Cold atomic group parameter automatic calibration simulation system and method based on artificial intelligence

Abstract

The invention discloses a cold atomic group parameter automatic calibration simulation system and method based on artificial intelligence, and belongs to the field of artificial intelligence. Comprising the following steps: constructing a cold atomic group database, extracting historical data of a calibrated cold atomic group image, constructing a cold atomic group standard set, and calculating an average pixel value of all cold atomic groups in the cold atomic group standard set; extracting an initial image of the cold atomic group shape set, calculating a center coordinate of a to-be-detected sample, constructing a cold atomic group similar model, marking the to-be-detected sample as a cold atomic group when the maximum similarity between the to-be-detected sample and the cold atomic group in the cold atomic group standard set is greater than or equal to a threshold value, and calibrating the number of the cold atomic groups; based on the cold atomic group image data, the average speed of the cold atomic group is calculated, and the temperature of the cold atomic group is calibrated; the automatic calibration of the cold atomic group parameters is realized, the accuracy of cold atomic group parameter detection is improved, and the experiment time is greatly saved.

Description

Technical Field

[0001] The present invention relates to the field of artificial intelligence technology, and in particular to an artificial intelligence-based cold atom group parameter automatic calibration simulation system and method. Background Art

[0002] A cold atom cluster refers to an atomic aggregate whose temperature is cooled to an extremely low level by significantly reducing the speed of atoms or molecules through a series of physical means under specific conditions. In the prior art, the calibration of cold atom cluster parameters usually relies on the experience of experimenters to manually calibrate the position of cold atom clusters in images. The lack of automation and intelligent means not only greatly prolongs the experimental time, but also may reduce the accuracy of the calibration. With the development of artificial intelligence technology, it can provide powerful data processing capabilities and algorithm optimization capabilities in cold atom cluster detection experiments. Based on artificial intelligence technology, how to save experimental time and improve the accuracy of calibration in cold atom cluster detection experiments has become a problem we need to study. Summary of the invention

[0003] The purpose of the present invention is to provide an artificial intelligence-based cold atom group parameter automatic calibration simulation system and method to solve the problems raised in the above background technology.

[0004] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0005] The method for automatic calibration of cold atom group parameters based on artificial intelligence comprises the following steps:

[0006] Step S1: constructing a cold atom cluster database, wherein the cold atom cluster database records cold atom cluster image data and cold atom cluster structure data;

[0007] Step S2: extracting historical data of the calibrated cold atom cluster image, constructing a standard set of cold atom clusters, and calculating the average pixel value of all cold atom clusters in the standard set of cold atom clusters;

[0008] Step S3: extracting the initial image of the cold atom cluster shape set, calculating the center coordinates of the sample to be tested, constructing a cold atom cluster similarity model, and when the maximum similarity between the sample to be tested and the cold atom clusters in the cold atom cluster specification set is greater than or equal to a threshold, marking the sample to be tested as a cold atom cluster, and calibrating the number of cold atom clusters;

[0009] Step S4: Based on the cold atom cluster image data, the average velocity of the cold atom cluster is calculated, and the temperature of the cold atom cluster is calibrated.

[0010] Furthermore, the specific implementation process of step S1 includes:

[0011] Step S1.1: The image sensor collects images of the cold atom cluster from the direction parallel to the laser and the direction perpendicular to the laser to generate a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time;

[0012] Since the movement direction of the cold atom cluster is non-directional, an image sensor is required to collect the movement of the cold atom cluster at different perspectives; the cold atom cluster is calibrated through the front image of the cold atom cluster. When the specific position of the cold atom cluster is calibrated, the movement of the cold atom cluster at the laser emission perspective per unit time is judged through the image data of the cold atom cluster in the direction parallel to the laser; the movement of the cold atom cluster at the vertical perspective of the laser is judged through the image data of the cold atom cluster in the direction vertical to the laser, thereby ensuring the accuracy of the acquired cold atom cluster speed.

