A system and method for measurement result analysis in quantum computing

Abstract

The application discloses a kind of measurement result analysis systems in quantum computing, including quantum computing simulator, priori setting module, data check module, posteriori calculation module, visual output module and feedback optimization module;The application also discloses a kind of measurement result analysis methods in quantum computing, based on the measurement result analysis system of one kind in quantum computing realization.The application discloses a kind of measurement result analysis systems and methods in quantum computing, the statistical index of each quantum state is calculated, not single frequency, the uncertainty of few-sample measurement result is quantified, and according to statistical index, form visual chart, abstract statistical result is translated into intuitive visual information, it is convenient for user to quickly understand the uncertainty range of quantum state probability;Meanwhile, it can flexibly meet the needs of different quantum scenes (such as algorithm verification, hardware test).The method can be used in quantum computing, quantum computing cloud platform and the like.

Description

Technical Field

[0001] This invention relates to the field of quantum computing technology, and specifically to a measurement result analysis system and method in quantum computing. Background Technology

[0002] Quantum computing is a novel computing paradigm based on quantum mechanics. Its core unit, the qubit, enables parallel information processing through superposition and entanglement states. In quantum computing, after a quantum chip or simulator executes a quantum algorithm, quantum measurement is used to convert the quantum state information into classically readable results. Due to the collapse properties of quantum measurement, the output is not the complex amplitude of the quantum state, but rather the number of samples taken from each ground state. It has wide applications in large-scale models, biomedicine, fintech, cryptographic security, artificial intelligence, large-scale unmanned systems, and aerospace.

[0003] As an important auxiliary tool for the development of quantum hardware, quantum computing simulators simulate the quantum measurement process through classical calculations and output sampling results. These results are usually displayed in the form of histograms to show the frequency of occurrence of each ground state. Theoretically, this frequency should be close to the quantum state measurement probability. However, due to the limited number of samplings, there will inevitably be a statistical deviation between the actual sampling results and the theoretical probability. This deviation is particularly significant in scenarios with few samples, which directly affects the accurate evaluation of the performance of quantum algorithms and the characteristics of quantum states.

[0004] Therefore, existing quantum computing technologies have limitations in processing sampling results. Their output mainly consists of ground state-frequency histograms and theoretical probability comparison curves, lacking in-depth statistical analysis of sampling results and failing to quantify the uncertainty of small sample measurement results. Summary of the Invention

[0005] To address the problem that existing quantum computing technologies cannot quantify the uncertainty of measurement results with a small sample size, this invention provides a measurement result analysis system and method in quantum computing.

[0006] To achieve the above objectives, the technical solution adopted by the present invention is as follows: A measurement result analysis system for quantum computing includes a quantum computing simulator, a priori setting module, a data verification module, a posterior calculation module, a visualization output module, and a feedback optimization module; wherein, The quantum computing simulator is used to perform quantum measurements and obtain a ground state count array; The prior setting module is used to preset or customize the prior distribution parameter array by default; The data verification module is used to verify whether the ground state count array is qualified; If qualified, the posterior calculation module is triggered to perform calculations based on the ground state count array and the preset prior distribution parameter array to obtain the posterior distribution parameter array; If the result is not satisfactory, the quantum computing simulator is triggered to perform a new quantum measurement to obtain a new ground state count array. The posterior calculation module is also used to calculate the statistical indicators of each quantum state based on the posterior distribution parameter array; wherein the statistical indicators include probability density distribution, mean, standard deviation and confidence interval; The visualization output module is used to generate visual charts based on statistical indicators; The feedback optimization module is used to check whether the confidence interval width of the quantum state with the most measurements exceeds a preset width threshold. If so, the feedback increases the number of samplings and triggers the quantum computing simulator to perform quantum measurements again, obtaining a new ground state count array; If not, then save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts.

[0007] In the above scheme, statistical indicators (including probability density distribution, mean, standard deviation, and confidence interval) of each quantum state are calculated by analyzing the quantum measurement results, rather than a single frequency. This quantifies the uncertainty of small sample measurement results and forms a visual chart based on the statistical indicators, transforming the abstract statistical results into intuitive visual information, which makes it easy for users to quickly understand the uncertainty range of quantum state probabilities. At the same time, through default or custom prior settings, it can flexibly meet the needs of different quantum scenarios (such as algorithm verification and hardware testing).

[0008] Preferably, the first element in the default preset prior distribution parameter array is... Prior distribution parameters .

[0009] Preferably, a qualified ground-state count array satisfies the following conditions: Ground state counting array In the middle, the first Number of measurements of each ground state It is a non-negative integer, and the total number of measurements Not less than the preset threshold number of times; in, They are respectively The number of measurements for each ground state.

