CN109446572B - Quantum measurement and control data processing method and device - Google Patents
Quantum measurement and control data processing method and device Download PDFInfo
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- CN109446572B CN109446572B CN201811122984.5A CN201811122984A CN109446572B CN 109446572 B CN109446572 B CN 109446572B CN 201811122984 A CN201811122984 A CN 201811122984A CN 109446572 B CN109446572 B CN 109446572B
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Abstract
The invention discloses a method and a device for processing quantum measurement and control data, and belongs to the technical field of quantum measurement and control. It comprises the following steps: acquiring a distribution diagram of quantum measurement and control data; judging a functional relation according with the distribution of the quantum measurement and control data according to the distribution map; if the distribution of the quantum measurement and control data is judged not to accord with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data; and if the distribution of the quantum measurement and control data accords with the functional relation, performing function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the functional relation. The invention realizes the denoising of the quantum measurement and control data and improves the accuracy of the data obtained after denoising.
Description
Technical Field
The invention belongs to the field of quantum measurement and control, and particularly relates to a method and a device for processing quantum measurement and control data.
Background
In the manufacture of quantum chips, the quantum chips need to be tested, a network analyzer is generally used for collecting test data, the collected data are stored as measurement and control data on one hand, and on the other hand, the collected data are presented in the form of oscillating waves on the network analyzer while being stored for observation. Later stage can process and utilize the measurement and control data stored to understand the physical mathematical meaning behind the data, and even can predict the future trend development of the data by means of the model according to constructing a corresponding model.
In general, the oscillating wave in the network analyzer has the characteristics of high oscillating frequency, unstable waveform and large noise during quantum measurement and control, and according to the characteristics of the oscillating wave, the characteristics of large noise and weak data distribution regularity of the quantum measurement and control data can be obtained, and the characteristics result in low data accuracy of subsequent quantum measurement and control data processing.
Therefore, it is important to select an appropriate processing method to reduce noise and obtain accurate quantum measurement and control data.
Disclosure of Invention
1. Problems to be solved
Aiming at the problem that the data obtained by processing with high processing difficulty is inaccurate due to the characteristics of high oscillation frequency, relatively unstable waveform and large noise of the existing measurement data, the invention provides a method and a device for processing quantum measurement and control data; the invention realizes the denoising of the quantum measurement and control data and improves the accuracy of the data obtained after denoising.
2. Technical proposal
In order to solve the problems, the invention adopts the following technical scheme.
The quantum measurement and control data processing method comprises the following steps:
acquiring a distribution diagram of quantum measurement and control data;
judging a functional relation according with the distribution of the quantum measurement and control data according to the distribution map;
If the distribution of the quantum measurement and control data is judged not to accord with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data;
and if the distribution of the quantum measurement and control data accords with the functional relation, performing function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the functional relation.
Further, the obtaining the distribution map of the quantum measurement and control data specifically includes:
acquiring a three-dimensional data sequence of the quantum measurement and control data;
drawing the three-dimensional data sequence to obtain a distribution diagram; wherein: the profile comprises a three-dimensional and/or a two-dimensional map.
Furthermore, gradient noise reduction processing is performed on the quantum measurement and control data, and the method specifically comprises the following steps:
determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram;
determining a reference data sequence of the quantum measurement and control data for noise reduction in the noise reduction direction;
and obtaining the difference value between the quantum measurement and control data and the reference data sequence value to realize gradient noise reduction.
Further, before determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram, the method specifically further comprises:
acquiring a three-dimensional data sequence of the quantum measurement and control data;
Judging whether the data format of the three-dimensional data sequence is correct or not;
if the data format of the three-dimensional data sequence is judged to be correct, triggering and executing the step of determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram;
and if the data format of the three-dimensional data sequence is judged to be wrong, ending.
Further, when the functional relationship is a sine function, performing sine function fitting noise reduction processing on the quantum measurement and control data, specifically including:
acquiring the quantum measurement and control data of a selected sequence;
acquiring a function of the quantum measurement and control data of the selected sequence;
acquiring each peak value and each peak value position of the function, and forming each peak value position into a peak value position data sequence;
acquiring an initial frequency sequence value fitted by a sine function according to the reciprocal of the difference between any two peak position data in the peak position data sequence;
sequentially performing sine function fitting according to the initial frequency sequence value to obtain a selected sequence fitting function value and a root mean square error sequence;
and determining a first optimized initial frequency and a first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, and carrying out noise reduction on the quantum measurement and control data according to the first optimized selected sequence fitting function value.
Further, acquiring each peak value and each peak position of the function, and forming each peak position into a peak position data sequence, specifically including:
setting a first peak threshold feature;
and acquiring each peak value and each peak value position data of the function according to the first peak value threshold characteristic.
Further, after acquiring each peak value and each peak position data of the function according to the first peak threshold feature, the method specifically further includes:
judging whether the data length of the peak position data sequence reaches a first length threshold value or not;
and if the data length of the peak position data sequence does not reach the first length threshold value, triggering and executing the step of resetting the first peak threshold value characteristic.
Further, after determining the first optimized initial angular velocity and the first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, the method specifically further comprises:
judging whether the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value or not;
judging that the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value, and ending;
And under the condition that the minimum numerical value of the root mean square error value sequence is larger than a first root mean square error value threshold value, optimizing the first optimized initial frequency to obtain a second optimized initial frequency, and triggering and executing the step of performing sine function fitting according to the second optimized initial frequency to obtain noise-reduced quantum measurement and control data and the root mean square error value sequence until the root mean square error value is smaller than or equal to the first root mean square error value threshold value.