[0013] Step S1.2: Construct a cold cluster database for storing cold cluster image data and cold cluster structure data, wherein the cold cluster image data includes a cold cluster shape set, a cold cluster motion image set, pixel values ​​and pixel coordinates, and the cold cluster structure data includes the circumference and area of ​​the cold cluster.

[0014] Furthermore, the specific implementation process of step S2 includes:

[0015] Step S2.1: Extract the historical data of the calibrated cold atom cluster image and construct the cold atom cluster standard set GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom group in the cold atom group gauge set, M represents the total number of cold atom groups in the cold atom group gauge set;

[0016] Step S2.2: Based on the cold atom cluster standard set, calculate the average pixel value of all cold atom clusters in the cold atom cluster standard set: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

[0017] Through the historical calibration of cold atom clusters, the shape characteristics of the cold atom clusters are obtained, thereby obtaining standard cold atom clusters and constructing a standard set of cold atom clusters; since the pixels of standard cold atom cluster images are highly similar, the average pixel value of the cold atom cluster can be calculated based on the pixels of all standard cold atom clusters, thereby calibrating the cold atom clusters more accurately.

[0018] Furthermore, the specific implementation process of step S3 includes:

[0019] Step S3.1: extracting the initial image ga1 of the cold atom cluster shape set, and dividing the initial image ga1 into sub-regions that overlap each other and have the same size;

[0020] Cold atom clusters are not fixed. The center coordinates of cold atom clusters in images at different time points are different. Therefore, only the initial image is extracted to calibrate the cold atom clusters. In order to avoid the cold atom clusters being cut when the image is cut, resulting in a reduction in the number of identified cold atom clusters and inaccurate number calibration of cold atom clusters, the initial image needs to be divided into overlapping sub-regions of the same size.

[0021] Step S3.2: When the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of 0 cluster is recorded as the sample to be tested, and the area S and perimeter L of the sample to be tested are extracted; the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested;

[0022] Step S3.3: Compare the sample to be tested with the cold atomic groups in the cold atomic group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the area of ​​the mth cold atom cluster in the canonical set of cold atom clusters;

[0023] Construct a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set;

[0024] The characteristics of cold atomic clusters are not only consistent but also independent. Therefore, it is necessary to compare the sample to be tested with all cold atomic clusters in the cold atomic cluster standard set, find the cold atomic cluster with the most similar characteristics, and compare the similarity and threshold with the cold atomic cluster to avoid missing the cold atomic clusters in the image.

[0025] Step S3.4: When the SMA is greater than or equal to the threshold, the sample to be tested is marked as a cold atomic cluster; the center coordinates of the cold atomic cluster are recorded, and the total number of the center coordinates of all cold atomic clusters is counted and recorded as the number of cold atomic clusters.

[0026] Furthermore, the specific implementation process of step S4 includes:

[0027] Step S4.1: Track the cold atom cluster and obtain the motion velocity v of the cold atom cluster in the direction parallel to the laser through the cold atom cluster shape set. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster;

[0028] The center coordinates of the cold atom cluster are the position coordinates of the cold atom cluster. The position coordinates of the cold atom cluster can be used to track the cold atom cluster and obtain its moving distance. The movement of the cold atom cluster can be obtained by the acquisition frequency per unit time, that is, the inverse of the total number of images acquired per unit time, and the total number of images acquired per unit time is not zero.

[0029] Step S4.2: Calibrate the temperature of the cold atomic group: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

[0030] The artificial intelligence-based cold atom group parameter automatic calibration simulation system includes: an acquisition storage module, a standard data module, a numerical calibration module and a temperature calibration module;

[0031] The acquisition and storage module includes an acquisition unit and a storage unit, which are used to construct a cold radical database;

[0032] The standard data module is used to construct a standard set of cold atomic groups and calculate the average pixel value of all cold atomic groups in the standard set of cold atomic groups;

[0033] The number calibration module includes a coordinate unit, a similarity unit and a statistical unit, and constructs a cold atom cluster similarity model by calculating the center coordinates of the sample to be tested, and calibrates the number of cold atom clusters;

[0034] The temperature calibration module includes a speed unit and a calibration unit, and calibrates the temperature of the cold atomic clusters by calculating the average speed of the cold atomic clusters.