[0010] Preferably, the posterior distribution parameter array is calculated using the following formula: ; in, They are respectively A prior distribution parameter, They are respectively The number of measurements for each ground state.

[0011] Preferably, the first step is calculated using the following formula. The probability density distribution of the quantum states: ; in, For the prior distribution parameter array, For the first A prior distribution parameter, To remove The sum of the remaining prior distribution parameters, excluding For the first The probability of a quantum state occurring, the binary beta function , This is a gamma function.

[0012] Preferably, the first step is calculated using the following formula. The average of the quantum states: ; in, For the first Each posterior distribution parameter.

[0013] Preferably, the first step is calculated using the following formula. Standard deviation of each quantum state: ; in, For the first Each posterior distribution parameter.

[0014] Preferably, in the visualization chart, the probability density distribution curve of the quantum state is plotted with the probability value on the horizontal axis and the probability density on the vertical axis, and the mean, standard deviation and confidence interval are labeled.

[0015] Preferably, the preset width threshold is 20%.

[0016] A method for analyzing measurement results in quantum computing, implemented based on the aforementioned system for analyzing measurement results in quantum computing, includes the following steps: S1: Perform quantum measurements to obtain the ground state count array; S2: Verify whether the ground state count array is qualified; If it passes, proceed to step S3; If it fails, return to step S1; S3: Calculate the posterior distribution parameter array based on the ground state count array and the preset prior distribution parameter array; S4: Calculate the statistical indices of each quantum state based on the posterior distribution parameter array; The statistical indicators include probability density distribution, mean, standard deviation, and confidence interval; S5: Create visual charts based on statistical indicators; S6: Check whether the confidence interval width of the quantum state with the most measurements exceeds the preset width threshold; If so, then increase the number of samples and return to step S1; If not, save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts; S7: Analysis complete.

[0017] Beneficial technical effects of the present invention: This invention provides a measurement result analysis system and method for quantum computing. By analyzing quantum measurement results, it calculates statistical indicators (including probability density distribution, mean, standard deviation, and confidence interval) for each quantum state, rather than a single frequency. This quantifies the uncertainty of small sample measurement results and generates visual charts based on the statistical indicators, transforming abstract statistical results into intuitive visual information, making it easy for users to quickly understand the uncertainty range of quantum state probabilities. At the same time, through default or custom prior settings, it can flexibly meet the needs of different quantum scenarios (such as algorithm verification and hardware testing). Attached Figure Description

[0018] Figure 1 This is a schematic diagram of the module connection of the present invention; Figure 2 This is an example of a visualization chart for the present invention; Figure 3 This is a flowchart illustrating the implementation steps of the technical solution of the present invention; The module includes: 1. Quantum computing simulator; 2. Prior setting module; 3. Data verification module; 4. Posterior calculation module; 5. Visualization output module; and 6. Feedback optimization module. Detailed Implementation

[0019] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the embodiments. However, the scope of protection of this invention is not limited to the specific embodiments described below.

[0020] Example 1 like Figure 1 As shown, a measurement result analysis system in quantum computing includes a quantum computing simulator 1, a priori setting module 2, a data verification module 3, a posterior calculation module 4, a visualization output module 5, and a feedback optimization module 6; wherein, The quantum computing simulator 1 is used to perform quantum measurements and obtain a ground state count array; The prior setting module 2 is used to preset or customize the prior distribution parameter array by default; The data verification module 3 is used to verify whether the ground state count array is qualified; If qualified, the posterior calculation module 4 is triggered to perform calculations based on the ground state count array and the preset prior distribution parameter array to obtain the posterior distribution parameter array; If it fails, the quantum computing simulator 1 is triggered to perform quantum measurement again to obtain a new ground state count array; The posterior calculation module 4 is further used to calculate the statistical indicators of each quantum state based on the posterior distribution parameter array; wherein the statistical indicators include probability density distribution, mean, standard deviation and confidence interval; The visualization output module 5 is used to generate visualization charts based on statistical indicators; The feedback optimization module 6 is used to check whether the confidence interval width of the quantum state with the most measurements exceeds a preset width threshold. If so, the feedback increases the number of samplings and triggers quantum computing simulator 1 to perform quantum measurements again, obtaining a new ground state count array; If not, then save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts.

[0021] In the specific implementation process, by analyzing the quantum measurement results, statistical indicators (including probability density distribution, mean, standard deviation, and confidence interval) of each quantum state are calculated, rather than a single frequency. This quantifies the uncertainty of small sample measurement results and generates visual charts based on the statistical indicators, transforming abstract statistical results into intuitive visual information, making it easier for users to quickly understand the uncertainty range of quantum state probabilities. At the same time, through default or custom prior settings, it can flexibly meet the needs of different quantum scenarios (such as algorithm verification and hardware testing).