A quantum measurement and control data processing device, the quantum measurement and control data processing device comprising:
the first acquisition module is used for acquiring a distribution diagram of the quantum measurement and control data;
the first judging module is used for judging the functional relation which accords with the distribution of the quantum measurement and control data according to the distribution map;
the first processing module is used for carrying out gradient noise reduction processing on the quantum measurement and control data under the condition that the distribution of the quantum measurement and control data is not in accordance with a functional relation;
and the second processing module is used for carrying out function fitting noise reduction processing on the quantum measurement and control data according to a function model corresponding to the function relation under the condition that the distribution of the quantum measurement and control data is judged to accord with the function relation.
A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the quantum measurement and control data processing method at run-time.
An electronic device comprising a memory and a processor, the memory having a computer program stored therein, the processor being arranged to run the computer program to perform the quantum measurement and control data processing method.
3. Advantageous effects
Compared with the prior art, the invention has the beneficial effects that:
(1) Aiming at the problems of large noise and need of denoising treatment of the quantum measurement and control data, according to the characteristics of essential shock waves of the quantum measurement and control data, firstly acquiring a distribution diagram of the quantum measurement and control data, judging a function relation which is accordant with three-dimensional data according to the distribution diagram, and further providing a corresponding denoising treatment method, so that different types of measurement and control data treatment methods can be known, the measurement and control data can be treated in a targeted manner, and the accuracy of the measurement and control data after denoising is improved;
(2) The distribution diagram comprises a three-dimensional diagram and/or a two-dimensional diagram, and the three-dimensional diagram and/or the two-dimensional diagram can be used for judging the processing method of the measurement and control data and the accuracy of the data obtained after the denoising processing of the measurement and control data;
(3) The gradient noise reduction processing method also needs to judge the data format of the measurement and control data before defining the noise reduction direction, thereby reducing the requirement on the initial value of the measurement and control data and being easier to approach the real frequency;
(4) The difference between any two peak position data in the sine function fitting method is the initial angular velocity sequence value, so that the determination of the frequency value of measurement and control data is quickened, unnecessary working steps are avoided, and the working efficiency is improved;
(5) According to the method, the relation between the minimum value of the root mean square error value sequence and the first root mean square error value threshold is determined, so that whether the first optimized initial angular velocity needs to be further and accurately processed is determined, the gap between the first optimized initial angular velocity and the real frequency is reduced, the frequency is conveniently determined, the frequency accuracy is improved, and the function fitting accuracy is improved;
(6) The processing device of the invention carries out specific operation on a data processing method in the quantum test through actual operation, thereby facilitating specific knowledge and actual operation of the data processing method in the quantum test;
(7) The storage medium of the invention shows that the data processing method in the quantum test can achieve the effect of mass production through storage, and can be widely used.
Drawings
FIG. 1 is a flow chart of a method for processing quantum measurement and control data according to the present application;
FIG. 2 is a flow chart of a sine function fitting noise reduction process of the present application;
FIG. 3 is a three-dimensional view of quantum measurement and control data suitable for gradient noise reduction in accordance with the present application;
FIG. 4 is a three-dimensional plot of quantum measurement and control data suitable for the sine function fitting noise reduction process of the present application;
FIG. 5 is a two-dimensional graph of quantum measurement and control data suitable for gradient noise reduction in accordance with the present application;
FIG. 6 is a two-dimensional plot of quantum measurement and control data suitable for the sine function fitting noise reduction process of the present application;
FIG. 7 is a three-dimensional view of the gradient noise reduced quantum measurement and control data of the present application;
FIG. 8 is a two-dimensional plot of the gradient noise reduced quantum measurement and control data of the present application;
FIG. 9 is a two-dimensional plot of the quantum measurement and control data after sine function fitting of the present application;
FIG. 10 is a block diagram of a measurement and control data processing apparatus according to the present application;
FIG. 11 is a flow chart of a method for processing quantum measurement and control data according to the present application.
In the figure: 1. a color icon; 11. a first acquisition module; 12. a first judgment module; 13. a first processing module; 14. and a second processing module.
Detailed Description
The application will be described in detail hereinafter with reference to the drawings in conjunction with embodiments. It should be noted that, without conflict, the embodiments of the present application and features of the embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and the claims of the present invention and the above figures are used for distinguishing between similar objects and not necessarily for describing a particular sequential or chronological order.
Example 1
The embodiment provides a quantum measurement and control data processing method, fig. 1 is a flowchart of the quantum measurement and control data processing method according to an embodiment of the invention, as shown in fig. 1, the flowchart includes the following steps:
step S101: acquiring a distribution diagram of quantum measurement and control data;
step S102: judging the functional relation according with the distribution of the quantum measurement and control data according to the distribution diagram;
step S103: if the distribution of the quantum measurement and control data is judged not to accord with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data; and if the distribution of the quantum measurement and control data accords with the functional relation, performing function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the functional relation.
Step S101 to step S103, the targeted noise reduction processing is realized according to the characteristics of the quantum measurement and control data, a distribution diagram of the quantum measurement and control data is firstly obtained, and the functional relation which the quantum measurement and control data accords with is judged according to the distribution diagram, so that a corresponding noise reduction processing method is provided, and the method specifically comprises the following steps: the quantum measurement and control data accords with the function relation, and the frequency of the shock wave corresponding to the quantum measurement and control data is proved to follow a certain rule, so that function fitting noise reduction treatment is carried out by adopting a function type model corresponding to the function relation; the quantum measurement and control data are in line with a sine function relation, and the frequency of the oscillating wave corresponding to the quantum measurement and control data is indicated to follow a sine waveform rule, and at the moment, a sine function is adopted for fitting noise reduction treatment; the quantum measurement and control data accords with the one-time function relation, and then straight line fitting noise reduction treatment is adopted; when the quantum measurement and control data do not accord with the functional relation, the waveform rule followed by the frequency of the oscillating wave corresponding to the quantum measurement and control data is uncertain, so that gradient noise reduction treatment is adopted. Classification noise reduction is adopted according to the essential characteristics of the quantum measurement and control data, so that the blindness of noise reduction processing is reduced, and the accuracy of the data obtained by the noise reduction processing is ensured to a certain extent.