[0035] Furthermore, the acquisition and storage module includes an acquisition unit and a storage unit;

[0036] The acquisition unit acquires images of the cold atom clusters from the direction parallel to the laser and the direction perpendicular to the laser through an image sensor to generate a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time;

[0037] The storage unit constructs a cold cluster database for storing cold cluster image data and cold cluster structure data. The cold cluster image data includes a cold cluster shape set, a cold cluster motion image set, pixel values ​​and pixel coordinates. The cold cluster structure data includes the perimeter and area of ​​the cold cluster.

[0038] Furthermore, the standard data module constructs a standard set of cold atom clusters GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom cluster in the cold atom cluster standard set, and M represents the total number of cold atom clusters in the cold atom cluster standard set; based on the cold atom cluster standard set, the average pixel value of all cold atom clusters in the cold atom cluster standard set is calculated: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

[0039] Further, the digital positioning module includes a coordinate unit, a similarity unit and a statistical unit;

[0040] The coordinate unit extracts the initial image ga1 of the cold atom cluster shape set, divides the initial image ga1 into sub-regions that overlap each other and have the same size; when the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of the 0 cluster is recorded as a sample to be tested, and the area S and the perimeter L of the sample to be tested are extracted; and the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested;

[0041] The similarity unit compares the sample to be tested with the cold atomic groups in the cold atomic group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. Represents the area of ​​the mth cold atom cluster in the cold atom cluster canonical set; constructs a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m ) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set;

[0042] The statistical unit, when the SMA is greater than or equal to the threshold, marks the sample to be tested as a cold atomic cluster; records the center coordinates of the cold atomic clusters, and counts the total number of the center coordinates of all cold atomic clusters, which is recorded as the number of cold atomic clusters.

[0043] Further, the temperature calibration module includes a speed unit and a calibration unit;

[0044] The speed unit tracks the cold atom cluster and obtains the movement speed v of the cold atom cluster in the direction parallel to the laser through the cold atom cluster shape set. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster;

[0045] The calibration unit calibrates the temperature of the cold atomic group: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

[0046] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in the artificial intelligence-based cold atom cluster parameter automatic calibration simulation system and method provided by the present invention, a cold atom cluster database is constructed; historical data of calibrated cold atom cluster images are extracted, a cold atom cluster standard set is constructed, and the average pixel value of all cold atom clusters in the cold atom cluster standard set is calculated; the initial image of the cold atom cluster shape set is extracted, the center coordinates of the sample to be tested are calculated, and a cold atom cluster similarity model is constructed. When the maximum similarity between the sample to be tested and the cold atom clusters in the cold atom cluster standard set is greater than or equal to a threshold, the sample to be tested is marked as a cold atom cluster, and the number of cold atom clusters is calibrated; based on the cold atom cluster image data, the average speed of the cold atom clusters is calculated, and the temperature of the cold atom clusters is calibrated; not only the automatic calibration of the cold atom cluster parameters is realized, but also the accuracy of the cold atom cluster parameter detection is improved, which greatly saves the experimental time. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0048] Figure 1 It is a structural schematic diagram of the artificial intelligence-based cold atom group parameter automatic calibration simulation system of the present invention;

[0049] Figure 2 It is a schematic diagram of the steps of the artificial intelligence-based cold atom group parameter automatic calibration simulation method of the present invention;

[0050] Figure 3 It is a pixel marking schematic diagram of the artificial intelligence-based cold atom group parameter automatic calibration simulation method of the present invention. DETAILED DESCRIPTION

