Simulation control system and method for cold atomic group detection based on virtual reality

Abstract

The invention discloses a simulation control system and method for cold atomic group detection based on virtual reality, and belongs to the field of simulation control. According to the method, an experimental equipment work log and cold atomic group data corresponding to the experimental equipment work log in a cold atomic group detection experiment are extracted, and a cold atomic group detection experiment database is constructed; according to the types of the cold atomic groups, constructing a cold atomic group type set; constructing a parameter model of the cold atomic group based on the cold atomic group detection experiment database; acquiring real-time cold atomic group characteristic data, real-time laser parameters and real-time magnetic field parameters in a virtual reality experiment, and calculating an evaluation value of the real-time laser parameters; an experimenter is assisted in finding optimal laser parameters and magnetic field parameters through a parameter model of a cold atomic group; therefore, the accuracy of cold atomic group detection is improved, the use of experimental equipment and consumables is reduced, and the experimental cost is reduced.

Description

Technical Field

[0001] The present invention relates to the field of simulation control technology, and in particular to a simulation control system and method for cold atom group detection based on virtual reality. Background Art

[0002] Virtual reality is a technology that uses computer graphics, sensor technology, and real-time computing to generate an interactive three-dimensional environment through computer simulation. It is widely used in many fields due to its highly immersive and interactive characteristics. The application of virtual reality in cold cluster detection can simulate and control the various characteristics of the detected cold clusters, but the experimental control method usually relies on the experience of the experimenter for manual adjustment, lacks automation and intelligent means, and it is difficult to achieve real-time and accurate optimization of the experimental equipment parameters for cold cluster detection. Especially under complex experimental conditions, the physical limitations of the experimental equipment make some parameters difficult to obtain, affecting the overall effectiveness of the experiment. Therefore, how to improve the accuracy of cold cluster detection through virtual reality technology has become a problem we need to solve. Summary of the invention

[0003] The purpose of the present invention is to provide a simulation control system and method for cold atom group detection based on virtual reality 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] A simulation control method for cold atom group detection based on virtual reality, the method comprising the following steps:

[0006] Step S1: extracting the experimental equipment work log and the cold atom group data corresponding to the experimental equipment work log in the cold atom group detection experiment, and constructing a cold atom group detection experiment database; constructing a cold atom group type set according to the types of cold atom groups;

[0007] Step S2: constructing a parameter model of cold atom clusters based on the cold atom cluster detection experimental database;

[0008] Step S3: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameters; assist the experimenter in finding the optimal laser parameters and magnetic field parameters through the parameter model of the cold atom cluster.

[0009] Furthermore, the specific implementation process of step S1 includes:

[0010] Step S1.1: extract the experimental equipment work log in the cold atom cluster detection experiment and the cold atom cluster data corresponding to the experimental equipment work log, and construct a cold atom cluster detection experiment database; the experimental equipment work log records the laser parameters and magnetic field parameters, the laser parameters include the laser frequency value and the light intensity value, and the magnetic field parameters are the magnetic field intensity value; the cold atom cluster data include cold atom cluster parameters and cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of the cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of the cold atom clusters;

[0011] Step S1.2: According to the types of cold atomic groups, construct a cold atomic group type set: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

[0012] It should be noted that cold atomic clusters can contain many different types of atoms: sodium, potassium, rubidium, cesium, strontium, calcium, helium, neon, argon, etc.; the cold atomic clusters required for the experiment are formed through various technical means, so it is necessary to classify the cold atomic clusters and analyze them specifically to improve the accuracy of the experiment.

[0013] Furthermore, the specific implementation process of step S2 includes:

[0014] Step S2.1: Construct cold atom cluster s based on the cold atom cluster detection experimental database i Parameter model: M = α 1 p 1 +α 2 G+α 3 p 3 +β 1 , T = α 4 p 1 +α 5 e -G +α 6 p 3 +β 2 , where M represents the cold atomic group s i The number of 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 represents the model coefficient, G represents the light intensity value, p 1 、p 3 They represent the detuning effect index of the laser frequency value and the magnetic field intensity value respectively; T represents the cold atomic cluster s iTemperature;

[0015] Detuning effect index of laser frequency value: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value of

[0016] Magnetic field strength value influence index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i The preset critical value of the magnetic field strength value in the detection experiment;

[0017] Step S2.2: Continuously update the model coefficient α 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 , until the optimal model coefficients are found:

[0018] Extracting cold radicals i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data;

[0019] Calculate cold clusters i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' n Represents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual value of temperature;

[0020] The model coefficients are continuously updated until the cold cluster s i The predicted value of the number of cold atom clusters s i When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