[0022] Example 2 A measurement result analysis system for quantum computing includes a quantum computing simulator 1, a priori setting module 2, a data verification module 3, a posterior calculation module 4, a visualization output module 5, and a feedback optimization module 6; wherein, The quantum computing simulator 1 is used to perform quantum measurements and obtain a ground state count array; The prior setting module 2 is used to preset or customize the prior distribution parameter array by default; More specifically, the default preset prior distribution parameter array in the first... Prior distribution parameters .

[0023] The data verification module 3 is used to verify whether the ground state count array is qualified; If qualified, the posterior calculation module 4 is triggered to perform calculations based on the ground state count array and the preset prior distribution parameter array to obtain the posterior distribution parameter array; If it fails, the quantum computing simulator 1 is triggered to perform quantum measurement again to obtain a new ground state count array; More specifically, a qualified ground-state count array satisfies the following conditions: Ground state counting array In the middle, the first Number of measurements of each ground state It is a non-negative integer, and the total number of measurements Not less than the preset threshold number of times; in, They are respectively The number of measurements for each ground state.

[0024] More specifically, the posterior distribution parameter array is calculated using the following formula: ; in, They are respectively A prior distribution parameter, They are respectively The number of measurements for each ground state.

[0025] The posterior calculation module 4 is further used to calculate the statistical indicators of each quantum state based on the posterior distribution parameter array; wherein the statistical indicators include probability density distribution, mean, standard deviation and confidence interval; More specifically, the first number is calculated using the following formula. The probability density distribution of the quantum states: ; in, For the prior distribution parameter array, For the first A prior distribution parameter, To remove The sum of the remaining prior distribution parameters, excluding For the first The probability of a quantum state occurring, the binary beta function , This is a gamma function.

[0026] More specifically, the first number is calculated using the following formula. The average of the quantum states: ; in, For the first Each posterior distribution parameter.

[0027] More specifically, the first number is calculated using the following formula. Standard deviation of each quantum state: ; in, For the first Each posterior distribution parameter.

[0028] The visualization output module 5 is used to generate visualization charts based on statistical indicators; More specifically, in the visualization chart, a quantum state probability density distribution curve is plotted with probability values ​​on the horizontal axis and probability density on the vertical axis, and the mean, standard deviation, and confidence interval are labeled.

[0029] The feedback optimization module 6 is used to check whether the confidence interval width of the quantum state with the most measurements exceeds a preset width threshold. More specifically, the preset width threshold is 20%; If so, the feedback increases the number of samplings and triggers quantum computing simulator 1 to perform quantum measurements again, obtaining a new ground state count array; If not, then save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts.

[0030] In the specific implementation process, assume that the ground state count array n = [100, 130, 24, 68] obtained through quantum measurement corresponds to the ground state |00 |01 |10 |11 The number of measurements, and using the default preset prior distribution parameter array. =[1,1,1,1]; The ground state count array n = [100, 130, 24, 68] is verified to be valid (all are non-negative integers, and the sum (N=322) ≥ 10). Posterior distribution parameter array: ; Calculate statistical indicators, including: No. The probability density distribution of the quantum states: ; Mean: ; ; ; ; Standard deviation: etc; Absolute error: ; Relative error: ; 95% confidence interval: Using the 2.5% and 97.5% quantiles of the posterior sample, the confidence interval for |01> is approximately [0.3493, 0.4555] and the confidence intervals for the other three quantum states. Based on statistical indicators, plot the probability posterior distribution of the four base states, and label the mean (red dashed line), 95% confidence interval (blue solid line), mean plus or minus standard deviation (green dashed line), and relative error (e.g., ...). The relative error of the state is approximately 13.5% and the absolute error is approximately (e.g., the relative error of the state is approximately 13.5%) and the absolute error is approximately (e.g., the absolute error of the state is approximately 13.5%). The absolute error of the state is approximately 5.4%. Figure 2 As shown; Check the master quantum state (the quantum state with the most measurements, in this case, the master quantum state). The 68% confidence interval width for the (state) is approximately 5.4%. If the width exceeds a preset threshold (e.g., 10%), feedback is provided to increase the number of samplings (e.g., to more than 500 times); otherwise, the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts are saved.