In an alternative embodiment of the present embodiment, for the step S101, the obtaining of the distribution map of the quantum measurement and control data may be implemented as follows:
s101-1, acquiring a three-dimensional data sequence of quantum measurement and control data;
specifically: the three-dimensional data sequence of the quantum measurement and control data is X, Y, Z sequence, and Z is a function value of X, Y, which may be expressed as Z (X, Y) by way of example.
S101-2, drawing a three-dimensional data sequence to obtain a distribution diagram; wherein: the profile includes a three-dimensional map and/or a two-dimensional map.
Specifically, the three-dimensional graph refers to a graph capable of reflecting three characteristics of the X, Y, Z sequence at the same time, and can be represented by adopting a space three-dimensional graph, or can also adopt a space two-dimensional plane graph to reflect the three characteristics of the X, Y, Z sequence by matching with other characteristics, such as color characteristics, so as to intuitively reflect the data distribution characteristics.
The two-dimensional graph refers to a graph reflecting the two characteristic relations of the X, Z sequence or a graph reflecting the two characteristic relations of the Y, Z sequence, and the two-dimensional graph is based on the visual reflection of the data distribution characteristics.
In an alternative embodiment of the present embodiment, the gradient noise reduction processing for the quantum measurement and control data in the step S103 is implemented by the following steps:
Step S103-3, determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram;
specifically, since the function value Z of the quantum measurement and control data is the function value of X, Y, that is, Z is Z (X, Y), it is determined that noise reduction is performed on Z along the X direction or the Y direction, which is determined by the characteristics of Z (X, Y) in the X direction or the Y direction.
Step S103-4, determining a reference data sequence of quantum measurement and control data for noise reduction in the noise reduction direction;
and step S103-5, obtaining a difference value between the quantum measurement and control data and the reference data sequence value, and carrying out gradient noise reduction.
In an alternative embodiment of the present embodiment, before determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram in step S103-3, the method further includes:
step S103-1, obtaining a three-dimensional data sequence of quantum measurement and control data, namely a X, Y, Z sequence;
step S103-2, judging whether the data format of the three-dimensional data sequence is correct; if the data format of the three-dimensional data sequence is judged to be correct, triggering and executing the step of determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram; and if the data format of the three-dimensional data sequence is judged to be wrong, ending.
Specifically, the data length of the X sequence is denoted as length (X), the data length of the Y sequence is denoted as length (Y), the data length of the Z sequence is denoted as length (Z), and if length (Z) =length (X) ×length (Y), it is indicated that the data format of the quantum measurement and control data is correct, and the quantum measurement and control data can be processed and utilized; otherwise, the error is not processed.
In this embodiment, after gradient noise reduction is performed on the difference value between the quantum measurement and control data and the reference data sequence value obtained in step S103-5, the method further includes:
step S103-6: carrying out gradient noise reduction on the quantum measurement and control data obtained by the gradient noise reduction obtained in the step S103-5 for the second time, comparing the second gradient noise reduction result with the first gradient noise reduction result, and if the two results are consistent, indicating that the first gradient noise reduction result meets the condition, and ending the noise reduction; if the two results are consistent, the second gradient noise reduction result is good, and the noise reduction is finished; otherwise, repeating the above process to continue noise reduction.
In an optional embodiment of this embodiment, when the functional relationship in the step S103 is a sine function, a sine function fitting noise reduction process is performed on the quantum measurement and control data, which is specifically implemented by the following manner:
step S104-1, quantum measurement and control data of a selected sequence are obtained;
step S104-2, obtaining a function of quantum measurement and control data of a selected sequence;
Step S104-3, each peak value and each peak value position of the function are obtained, and each peak value position is formed into a peak value position data sequence;
step S104-4, obtaining an initial frequency sequence value of sine function fitting according to the reciprocal of the difference between any two peak position data in the peak position data sequence, specifically, the difference between any two peak position data is T, and the initial frequency f=1/T of sine function fitting;
and step S104-5, sequentially performing sine function fitting according to the initial frequency sequence value to obtain a selected sequence fitting function value and a root mean square error sequence.
And step S104-6, determining a first optimized initial angular velocity and a first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, and carrying out noise reduction on the quantum measurement and control data according to the first optimized selected sequence fitting function value.
In the specific implementation, a certain sequence of the three-dimensional data of the quantum measurement and control is obtained as a noise reduction basis, function fitting is carried out on the selected sequence, and then the quantum measurement and control data of other sequences and the function fitting value of the sequence are subjected to difference, so that the noise reduction can be completed.
Specifically, two-dimensional X, Z or Y, Z in quantum measurement and control data, wherein: x, Z may be expressed as Z (X), Y, Z may be expressed as Z (Y), a function image of Z (X) or Z (Y) is obtained, Z (Y) when the X value is selected as X0 is selected as an example in this embodiment, each peak value and each peak position of the Z (Y) function image are obtained, and each peak position is formed into a peak position data sequence; and acquiring initial angular speed or initial frequency of sine function fitting according to the difference between any two peak position data in the peak position data sequence, wherein the difference between any two peak position data is T, and the initial frequency f=1/T of sine function fitting.