[0051] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0052] See also Figure 1-Figure 3 , the present invention provides a technical solution:

[0053] The method for automatic calibration of cold atom group parameters based on artificial intelligence comprises the following steps:

[0054] Step S1: constructing a cold atom cluster database, which records cold atom cluster image data and cold atom cluster structure data;

[0055] Step S2: extracting historical data of the calibrated cold atom cluster image, constructing a standard set of cold atom clusters, and calculating the average pixel value of all cold atom clusters in the standard set of cold atom clusters;

[0056] Step S3: extracting the initial image of the cold atom cluster shape set, calculating the center coordinates of the sample to be tested, constructing a cold atom cluster similarity model, and when the maximum similarity between the sample to be tested and the cold atom clusters in the cold atom cluster specification set is greater than or equal to a threshold, marking the sample to be tested as a cold atom cluster, and calibrating the number of cold atom clusters;

[0057] Step S4: Based on the cold atom cluster image data, the average velocity of the cold atom cluster is calculated, and the temperature of the cold atom cluster is calibrated.

[0058] Specifically, the specific implementation process of step S1 includes:

[0059] Step S1.1: The image sensor collects images of the cold atom cluster from the direction parallel to the laser and the direction perpendicular to the laser to generate a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time;

[0060] Step S1.2: Construct a cold cluster database for storing cold cluster image data and cold cluster structure data. The cold cluster image data includes a cold cluster shape set, a cold cluster motion image set, pixel values ​​and pixel coordinates. The cold cluster structure data includes the circumference and area of ​​the cold cluster.

[0061] Specifically, the specific implementation process of step S2 includes:

[0062] Step S2.1: Extract the historical data of the calibrated cold atom cluster image and construct the cold atom cluster standard set GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom group in the cold atom group gauge set, M represents the total number of cold atom groups in the cold atom group gauge set;

[0063] Step S2.2: Based on the cold atom cluster standard set, calculate the average pixel value of all cold atom clusters in the cold atom cluster standard set: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

[0064] For example: M=6, GB={gb1, gb2, gb3, gb4, gb5, gb6}, FAV(gb1)=168, FAV(gb2)=168, FAV(gb3)=167, FAV(gb1)=169, FAV(gb1)=170, FAV(gb1)=166, then the average pixel value MSN of all cold atom clusters in the cold atom cluster standard set=(168+168+167+169+170+166) / 6=168.

[0065] Specifically, the specific implementation process of step S3 includes:

[0066] Step S3.1: extracting the initial image ga1 of the cold atom cluster shape set, and dividing the initial image ga1 into sub-regions that overlap each other and have the same size;

[0067] Step S3.2: When the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of 0 cluster is recorded as the sample to be tested, and the area S and perimeter L of the sample to be tested are extracted; the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested;

[0068] like Figure 3 , O represents 1, P represents 0, among which the space is 0, the area occupied by 0 in the statistical contour is the area of ​​the sample to be tested, and the length of the statistical contour of the sample to be tested is the perimeter of the sample to be tested: Lgb1=12, Sgb1=7; Lgb2=14, Sgb2=7; Lgb3=4, Sgb3=1; Lgb4=4, Sgb4=1; Lgb5=8, Sgb5=4; Lgb6=10, Sgb6=6.

[0069] Step S3.3: Compare the sample to be tested with the cold atomic groups in the cold atomic group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the area of ​​the mth cold atom cluster in the canonical set of cold atom clusters;

[0070] Construct a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m ) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set;

[0071] Step S3.4: When the SMA is greater than or equal to the threshold, the sample to be tested is marked as a cold atomic cluster; the center coordinates of the cold atomic cluster are recorded, and the total number of the center coordinates of all cold atomic clusters is counted and recorded as the number of cold atomic clusters.

