The multi-qubit reading result correction device provided in this embodiment may include but is not limited to a quantum computer, any processor with data processing capability in a quantum computer, or an external processing device connected to a quantum computer.

[0095] Among them, the processor 21 may include one or more processing cores, such as a 4-core processor, an 8-core processor, etc. The processor 21 can be implemented in at least one hardware form of a digital signal processor (DSP), a field programmable gate array (FPGA), and a programmable logic array (PLA). The processor 21 may also include a main processor and a coprocessor. The main processor is a processor for processing data in the awake state, also known as a central processing unit (CPU); the coprocessor is a low-power processor for processing data in the standby state. In some embodiments, the processor 21 may be integrated with a graphics processing unit (GPU), which is responsible for rendering and drawing the content to be displayed on the display screen. In some embodiments, the processor 21 may also include an artificial intelligence (AI) processor, which is used to process computing operations related to machine learning.

[0096] The memory 20 may include one or more computer-readable storage media, which may be non-transitory. The memory 20 may also include high-speed random access memory, and non-volatile memory, such as one or more disk storage devices, flash memory storage devices. In this embodiment, the memory 20 is at least used to store the following computer program 201, wherein, after the computer program is loaded and executed by the processor 21, it can implement the relevant steps of a multi-qubit reading result correction method disclosed in any of the aforementioned embodiments. In addition, the resources stored in the memory 20 may also include an operating system 202 and data 203, etc., and the storage method may be temporary storage or permanent storage. Among them, the operating system 202 may include Windows, Unix, Linux, etc. The data 203 may include but is not limited to a multi-qubit reading result correction method, etc.

[0097] In some embodiments, a multi-qubit reading result correction device may further include a display screen 22 , an input / output interface 23 , a communication interface 24 , a power supply 25 , and a communication bus 26 .

[0098] Those skilled in the art will understand that Figure 8 The structure shown in does not constitute a limitation on a multi-qubit read result correction device and may include more or fewer components than shown in the figure.

[0099] An embodiment of the present invention provides a multi-qubit reading result correction device, which includes a memory and a processor. When the processor executes a program stored in the memory, it can implement the following method: a multi-qubit reading result correction method.

[0100] Finally, the present invention also provides an embodiment corresponding to a non-volatile storage medium. The non-volatile storage medium stores a computer program, which, when executed by a processor, implements the steps described in the above method embodiment.

[0101] It is understood that if the methods in the above embodiments are implemented in the form of software functional units and sold or used as independent products, they can be stored in a non-volatile storage medium. Based on this understanding, the technical solution of the present invention, or the portion 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 storage medium and executes all or part of the steps of the methods described in each embodiment of the present invention. The aforementioned storage medium includes various media that can store program code, such as a USB flash drive, a mobile hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0102] The above is a detailed introduction to a multi-qubit reading result correction method, device and medium provided by the present invention. The various embodiments in the specification are described in a progressive manner, and each embodiment focuses on the differences from other embodiments. The same and similar parts between the embodiments can be referred to each other. For the device disclosed in the embodiment, since it corresponds to the method disclosed in the embodiment, the description is relatively simple, and the relevant parts can be referred to the method part description. It should be pointed out that for ordinary technicians in this technical field, without departing from the principle of the present invention, the present invention can also be improved and modified in several ways, and these improvements and modifications also fall within the scope of protection of the present invention.

[0103] It should also be noted that, in this specification, relational terms such as first and second, etc., are used only to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "comprises," "comprising," or any other variants thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus comprising a series of elements includes not only those elements, but also other elements not explicitly listed, or elements inherent to such process, method, article, or apparatus. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of additional identical elements in the process, method, article, or apparatus comprising the element.

Claims

1. A multi-qubit reading result correction method, characterized in that: include: Obtaining a noisy multi-bit read result in a quantum computer, and determining a noisy distribution vector and a read error response matrix corresponding to the multi-bit read result; Initialize the ideal distribution vector to a vector with the same length as the noisy distribution vector but with values of 0; Iterating the ideal distribution vector with the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, and obtaining the iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector; The ideal distribution vector is used to correct the noisy multi-bit reading result in the quantum computer.

2. The multi-qubit reading result correction method according to claim 1, characterized in that: Taking the minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, iterating the ideal distribution vector, and obtaining the iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector includes: Iteratively determining the minimum value of the objective function using a gradient or non-gradient iterative method under a preset cutoff condition, and determining the value of the ideal distribution vector when the objective function takes the minimum value as the final ideal distribution vector; Wherein, the objective function is: ； R represents the read error response matrix; represents the ideal distribution vector; represents the noisy distribution vector; represents the Euclidean norm.

3. The multi-qubit reading result correction method according to claim 2, characterized in that: The preset cutoff conditions include: The result values of the objective function in two consecutive iterations are both less than the first threshold, or the number of iterations reaches the second threshold.

4. The multi-qubit reading result correction method according to any one of claims 1 to 3, characterized in that: When iterating the ideal distribution vector, the method further includes: The ideal distribution vector is limited to have a minimum value of 0 and a maximum value of 1.