Wherein the sine is fitted to the functionWherein 1 represents the amplitude of the function, +.>Representing up-down displacement of the function, d representing up-down translation of the function image, ω representing angular velocity, f representing frequency, the relation between the two being w=2pi f, further obtaining a function angular velocity w data sequence or a frequency f sequence, then traversing each initial value of the angular velocity w data sequence (or the frequency f sequence) as an initial value, performing sine function fitting, recording root mean square error values of each fitting to form a root mean square error sequence, then determining a minimum root mean square error value, taking the initial angular velocity (or frequency) corresponding to the minimum root mean square error value as a first optimized initial angular velocity (or frequency), taking the function fitting value corresponding to the minimum root mean square error value as a first best fitting function value, in the process, determining the initial value of the angular velocity (or frequency) by means of peak positions, performing sine function fitting according to the obtained initial values of the plurality of angular velocities (or frequencies), determining the best fitting result, namely the first best fitting function value parameters 1, ω (or f) and, in specific implementation, the first best fitting function value parameters 1, ω (or f) and (or f) of the best fitting function value are performed >d, recording, wherein the process reduces the data debugging period and also provides an accurate noise reduction foundation for noise reduction of the quantum measurement and control data.
Since the first best fit function value is Z (Y) when the X value is selected to be X0, it is denoted as Z X0 (Y) Z of other X sequences can be directly reduced in the subsequent noise X (Y) and Z X0 And (Y) performing difference, so that noise reduction of the quantum measurement and control data can be realized.
Through the steps S104-1 to S104-6, the problems faced when the function fitting is carried out due to unstable frequency of the quantum measurement and control data are overcome, and particularly, the least square fitting method of the sine function is used for comparing the initial frequency depending on the oscillating wave. For quantum measurement and control data with unstable frequency, if a sine function least square fitting method is adopted to directly process the quantum measurement and control data, the period value of the data is required to be continuously debugged to obtain the initial frequency of the oscillating wave, and the debugging period and the data processing difficulty are greatly increased in the whole process. The data debugging period and the data processing difficulty can be greatly reduced, specifically, the difference between any two peak positions is obtained through the function peak value of quantum measurement and control data, namely, the period T between any two peak values, and the function frequency f or the function angular velocity w is obtained according to the peak period; w=2pi f=2pi/T, and further obtain a function frequency f or a function angular velocity w data sequence, take each angular velocity value in the function frequency f or the angular velocity w data sequence as an angular velocity initial value, traverse each frequency initial value or angular velocity initial value, and perform sine function fitting, record root mean square error values of each fitting to form a root mean square error sequence, determine a minimum root mean square error value, and take an initial frequency or initial angular velocity corresponding to the minimum root mean square error value as a first optimized frequency or a first optimized initial angular velocity, select a sequence fitting function value from function fitting values corresponding to the minimum root mean square error value, in the process, by determining a frequency initial value or an angular velocity initial value by means of a peak value, perform sine function fitting according to a plurality of obtained frequency initial values or angular velocity initial values, determine an optimal fitting result according to root mean square error values of each fitting, namely, the first optimized selected sequence fitting function value, and perform noise reduction of quantum measurement and control data on the basis.
In an alternative embodiment of the present embodiment, for each peak and each peak position of the acquisition function in step S104-3, the peak positions are combined into a peak position data sequence by:
step S104-3-1, setting a first peak threshold feature;
step S104-3-2, each peak value and each peak value position data of the function are obtained according to the first peak value threshold value characteristic.
Through the steps S104-3-1 to S104-3-2, the searching of the peak value of the quantum measurement and control data and the determination of the peak value position are realized. Specifically, reference may be made to chinese patent application No. 201810513833.6, which is a method for searching for peak values of quantum measurement and control data introduced in a method for testing a quantum chip, and will not be described herein.
In an alternative embodiment of the present embodiment, after each peak and each peak position data of the function are obtained according to the first peak threshold feature in step S104-3-2, the method further includes:
step S104-3-3, judging whether the data length of the peak position data sequence reaches a first length threshold value;
step S104-3-4, if the data length of the peak position data sequence is not up to the first length threshold, triggering to execute the step of resetting the first peak threshold feature.
Through the step S104-3-3 and the step S104-3-4, the repeated traversing searching of the peak value is realized, the searched peak value which is as complete as possible is ensured, and the initial angular velocity which is as accurate as possible is further ensured.
In an alternative embodiment of the present embodiment, after determining the first initial angular velocity and the first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence in the step S104-6, the method further includes:
step S104-7, judging whether the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value;
judging that the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value, and ending;
and under the condition that the minimum numerical value of the root mean square error value sequence is larger than the first root mean square error value threshold value, optimizing the first optimized initial angular velocity to obtain a second optimized initial angular velocity, and triggering and executing the step of performing sine function fitting according to the second optimized initial angular velocity to obtain noise-reduced quantum measurement and control data and the root mean square error sequence until the root mean square error value is smaller than the first root mean square error value threshold value.
The optimization adjustment of the first optimized initial angular velocity determined for the first time is carried out according to the root mean square error value sequence, so that the accuracy of function fitting is further improved, and the accuracy of the obtained noise reduction data is ensured.
Example 2
The present embodiment provides a quantum measurement and control data processing method, and the specific implementation method is the same as embodiment 1, and is different from the embodiment in that the present invention is illustrated by the following specific implementation manner.