[0072] Specifically, the specific implementation process of step S4 includes:

[0073] Step S4.1: Track the cold atom cluster and obtain the motion velocity v of the cold atom cluster in the direction parallel to the laser through the cold atom cluster shape set. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster;

[0074] Step S4.2: Calibrate the temperature of the cold atomic group: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

[0075] The artificial intelligence-based cold atom group parameter automatic calibration simulation system includes: an acquisition storage module, a standard data module, a numerical calibration module and a temperature calibration module;

[0076] The acquisition and storage module includes an acquisition unit and a storage unit, and is used to construct a cold atomic group database;

[0077] A standard data module, used to construct a standard set of cold atomic clusters and calculate the average pixel value of all cold atomic clusters in the standard set of cold atomic clusters;

[0078] The number calibration module includes a coordinate unit, a similarity unit and a statistical unit. By calculating the center coordinates of the sample to be tested, a similarity model of the cold atom cluster is constructed to calibrate the number of the cold atom clusters.

[0079] The temperature calibration module includes a speed unit and a calibration unit, and calibrates the temperature of the cold atomic clusters by calculating the average speed of the cold atomic clusters.

[0080] Preferably, the acquisition and storage module includes an acquisition unit and a storage unit;

[0081] The acquisition unit acquires images of the cold atom cluster from the direction parallel to the laser and the direction perpendicular to the laser through the image sensor, and generates a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time;

[0082] A storage unit constructs a cold atom cluster database for storing cold atom cluster image data and cold atom cluster structure data. The cold atom cluster image data includes a cold atom cluster shape set, a cold atom cluster motion image set, pixel values ​​and pixel coordinates. The cold atom cluster structure data includes the perimeter and area of ​​the cold atom cluster.

[0083] Preferably, the standard data module extracts historical data of the calibrated cold atom cluster image to construct a cold atom cluster standard set GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom cluster in the cold atom cluster standard set, and M represents the total number of cold atom clusters in the cold atom cluster standard set; based on the cold atom cluster standard set, the average pixel value of all cold atom clusters in the cold atom cluster standard set is calculated: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

[0084] Preferably, the digital positioning module includes a coordinate unit, a similarity unit and a statistical unit;

[0085] Coordinate unit, by extracting the initial image ga1 of the cold atom cluster shape set, the initial image ga1 is divided into overlapping sub-regions of the same size; when the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of 0 aggregation is recorded as the sample to be tested, and the area S and perimeter L of the sample to be tested are extracted; the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested;

[0086] Similarity unit, compares the sample to be tested with the cold atom groups in the cold atom group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. Represents the area of ​​the mth cold atom cluster in the cold atom cluster canonical set; constructs a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m ) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set;

[0087] The statistical unit marks the sample to be tested as a cold atom cluster when the SMA is greater than or equal to the threshold value; records the center coordinates of the cold atom cluster, and counts the total number of the center coordinates of all the cold atom clusters, which is recorded as the number of cold atom clusters.

[0088] Preferably, the temperature calibration module includes a speed unit and a calibration unit;

[0089] The velocity unit tracks the cold atom cluster and obtains the velocity v of the cold atom cluster in the direction parallel to the laser through the shape set of the cold atom cluster. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster;

[0090] Calibration unit, calibrates the temperature of cold atomic groups: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

[0091] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0092] Finally, it should be noted that the above is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An artificial intelligence-based cold atom group parameter automatic calibration simulation method, characterized in that: The method comprises the following steps: Step S1: constructing a cold atom cluster database, wherein the cold atom cluster database records cold atom cluster image data and cold atom cluster structure data; Step S2: extracting historical data of the calibrated cold atom cluster image, constructing a standard set of cold atom clusters, and calculating the average pixel value of all cold atom clusters in the standard set of cold atom clusters; Step S3: extracting the initial image of the cold atom cluster shape set, calculating the center coordinates of the sample to be tested, constructing a cold atom cluster similarity model, and when the maximum similarity between the sample to be tested and the cold atom clusters in the cold atom cluster specification set is greater than or equal to a threshold, marking the sample to be tested as a cold atom cluster, and calibrating the number of cold atom clusters; Step S4: Based on the cold atom cluster image data, the average velocity of the cold atom cluster is calculated, and the temperature of the cold atom cluster is calibrated.