[0031] Example 3 like Figure 3 As shown, a method for analyzing measurement results in quantum computing, implemented based on the aforementioned system for analyzing measurement results in quantum computing, includes the following steps: S1: Perform quantum measurements to obtain the ground state count array; S2: Verify whether the ground state count array is qualified; If it passes, proceed to step S3; If it fails, return to step S1; S3: Calculate the posterior distribution parameter array based on the ground state count array and the preset prior distribution parameter array; S4: Calculate the statistical indices of each quantum state based on the posterior distribution parameter array; The statistical indicators include probability density distribution, mean, standard deviation, and confidence interval; S5: Create visual charts based on statistical indicators; S6: Check whether the confidence interval width of the quantum state with the most measurements exceeds the preset width threshold; If so, then increase the number of samples and return to step S1; If not, save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts; S7: Analysis complete.

[0032] Based on the disclosure and teachings of the foregoing specification, those skilled in the art can make changes and modifications to the above embodiments. Therefore, the present invention is not limited to the specific embodiments disclosed and described above, and some modifications and changes to the invention should also fall within the protection scope of the claims of the present invention. Furthermore, although some specific terms are used in this specification, these terms are only for convenience of explanation and do not constitute any limitation on the present invention.

Claims

1. A measurement result analysis system for quantum computing, characterized in that, It includes a quantum computing simulator, a priori setup module, a data verification module, a posterior computation module, a visualization output module, and a feedback optimization module; among which, The quantum computing simulator is used to perform quantum measurements and obtain a ground state count array; The prior setting module is used to preset or customize the prior distribution parameter array by default; The data verification module is used to verify whether the ground state count array is qualified; If qualified, the posterior calculation module is triggered to perform calculations based on the ground state count array and the preset prior distribution parameter array to obtain the posterior distribution parameter array; If the result is not satisfactory, the quantum computing simulator is triggered to perform a new quantum measurement to obtain a new ground state count array. The posterior calculation module is also used to calculate the statistical indicators of each quantum state based on the posterior distribution parameter array; wherein the statistical indicators include probability density distribution, mean, standard deviation and confidence interval; The visualization output module is used to generate visual charts based on statistical indicators; The feedback optimization module is used to check whether the confidence interval width of the quantum state with the most measurements exceeds a preset width threshold. If so, the feedback increases the number of samplings and triggers the quantum computing simulator to perform quantum measurements again, obtaining a new ground state count array; If not, then save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts.

2. The measurement result analysis system in quantum computing according to claim 1, characterized in that, The default preset prior distribution parameter array Prior distribution parameters .

3. The measurement result analysis system in quantum computing according to claim 1, characterized in that, A qualified ground-state count array satisfies the following conditions: Ground state counting array In the middle, the first Number of measurements of each ground state It is a non-negative integer, and the total number of measurements Not less than the preset threshold number of times; in, They are respectively The number of measurements for each ground state.

4. The measurement result analysis system in quantum computing according to claim 1, characterized in that, The posterior distribution parameter array is calculated using the following formula: ； in, They are respectively A prior distribution parameter, They are respectively The number of measurements for each ground state.

5. A measurement result analysis system for quantum computing according to claim 1, characterized in that, The number is calculated using the following formula. The probability density distribution of the quantum states: ； in, For the prior distribution parameter array, For the first A prior distribution parameter, To remove The sum of the remaining prior distribution parameters, excluding For the first The probability of a quantum state occurring, the binary beta function , This is a gamma function.

6. The measurement result analysis system in quantum computing according to claim 1, characterized in that, The number is calculated using the following formula. The average of the quantum states: ； in, For the first Each posterior distribution parameter.

7. A measurement result analysis system for quantum computing according to claim 6, characterized in that, The number is calculated using the following formula. Standard deviation of each quantum state: ； in, For the first Each posterior distribution parameter.

8. A measurement result analysis system for quantum computing according to claim 1, characterized in that, In the visualization chart, the probability density distribution curve of the quantum state is plotted with the probability value on the horizontal axis and the probability density on the vertical axis, and the mean, standard deviation and confidence interval are marked.

9. A measurement result analysis system for quantum computing according to claim 1, characterized in that, The preset width threshold is 20%.

10. A method for analyzing measurement results in quantum computing, characterized in that, Includes the following steps: S1: Perform quantum measurements to obtain the ground state count array; S2: Verify whether the ground state count array is qualified; If it passes, proceed to step S3; If it fails, return to step S1; S3: Calculate the posterior distribution parameter array based on the ground state count array and the preset prior distribution parameter array; S4: Calculate the statistical indices of each quantum state based on the posterior distribution parameter array; The statistical indicators include probability density distribution, mean, standard deviation, and confidence interval; S5: Create visual charts based on statistical indicators; S6: Check whether the confidence interval width of the quantum state with the most measurements exceeds the preset width threshold; If so, then increase the number of samples and return to step S1; If not, save the ground state count array, prior distribution parameter array, posterior distribution parameter array, statistical indicators, and visualization charts; S7: Analysis complete.

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