The embodiment aims at quantum measurement and control data A, wherein the quantum measurement and control data A is three-dimensional data and is stored in the form of (x, y, z). When data processing is performed, the following is specific:
step S201, drawing three-dimensional data A by using an m1tplotlib open source module to obtain a distribution diagram of the three-dimensional data; wherein: the profile includes a three-dimensional map and/or a two-dimensional map. The three-dimensional graph refers to a graph capable of reflecting three characteristics of the X, Y, Z sequence at the same time, and can be represented by a space three-dimensional graph, or can be represented by a space two-dimensional plane graph matched with other characteristics, such as color characteristics or gray characteristics, so as to reflect the three characteristic relationships of the X, Y, Z sequence, and the data distribution characteristics can be intuitively reflected. The two-dimensional graph refers to a graph reflecting the two characteristic relations of the X, Z sequence or a graph reflecting the two characteristic relations of the Y, Z sequence, and the two-dimensional graph is based on the visual reflection of the data distribution characteristics.
In this embodiment, a graph of three feature relationships of X, Y, Z sequence is reflected by matching a space two-dimensional plan view with gray features, as shown in fig. 3 and 4, where in fig. 3 and 4, the X sequence of data is taken as the X axis, the Y sequence of data is taken as the X axis, the gray value on the xy plane reflects the Z value feature, and according to the color icon 1 on one side, it can be found that the gray value corresponding to the positive Z value along the Y axis increases, that is, the noise of the positive quantum measurement and control data along the Y axis gradually increases. And fig. 3 is that the quantum measurement and control data does not follow a specific waveform rule, and fig. 4 is that the quantum measurement and control data follows a sine waveform rule. In order to further intuitively display the distribution of the quantum measurement and control data, a two-dimensional graph is also adopted in the embodiment to reflect two characteristic relationships of the Y, Z sequence, as shown in fig. 5 and 6. Wherein, fig. 5 is the characteristic data of quantum measurement, other data is noise data, the distribution of the data does not follow the specific waveform rule, and fig. 6 is the sine waveform rule of measurement and control data.
Step S202, judging that the distribution of the quantum measurement and control data accords with a legal sine function relation according to a distribution diagram;
step S203, if the distribution of the quantum measurement and control data is judged not to accord with the function relation, carrying out gradient noise reduction treatment on the quantum measurement and control data; and if the distribution of the quantum measurement and control data accords with the function relation, performing sine function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the function relation.
Specifically, as the function data shown in fig. 3 and 5, the distribution does not follow a specific waveform rule, then the gradient noise reduction process; if the data of fig. 4 and 6 satisfy a certain sine function characteristic, a sine function fitting noise reduction process is adopted.
The gradient noise reduction processing for the quantum measurement and control data in the step S203 is realized through the following steps:
step S203-1, obtaining a three-dimensional data sequence of quantum measurement and control data, namely a X, Y, Z sequence;
step S203-2, judging whether the data format of the three-dimensional data sequence is correct; if the data format of the three-dimensional data sequence is judged to be correct, the step S203-3 is carried out; and if the data format of the three-dimensional data sequence is judged to be wrong, ending.
Specifically, the data length of the X sequence is denoted as length (X), the data length of the Y sequence is denoted as length (Y), the data length of the Z sequence is denoted as length (Z), and if length (Z) =length (X) ×length (Y), it is indicated that the data format of the quantum measurement and control data is correct, and the quantum measurement and control data can be processed and utilized; otherwise, the error is not processed.
Step S203-3, determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram; in the present embodiment, as for the function data shown in fig. 3 and 5, it can be seen from fig. 3 that the noise value greatly varies with the positive direction of the Y direction, so gradient noise reduction is performed in the X direction, and if gradient noise reduction is performed in the Y direction, the function value with large noise minus the function value with small noise does not have the effect of noise reduction. The present embodiment determines that denoising is performed in the X direction. The specific operation procedure is shown in steps S203-4 to S203-5.
Step S203-4, determining a reference data sequence of quantum measurement and control data for noise reduction in the noise reduction direction;
specifically, the maximum Z value of each Y line is determined in the X direction, and the maximum Z values of all Y lines are recorded as the reference data sequence Zm1X (xi, yj). This process may be obtained using a traversal comparison process, which is not described in further detail herein.
And step S203-5, obtaining a difference value between the quantum measurement and control data and the reference data sequence value, and performing gradient noise reduction.
After the noise reduction is finished, the data can be stored, and the m1tplotlib open source module is adopted again to plot the three-dimensional data 1 after the noise reduction. The three-dimensional graph is drawn as shown in fig. 7, and the background color of the graph is basically consistent, which indicates that the noise is removed by 1; and the two-dimensional graph is shown in fig. 8, so that the characteristic value of the quantum measurement and control data of the graph is obviously separated from the noise value.
The step S203 of performing sine function fitting noise reduction processing on the quantum measurement and control data is implemented by the following steps for the data satisfying certain sine function characteristics as shown in fig. 4 and 6:
step S204-1, quantum measurement and control data of a selected sequence are obtained;
specifically, in the quantum measurement and control data, two dimensions X, Z or Y, Z are provided, wherein: x, Z may be expressed as Z (X), Y, Z may be expressed as Z (Y), and a function image of Z (X) or Z (Y) is acquired, and Z (Y) is exemplified when the value X in this embodiment is selected as X0.
Step S204-2, obtaining a function of quantum measurement and control data of Z (Y);
step S204-3, each peak value and each peak value position of the function are obtained, and each peak value position is formed into a peak value position data sequence;
Wherein; for each peak and each peak position of the acquisition function in step S204-3, the peak positions are combined into a peak position data sequence by:
step S204-3-1, setting a first peak threshold feature;
step S204-3-2, each peak value and each peak value position data of the function are obtained according to the first peak value threshold characteristic.
Through the steps S204-3-1 to S204-3-2, the searching of the peak value of the quantum measurement and control data and the determination of the peak value position are realized. Specifically, reference may be made to chinese patent application No. 201810513833.6, which is a method for searching for peak values of quantum measurement and control data introduced in a method for testing a quantum chip, where the peak value position is stored in an array frequency, so as to determine the frequency f of a function.