2. The artificial intelligence-based cold atom group parameter automatic calibration simulation method according to claim 1, characterized in that: The specific implementation process of step S1 includes: Step S1.1: The image sensor collects images of the cold atom cluster from the direction parallel to the laser and the direction perpendicular to the laser to generate a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time; Step S1.2: Construct a cold cluster database for storing cold cluster image data and cold cluster structure data, wherein the cold cluster image data includes a cold cluster shape set, a cold cluster motion image set, pixel values ​​and pixel coordinates, and the cold cluster structure data includes the circumference and area of ​​the cold cluster.

3. The artificial intelligence-based cold atom group parameter automatic calibration simulation method according to claim 2, characterized in that: The specific implementation process of step S2 includes: Step S2.1: Extract the historical data of the calibrated cold atom cluster image and construct the cold atom cluster standard set GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom group in the cold atom group gauge set, M represents the total number of cold atom groups in the cold atom group gauge set; Step S2.2: Based on the cold atom cluster standard set, calculate the average pixel value of all cold atom clusters in the cold atom cluster standard set: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

4. The artificial intelligence-based cold atom group parameter automatic calibration simulation method according to claim 3 is characterized in that: The specific implementation process of step S3 includes: Step S3.1: extracting the initial image ga1 of the cold atom cluster shape set, and dividing the initial image ga1 into sub-regions that overlap each other and have the same size; Step S3.2: When the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of 0 cluster is recorded as the sample to be tested, and the area S and perimeter L of the sample to be tested are extracted; the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested; Step S3.3: Compare the sample to be tested with the cold atomic groups in the cold atomic group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the area of ​​the mth cold atom cluster in the canonical set of cold atom clusters; Construct a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m ) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set; Step S3.4: When the SMA is greater than or equal to the threshold, the sample to be tested is marked as a cold atomic cluster; the center coordinates of the cold atomic cluster are recorded, and the total number of the center coordinates of all cold atomic clusters is counted and recorded as the number of cold atomic clusters.

5. The artificial intelligence-based cold atom group parameter automatic calibration simulation method according to claim 4 is characterized in that: The specific implementation process of step S4 includes: Step S4.1: Track the cold atom cluster and obtain the motion velocity v of the cold atom cluster in the direction parallel to the laser through the cold atom cluster shape set. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster; Step S4.2: Calibrate the temperature of the cold atomic group: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

6. The artificial intelligence-based cold atom group parameter automatic calibration simulation system is characterized by: The system includes: an acquisition and storage module, a standard data module, a digital calibration module and a temperature calibration module; The acquisition and storage module includes an acquisition unit and a storage unit, which are used to construct a cold radical database; The standard data module is used to construct a standard set of cold atomic groups and calculate the average pixel value of all cold atomic groups in the standard set of cold atomic groups; The number calibration module includes a coordinate unit, a similarity unit and a statistical unit, and constructs a cold atom cluster similarity model by calculating the center coordinates of the sample to be tested, and calibrates the number of cold atom clusters; The temperature calibration module includes a speed unit and a calibration unit, and calibrates the temperature of the cold atomic clusters by calculating the average speed of the cold atomic clusters.

7. The artificial intelligence-based cold radical parameter automatic calibration simulation system according to claim 6, characterized in that: The acquisition and storage module includes an acquisition unit and a storage unit; The acquisition unit acquires images of the cold atom clusters from the direction parallel to the laser and the direction perpendicular to the laser through an image sensor to generate a cold atom cluster shape set GA = {ga i |i∈[1,I]} and the cold atom cluster motion image set S={s j |j∈[1,J]}, where g i represents the i-th laser parallel direction image data collected per unit time, I represents the total number of laser parallel direction image data collected per unit time, and s j represents the i-th laser vertical image data collected in a unit time, and J represents the total number of laser vertical image data collected in a unit time; The storage unit constructs a cold cluster database for storing cold cluster image data and cold cluster structure data. The cold cluster image data includes a cold cluster shape set, a cold cluster motion image set, pixel values ​​and pixel coordinates. The cold cluster structure data includes the perimeter and area of ​​the cold cluster.