5. The multi-qubit reading result correction method according to claim 1, characterized in that: Determining a read error response matrix corresponding to the multi-bit read result includes: Obtaining a single-bit read fidelity of a corresponding quantum bit in the multi-bit read result, and determining a matrix element in the error response matrix using an error response matrix element calculation formula to obtain the error response matrix; The error response matrix element calculation formula is: ； Both row and col are binary strings, row is the row index of the matrix, indicating the reading result of the multi-qubit, and col is the column index of the matrix, indicating the real state of the multi-qubit; R row,col represents the matrix element at row th row and column col th in the error response matrix; k represents the number of quantum bits contained in the multi-bit read result; Represents the read fidelity of row th row and column col th column in the single-bit read fidelity matrix of the i-th quantum bit.

6. The multi-qubit reading result correction method according to claim 5, characterized in that: When calculating the matrix elements in the error response matrix, the method further includes: If the Hamming distance of the matrix element is greater than a third threshold, setting the matrix element to 0; The Hamming distance is the number of quantum bits of different positions contained in the row index and column index of the matrix element.

7. The multi-qubit reading result correction method according to claim 5, characterized in that: Obtaining a single-bit read fidelity of a corresponding quantum bit in the multi-bit read result includes: From the pre-established index dictionary, the corresponding single-bit read fidelity is called by the index of the corresponding quantum bit; The index dictionary stores various single-bit reading fidelities corresponding to any quantum bit in the quantum computer.

8. The multi-qubit reading result correction method according to claim 7, characterized in that: The establishment of the index dictionary includes: Encode all qubits contained in the quantum computer to obtain the index corresponding to each qubit in the quantum computer, and add the corresponding index item to the pre-established dictionary according to the index of each qubit; Obtaining a single-bit read fidelity matrix for each of the quantum bits; Saving the first single-bit read fidelity and the second single-bit read fidelity in the single-bit read fidelity matrix under corresponding index items in the dictionary; Among them, the first single-bit read fidelity is the read fidelity when the current quantum bit’s true state is the |0> state and the |0> state is read; the second single-bit read fidelity is the read fidelity when the current quantum bit’s true state is the |1> state and the |1> state is read.

9. The multi-qubit reading result correction method according to claim 8, characterized in that: Obtaining the single-bit read fidelity matrix includes: Prepare the current quantum bit into the |0> state and repeatedly read it multiple times; Determining a first single-bit read fidelity based on the number of times the |0> state is read in the repeated read results; and determining a third single-bit read fidelity based on the difference between 1 and the first single-bit read fidelity; wherein the third single-bit read fidelity is the read fidelity when the actual state of the current qubit is the |0> state but the |1> state is read; Prepare the current quantum bit into the |1> state and repeatedly read it multiple times; The second single-bit read fidelity is determined based on the number of times the |1> state is read in the repeated reading results; and the fourth single-bit read fidelity is determined based on the difference between 1 and the second single-bit read fidelity; wherein the fourth single-bit read fidelity is the reading fidelity when the true state of the current quantum bit is the |1> state but the |0> state is read.

10. The multi-qubit reading result correction method according to claim 1, characterized in that: Determining a noise distribution vector corresponding to the multi-bit read result includes: Repeating multiple readings of the quantum circuit corresponding to the multi-bit reading result in the quantum computer, and obtaining a binary result string obtained each time; Counting the number of occurrences of different binary result strings in each binary result string to determine the occurrence probability of each binary result string; The noise distribution vector is determined according to the occurrence probabilities of various binary result strings.

11. The multi-qubit reading result correction method according to claim 10, characterized in that: After repeatedly reading the quantum circuit corresponding to the multi-bit reading result in the quantum computer for multiple times and obtaining the binary result string read each time, the method further includes: Completing the binary result string according to the theoretical reading result of the multi-bit reading result; wherein the number of occurrences of the completed binary result string is 0; Sort all binary result strings.

12. A multi-qubit reading result correction device, characterized in that: include: an acquisition module, configured to acquire a noisy multi-bit read result in a quantum computer and determine a noisy distribution vector and a read error response matrix corresponding to the multi-bit read result; an initialization module, configured to initialize the ideal distribution vector to a vector having the same length as the noise distribution vector but with values of 0; an iterative module, configured to iterate the ideal distribution vector with a minimum deviation between the noisy distribution vector corrected by the read error response matrix and the ideal distribution vector as a constraint condition, and obtain an iterative result of the ideal distribution vector with the minimum deviation as the final ideal distribution vector; A correction module is used to correct the noisy multi-bit reading result in the quantum computer by using the ideal distribution vector.

13. A computer program product comprising a computer program / instructions, characterized in that When the computer program / instructions are executed by a processor, the steps of the multi-qubit reading result correction method as described in any one of claims 1 to 11 are implemented.

14. A multi-qubit reading result correction device, characterized in that: include: memory for storing computer programs; A processor, configured to implement the steps of the multi-qubit reading result correction method according to any one of claims 1 to 11 when executing the computer program.

15. A non-volatile storage medium, characterized in that: The non-volatile storage medium stores a computer program, which, when executed by a processor, implements the steps of the multi-qubit reading result correction method according to any one of claims 1 to 11.

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