Step S204-3-3, judging whether the data length of the peak position data sequence reaches a first length threshold value;
step S204-3-4, if it is determined that the data length of the peak position data sequence does not reach the first length threshold, triggering the step of resetting the first peak threshold feature.
Through the secondary traversal searching of the peak value, the searched complete peak value is ensured, and the initial angular speed as accurate as possible is further ensured.
In specific operation, referring to fig. 2, when the data length of the array frequency is smaller than or equal to the first length threshold, it is indicated that the number of the selected function peaks is insufficient, and this will cause the automatic peak/valley searching algorithm r1 ndow 1lk to stay between specific values when being called, so that the period of the function is not easy to be determined, therefore when the data length of the array frequency is smaller than or equal to the first length threshold, the values in the array frequency contained in the Y sequence and the Z sequence are removed, the values in the array frequency are transferred to the array temp for temporary storage, the peak value of the function is determined by calling the automatic peak/valley searching algorithm r1 ndow 1lk and stored in the array temp until the length of the array frequency is greater than or equal to the first length threshold, that is, the number of the selected function peaks is sufficient to determine the period of the function, and at this time, all the data in the temporary storage is transferred to the array frequency, and step S204-4 is executed.
S204-4, acquiring an initial frequency sequence value fitted by a sine function according to the difference between any two peak position data in the peak position data sequence; wherein: the difference between the peak position data represents the period T of any two adjacent peaks, from which the frequency f can be calculated, specifically: f=1/T.
And S204-5, sequentially performing sine function fitting according to the initial frequency sequence value to obtain noise-reduced quantum measurement and control data and a root mean square error sequence.
Specifically, each initial angular velocity is traversed, and is substituted as an initial value into a least square sine fitting function le1stsq to perform least square fitting, the fitting result is stored in an array FitResult, and meanwhile, the root mean square error is calculated for each fitting result and is stored in an array RMSE, although the sine function is aimed atThe invocation of the least squares sine fit function le1stsq function requires the transfer of four parameters 1, f,/-for>d fitting, wherein 1 represents the amplitude of the function, f represents the frequency of the function, +.>Representing the up-down displacement of the function, d representing the up-down translation of the function image, but according to the characteristics of the le1stsq function, the result of fitting the function depends largely on the frequency f, so that the initial value of the frequency f is determined to call the le1stsq function for fitting.
And S204-6, determining a first optimized initial angular velocity and a first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, and carrying out noise reduction on the quantum measurement and control data according to the first optimized selected sequence fitting function value.
Wherein: first optimizing the selected sequence fitting function value to record parameters 1, f,d, recording in a form, and performing noise reduction, namely performing difference calculation on quantum measurement and control data of other sequences and quantum measurement and control data of selected sequences.
Step S204-1 to step S204-6 overcome the problem faced by the function fitting of the unstable frequency of the quantum measurement and control data, and particularly, the least square fitting method of the sine function is used for comparing the initial frequency depending on the oscillating wave. For quantum measurement and control data with unstable frequency, if a sine function least square fitting method is adopted for processing, the period value of the data is required to be continuously debugged to obtain the initial frequency of the oscillating wave, and the debugging period and the data processing difficulty are greatly increased in the whole process.
Step S204-7, judging whether the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value;
judging that the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value, and ending;
and under the condition that the minimum numerical value of the root mean square error value sequence is larger than the first root mean square error value threshold value, optimizing the first optimized initial angular velocity to obtain a second optimized initial angular velocity, and triggering and executing the step of performing sine function fitting according to the second optimized initial angular velocity to obtain noise-reduced quantum measurement and control data and root mean square error until the root mean square error value is larger than or equal to the first root mean square error value threshold value.
And through the step S204-7, the accuracy of function fitting is further improved by optimally adjusting the first optimized initial angular velocity determined for the first time according to the root mean square error value sequence.
Specific: the smaller the root mean square error value, the higher the fitting similarity, the larger the value, the lower the fitting similarity, and further optimization is needed. So that the first optimized initial frequency is optimized under the condition that the minimum value of the root mean square error value sequence is judged to be larger than the first root mean square error value threshold valueObtaining a second optimized initial frequency, graphically reducing the frequency f by 1/n or enlarging it by a factor of n, where n = 1,2,3,4,5,6, … …, each time a second optimized initial frequency is obtained, performing a sinusoidal function according to the second optimized initial frequencyAnd (3) obtaining noise-reduced quantum measurement and control data and root mean square error, comparing the root mean square error with a first root mean square error value threshold, and ending the program if the root mean square error is smaller than or equal to the first root mean square error value threshold.
This is because the root mean square error is the square root of the ratio of the square of the observed value to the true value deviation and the number of observations n, in actual measurement, the number of observations n is always limited, the true value can only be replaced by the most reliable (optimal) value, the root mean square error is very sensitive to the reflection of an extra large or extra small error in a set of measurements, so that the root mean square error can reflect the precision of the measurements, and the smaller the root mean square error value, the higher the fitting precision.
And according to the index value corresponding to the minimum value of the data in the array RMSE, the parameter value in the array FitResult, namely 1, f,d=fitresult index value]. Then 1, f, & gt>d proxy least squares sine fitting function +.>In the process, the obtained function graph of the first best fitting function value is shown as a graph in fig. 9, and the sine function fitting graph by the method and the quantum measurement and control data shown in fig. 6 can be seen to have higher fitting degree.
The initial value of the angular velocity is determined by processing the measured data through function fitting, so that the accuracy of the initial value of the frequency is ensured, the accuracy of the measured data processing is also ensured, the similarity between the fitted function data and the measured data is improved, and the trend rule of the quantum measurement and control data is found by least square fitting of a sine function on one hand and noise reduction on the other hand.