8. The artificial intelligence-based cold radical parameter automatic calibration simulation system according to claim 7, characterized in that: The standard data module extracts the historical data of the calibrated cold atom cluster image to construct the cold atom cluster standard set GB = {gb m |m∈[1,M]}, where gb m represents the mth cold atom cluster in the cold atom cluster standard set, and M represents the total number of cold atom clusters in the cold atom cluster standard set; based on the cold atom cluster standard set, the average pixel value of all cold atom clusters in the cold atom cluster standard set is calculated: Among them, FAV (gb m ) represents the average pixel value of the mth cold atom cluster in the cold atom cluster standard set, and MSN represents the average pixel value of all cold atom clusters in the cold atom cluster standard set.

9. The artificial intelligence-based cold radical parameter automatic calibration simulation system according to claim 8, characterized in that: The digital positioning module includes a coordinate unit, a similarity unit and a statistical unit; The coordinate unit extracts the initial image ga1 of the cold atom cluster shape set, divides the initial image ga1 into sub-regions that overlap each other and have the same size; when the pixel value in the sub-region is greater than the average pixel value of all cold atom clusters in the cold atom cluster standard set, the pixel value is marked as 0; otherwise, the pixel value is marked as P; the image of the 0 cluster is recorded as a sample to be tested, and the area S and the perimeter L of the sample to be tested are extracted; and the center coordinates (x, y) of the cold atom cluster to be tested are calculated: Among them, x h represents the horizontal coordinate of the hth pixel in the sample to be tested, H represents the total number of pixels in the sample to be tested, and y h Represents the ordinate of the hth pixel in the sample to be tested; The similarity unit compares the sample to be tested with the cold atomic groups in the cold atomic group specification set: Among them, smaL|gb m It represents the similarity of the perimeter between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. represents the perimeter of the mth cold atom cluster in the cold atom cluster gauge set, It represents the area similarity between the sample to be tested and the mth cold atom cluster in the cold atom cluster standard set. Represents the area of ​​the mth cold atom cluster in the cold atom cluster canonical set; constructs a similar model of cold atom clusters: SMA=max{SMA(gb m )|m∈[1,M]}, where w1 and w2 represent the preset weight factors, and w3 represents the preset error factor; SMA(gb m ) represents the weighted similarity between the sample to be tested and the mth cold atom group in the cold atom group standard set; SMA represents the maximum similarity between the sample to be tested and the cold atom group in the cold atom group standard set; The statistical unit, when the SMA is greater than or equal to the threshold, marks the sample to be tested as a cold atomic cluster; records the center coordinates of the cold atomic clusters, and counts the total number of the center coordinates of all cold atomic clusters, which is recorded as the number of cold atomic clusters.

10. The artificial intelligence-based cold radical parameter automatic calibration simulation system according to claim 9, characterized in that: The temperature calibration module includes a speed unit and a calibration unit; The speed unit tracks the cold atom cluster and obtains the movement speed v of the cold atom cluster in the direction parallel to the laser through the cold atom cluster shape set. 1d , the velocity v of the cold atom cluster in the vertical direction of the laser is obtained through the cold atom cluster motion image set 2d , calculate the average velocity of the cold atom cluster Where D represents the number of cold atomic groups, represents the velocity of the dth cold atomic cluster; The calibration unit calibrates the temperature of the cold atomic group: Among them, k is the Boltzmann constant, m is the mass of the atom, and T represents the temperature of the cold atomic cluster.

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