[0021] It should be noted that the number of cold atoms increases linearly with the increase of the intensity of the cooling laser; this is because a stronger laser can provide a greater radiation pressure, thereby more effectively slowing down the speed of atoms, allowing more atoms to be cooled and trapped in the magneto-optical trap; and as the intensity of the cooling laser increases, the temperature of the cold atom cluster will increase; the number of cold atoms also depends on the frequency detuning of the cooling laser, that is, the difference between the laser frequency value and the atomic transition frequency. The appropriate detuning amount can optimize the cooling effect, allowing more atoms to be cooled to a sufficiently low temperature and captured; the frequency detuning of the cooling laser also has an important influence on the temperature of the cold atom cluster. When there is an appropriate detuning between the laser frequency value and the atomic transition frequency, a more efficient cooling effect can be achieved, thereby reducing the temperature of the cold atom cluster; a moderate magnetic field size can optimize the cooling effect and reduce the temperature of the cold atom cluster, but if the magnetic field is too large or too small, it may cause the cooling effect to weaken or fail; the magnetic field gradient has a significant effect on the number of cold atoms. In the magneto-optical trap, increasing the magnetic field gradient can more effectively cool and trap atoms, thereby increasing the number of cold atoms.

[0022] Furthermore, the specific implementation process of step S3 includes:

[0023] Step S3.1: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameter: h = |fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, issue an early warning and prompt the experimenter to change the laser frequency value; otherwise, predict the cold atom cluster parameters;

[0024] It should be noted that different types of cold atom clusters have different transition frequencies. In the cold atom cluster detection experiment, the laser frequency value of the experimental equipment needs to match or be close to resonance with the transition frequency of the cold atom cluster. The setting of the laser frequency value is the first step in the detection experiment. Therefore, it is necessary to evaluate the setting of the laser frequency value to save the experimental time of the experimenters and realize the efficiency of the experiment.

[0025] Step S3.2: Based on the real-time cold cluster characteristic data, extract the corresponding cold cluster parameter model, obtain the cold cluster parameter prediction value, and assist the experimenter in finding the optimal laser parameters and magnetic field parameters.

[0026] A simulation control system for cold atom group detection based on virtual reality, the system includes: a data acquisition module, a model building module and an early warning module;

[0027] The data acquisition module includes a storage unit and a classification unit, and constructs a cold atom group detection experiment database by extracting the experimental equipment work log in the cold atom group detection experiment and the cold atom group data corresponding to the experimental equipment work log; constructs a cold atom group type set according to the types of cold atom groups;

[0028] The model building module includes a model unit and an update unit, which are used to build a parameter model of the cold atomic group;

[0029] The early warning module includes an evaluation unit and a query unit, which obtains real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, calculates the evaluation value of the real-time laser parameters; and assists experimenters in finding the optimal laser parameters and magnetic field parameters through the parameter model of the cold atom cluster.

[0030] Furthermore, the data acquisition module includes a storage unit and a classification unit:

[0031] The storage unit constructs a cold atom cluster detection experiment database by extracting the experimental equipment work log in the cold atom cluster detection experiment and the cold atom cluster data corresponding to the experimental equipment work log; the experimental equipment work log records the laser parameters and the magnetic field parameters, the laser parameters include the laser frequency value and the light intensity value, and the magnetic field parameters are the magnetic field intensity value; the cold atom cluster data include the cold atom cluster parameters and the cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of the cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of the cold atom clusters;

[0032] The classification unit constructs a cold atom group type set according to the type of cold atom group: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

[0033] Further, the model building module includes a model unit and an update unit;

[0034] The model unit constructs a cold atom cluster s based on the cold atom cluster detection experimental database. i Parameter model: M = α 1 p 1 +α 2 G+α 3 p 3 +β 1 , T = α 4 p 1 +α 5 e -G +α 6 p 3 +β 2 , where M represents the cold atomic group s i The number of 1 , α 2 , α 3 , α 4 , α 5 , α6 , β 1 , β 2 represents the model coefficient, G represents the light intensity value, p 1 、p 3 They represent the detuning effect index of the laser frequency value and the magnetic field intensity value respectively; T represents the cold atomic cluster s i The temperature of the laser frequency value; the detuning amount influences the index: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value; the magnetic field strength value affects the index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i Preset critical value of magnetic field strength in detection experiment; continuously update model coefficient α 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 , until the optimal model coefficients are found;

[0035] The updating unit extracts cold atomic groups s i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data; the cold atom cluster s is calculated. i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' n Represents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual temperature value of the cold atom cluster s i The predicted value of the number of cold atom clusters s i When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

[0036] Further, the early warning module includes an evaluation unit and a query unit;

[0037] The evaluation unit obtains the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculates the evaluation value of the real-time laser parameter: h=|fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, an early warning is issued, and the experimenter is prompted to change the laser frequency value; otherwise, the cold atom cluster parameters are predicted;

[0038] The query unit extracts the parameter model of the corresponding cold atom cluster based on the real-time cold atom cluster characteristic data, obtains the predicted value of the cold atom cluster parameters, and assists the experimenter in finding the optimal laser parameters and magnetic field parameters.