Example 3
The present embodiment provides a processing device for a quantum program, which is used to implement the foregoing embodiments and preferred embodiments, and is not described in detail. As used below, the term "module" may be a combination of software and/or hardware that implements a predetermined function. While the means described in the following embodiments are preferably implemented in software, implementation in hardware, or a combination of software and hardware, is also possible and contemplated.
FIG. 10 is a block diagram of a quantum measurement and control data processing apparatus according to an embodiment of the present invention, as shown in FIG. 10, the quantum measurement and control data processing apparatus includes: the first acquisition module 11 is used for acquiring a distribution diagram of the quantum measurement and control data; the first judging module 12 is used for judging the functional relation according with the distribution of the quantum measurement and control data according to the distribution map; the first processing module 13 is configured to perform gradient noise reduction processing on the quantum measurement and control data under the condition that the distribution of the quantum measurement and control data is determined to be not in accordance with the functional relationship; and the second processing module 14 is configured to perform sine function fitting noise reduction processing on the quantum measurement and control data according to a function model corresponding to the function relationship if it is determined that the distribution of the quantum measurement and control data accords with the function relationship.
The specific embodiment is directed to a processing flow of the quantum measurement and control data C, which is three-dimensional data and is stored in a form of (X, Y, Z), as shown in fig. 11. When data processing is performed, the following is specific:
step 1: directly importing the quantum measurement and control data C into a quantum measurement and control data processing device, and carrying out specific processing on the quantum measurement and control data C in the quantum measurement and control data processing device;
Step 2: the quantum measurement and control data C can acquire a distribution diagram of the quantum measurement and control data C through the first acquisition module 11;
step 2.1: acquiring a three-dimensional data sequence of quantum measurement and control data C;
step 2.2: the three-dimensional data sequence of the quantum measurement and control data C is X, Y, Z sequence, and Z is a function value of X, Y, and illustratively, Z may be represented as Z (X, Y);
step 2.3: drawing a three-dimensional data sequence of the quantum measurement and control data C to obtain a distribution diagram; wherein: the profile comprises a three-dimensional and/or two-dimensional map;
step 3: the first judging module 12 judges the functional relation according to the distribution diagram obtained in the step 2, in which the distribution of the quantum measurement and control data C accords with, and judges the noise reduction direction of the quantum measurement and control data C; if the distribution of the quantum measurement and control data C accords with the sine function relation, the quantum measurement and control data C is processed by the second processing module 14; if the distribution of the quantum measurement and control data C does not accord with the functional relation, the quantum measurement and control data C is processed by the first processing module 13;
step 4: when the distribution of the quantum measurement and control data C does not accord with the functional relationship, the first processing module 13 processes the quantum measurement and control data C through gradient noise reduction, and the specific processing process of the gradient noise reduction on the quantum measurement and control data C is as shown in embodiment 1, and is not described in detail here;
Step 5: when the distribution of the quantum measurement and control data C accords with the sine function relationship, the second processing module 14 processes the quantum measurement and control data C through function fitting, and the specific processing process of the function fitting on the quantum measurement and control data C is also as shown in embodiment 1, and no specific description is given here;
step 6: the data in the quantum measurement and control data C can be processed to obtain new measurement and control data, the new measurement and control data can be processed through the first acquisition module 11, so that a distribution diagram of the new measurement and control data is acquired, the approximate distribution of the new measurement and control data is known, whether the data processing in the quantum measurement and control data C is reasonable or not is judged, if not, the processing is continued, and if so, the new measurement and control data is tidied and collected for standby.
It should be noted that each of the above modules may be implemented by software or hardware, and for the latter, it may be implemented by, but not limited to: the modules are all located in the same processor; alternatively, the above modules may be located in different processors in any combination.
Example 4
The present embodiment provides a storage medium having a computer program stored therein, wherein the computer program is arranged to perform the steps of any of the method embodiments described above when run.
Alternatively, in the present embodiment, the above-described storage medium may be configured to store a computer program for performing the steps of:
step S1, obtaining a distribution diagram of quantum measurement and control data;
s2, judging a functional relation according with the distribution of the quantum measurement and control data according to the distribution diagram;
step S3, if the distribution of the quantum measurement and control data is judged to be not in accordance with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data; and if the distribution of the quantum measurement and control data accords with the function relation, performing sine function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the function relation.
Alternatively, in the present embodiment, the storage medium may include, but is not limited to: a usb disk, a Read-Only Memory (ROM), a random access Memory (Random Access Memory, RAM), a removable hard disk, a magnetic disk, or an optical disk, or other various media capable of storing a computer program.
Example 5
The present embodiment provides an electronic device comprising a memory having a computer program stored therein and a processor arranged to run the computer program to perform the steps of any of the method embodiments described above.
Optionally, the electronic apparatus may further include a transmission device and an input/output device, where the transmission device is connected to the processor, and the input/output device is connected to the processor.
Alternatively, in the present embodiment, the above-described processor may be configured to execute the following steps by a computer program:
step S1, obtaining a distribution diagram of quantum measurement and control data;
s2, judging a functional relation according with the distribution of the quantum measurement and control data according to the distribution diagram;
step S3, if the distribution of the quantum measurement and control data is judged to be not in accordance with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data; and if the distribution of the quantum measurement and control data accords with the function relation, performing sine function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the function relation.
Alternatively, specific examples in this embodiment may refer to examples described in the foregoing embodiments and optional implementations, and this embodiment is not described herein.
It will be appreciated by those skilled in the art that the modules or steps of the invention described above may be implemented in a general purpose computing device, they may be concentrated on a single computing device, or distributed across a network of computing devices, they may alternatively be implemented in program code executable by computing devices, so that they may be stored in a memory device for execution by computing devices, and in some cases, the steps shown or described may be performed in a different order than that shown or described, or they may be separately fabricated into individual integrated circuit modules, or multiple modules or steps within them may be fabricated into a single integrated circuit module for implementation. Thus, the present invention is not limited to any specific combination of hardware and software.
The invention and its embodiments have been described above schematically, without limitation, and the actual construction is not limited to this, but is shown in the drawings as one of its embodiments. Therefore, if one of ordinary skill in the art is informed by this disclosure, a structural manner and an embodiment similar to the technical scheme are not creatively designed without departing from the gist of the present invention, and all the structural manners and the embodiment are considered to be within the protection scope of the present patent.
Claims (11)
1. The quantum measurement and control data processing method is characterized by comprising the following steps of:
acquiring a distribution diagram of quantum measurement and control data;
judging a functional relation according with the distribution of the quantum measurement and control data according to the distribution map;
if the distribution of the quantum measurement and control data is judged not to accord with the functional relation, carrying out gradient noise reduction treatment on the quantum measurement and control data;
and if the distribution of the quantum measurement and control data accords with the functional relation, performing function fitting noise reduction treatment on the quantum measurement and control data according to a function model corresponding to the functional relation.
2. The method for processing quantum measurement and control data according to claim 1, wherein the obtaining the distribution map of the quantum measurement and control data specifically comprises:
Acquiring a three-dimensional data sequence of the quantum measurement and control data;
drawing the three-dimensional data sequence to obtain a distribution diagram; wherein: the profile comprises a three-dimensional and/or a two-dimensional map.
3. The method for processing quantum measurement and control data according to claim 1, wherein the gradient noise reduction processing is performed on the quantum measurement and control data, and specifically comprises the following steps:
determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram;
determining a reference data sequence of the quantum measurement and control data for noise reduction in the noise reduction direction;
and obtaining the difference value between the quantum measurement and control data and the reference data sequence value to realize gradient noise reduction.
4. The method for processing quantum measurement and control data according to claim 3, further comprising, before determining the noise reduction direction of the quantum measurement and control data according to the distribution map:
acquiring a three-dimensional data sequence of the quantum measurement and control data;
judging whether the data format of the three-dimensional data sequence is correct or not;
if the data format of the three-dimensional data sequence is judged to be correct, triggering and executing the step of determining the noise reduction direction of the quantum measurement and control data according to the distribution diagram;
And if the data format of the three-dimensional data sequence is judged to be wrong, ending.
5. The method for processing quantum measurement and control data according to claim 1, wherein when the functional relationship is a sine function, performing sine function fitting noise reduction processing on the quantum measurement and control data, specifically comprising:
acquiring the quantum measurement and control data of a selected sequence;
acquiring a function of the quantum measurement and control data of the selected sequence;
acquiring each peak value and each peak value position of the function, and forming each peak value position into a peak value position data sequence;
acquiring an initial frequency sequence value fitted by a sine function according to the reciprocal of the difference between any two peak position data in the peak position data sequence;
sequentially performing sine function fitting according to the initial frequency sequence value to obtain a selected sequence fitting function value and a root mean square error sequence;
and determining a first optimized initial frequency and a first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, and carrying out noise reduction on the quantum measurement and control data according to the first optimized selected sequence fitting function value.
6. The method for processing quantum measurement and control data according to claim 5, wherein obtaining each peak value and each peak position of the function and forming each peak position into a peak position data sequence comprises:
Setting a first peak threshold feature;
and acquiring each peak value and each peak value position data of the function according to the first peak value threshold characteristic.
7. The method according to claim 6, wherein after acquiring each peak value and each peak position data of the function according to the first peak threshold feature, the method further comprises:
judging whether the data length of the peak position data sequence reaches a first length threshold value or not;
and if the data length of the peak position data sequence does not reach the first length threshold value, triggering and executing the step of resetting the first peak threshold value characteristic.
8. The method according to claim 5, wherein after determining the first optimized initial angular velocity and the first optimized selected sequence fitting function value according to the minimum value of the root mean square error value sequence, further comprising:
judging whether the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value or not;
judging that the minimum value of the root mean square error value sequence is smaller than or equal to a first root mean square error value threshold value, and ending;
And under the condition that the minimum numerical value of the root mean square error value sequence is larger than a first root mean square error value threshold value, optimizing the first optimized initial frequency to obtain a second optimized initial frequency, and triggering and executing the step of performing sine function fitting according to the second optimized initial frequency to obtain noise-reduced quantum measurement and control data and the root mean square error value sequence until the root mean square error value is smaller than or equal to the first root mean square error value threshold value.
9. The utility model provides a quantum measurement and control data processing apparatus which characterized in that, quantum measurement and control data processing apparatus includes:
the first acquisition module is used for acquiring a distribution diagram of the quantum measurement and control data;
the first judging module is used for judging the functional relation which accords with the distribution of the quantum measurement and control data according to the distribution map;
the first processing module is used for carrying out gradient noise reduction processing on the quantum measurement and control data under the condition that the distribution of the quantum measurement and control data is not in accordance with a functional relation;
and the second processing module is used for carrying out function fitting noise reduction processing on the quantum measurement and control data according to a function model corresponding to the function relation under the condition that the distribution of the quantum measurement and control data is judged to accord with the function relation.
10. A storage medium having a computer program stored therein, wherein the computer program is arranged to perform the method of any of claims 1 to 8 when run.
11. An electronic device comprising a memory and a processor, characterized in that the memory has stored therein a computer program, the processor being arranged to run the computer program to perform the method of any of the claims 1 to 8.
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