[0039] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: in the simulation control system and method for cold cluster detection based on virtual reality provided by the present invention, a cold cluster detection experiment database is constructed by extracting the experimental equipment work log in the cold cluster detection experiment and the cold cluster data corresponding to the experimental equipment work log; a cold cluster type set is constructed according to the types of cold clusters; a parameter model of cold clusters is constructed based on the cold cluster detection experiment database; real-time cold cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment are obtained, and the evaluation value of the real-time laser parameters is calculated; the parameter model of the cold cluster is used to assist the experimenter in finding the optimal laser parameters and magnetic field parameters; thereby improving the accuracy of cold cluster detection while reducing the use of experimental equipment and consumables and reducing the experimental cost. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] 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:

[0041] Figure 1 It is a structural schematic diagram of a simulation control system for cold atom group detection based on virtual reality of the present invention;

[0042] Figure 2 It is a schematic diagram of the steps of the simulation control method for cold atom group detection based on virtual reality of the present invention. DETAILED DESCRIPTION

[0043] 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.

[0044] See also Figure 1-Figure 2 , the present invention provides a technical solution:

[0045] A simulation control method for cold atom group detection based on virtual reality, the method comprising the following steps:

[0046] Step S1: extracting the experimental equipment work log and the cold atom group data corresponding to the experimental equipment work log in the cold atom group detection experiment, and constructing a cold atom group detection experiment database; constructing a cold atom group type set according to the types of cold atom groups;

[0047] Step S2: constructing a parameter model of cold atom clusters based on the cold atom cluster detection experimental database;

[0048] Step S3: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameters; assist the experimenter in finding the optimal laser parameters and magnetic field parameters through the parameter model of the cold atom cluster.

[0049] Specifically, the specific implementation process of step S1 includes:

[0050] Step S1.1: extract the experimental equipment work log in the cold atom cluster detection experiment and the cold atom cluster data corresponding to the experimental equipment work log, and construct a cold atom cluster detection experiment database; the experimental equipment work log records the laser parameters and magnetic field parameters, the laser parameters include the laser frequency value and the light intensity value, and the magnetic field parameters are the magnetic field intensity value; the cold atom cluster data include the cold atom cluster parameters and the cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of the cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of the cold atom clusters;

[0051] Step S1.2: According to the types of cold atomic groups, construct a cold atomic group type set: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

[0052] Specifically, the specific implementation process of step S2 includes:

[0053] Step S2.1: Construct cold atom cluster s based on the cold atom cluster detection experimental database i Parameter model: M = α 1 p 1 +α 2 G+α 3 p 3 +β 1 , T = α 4 p 1 +α 5 e -G+α 6 p 3 +β 2 , where M represents the cold atomic group s i The number of 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 represents the model coefficient, G represents the light intensity value, p 1 、p 3 They represent the detuning effect index of the laser frequency value and the magnetic field intensity value respectively; T represents the cold atomic cluster s i Temperature;

[0054] Detuning effect index of laser frequency value: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value of

[0055] Magnetic field strength value influence index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i The preset critical value of the magnetic field strength value in the detection experiment;

[0056] Step S2.2: Continuously update the model coefficient α 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 , until the optimal model coefficients are found:

[0057] Extracting cold radicals i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data;

[0058] Calculate cold clusters i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' nRepresents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual value of temperature;

[0059] The model coefficients are continuously updated until the cold cluster s i The predicted value of the number of cold atom clusters s i When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

[0060] Specifically, the specific implementation process of step S3 includes:

[0061] Step S3.1: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameter: h = |fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, issue an early warning and prompt the experimenter to change the laser frequency value; otherwise, predict the cold atom cluster parameters;

[0062] Step S3.2: Based on the real-time cold cluster characteristic data, extract the corresponding cold cluster parameter model, obtain the cold cluster parameter prediction value, and assist the experimenter in finding the optimal laser parameters and magnetic field parameters.

[0063] For example: I = 6, cold atom group type set S = {s1, s2, s3, s4, s5, s6};

[0064] The cold atom cluster detection experiment will detect the cold atom cluster s3, extract the transition frequency value F(s3)=2.654 of the cold atom cluster s3, extract the real-time laser parameters, the real-time laser frequency value f=1, the evaluation threshold is 0.5, and calculate the evaluation value of the real-time laser parameters: h=|fF(s3)| / F(s3)=|1-2.654| / 2.654=0.6232, 0.6532>0.5, issue a warning to prompt the experimenter to change the laser frequency value; re-extract the real-time laser parameters until the evaluation value of the real-time laser parameters is greater than the evaluation threshold, extract the parameter model of the cold atom cluster s3, input the real-time laser parameters and the real-time magnetic field parameters into the parameter model of the cold atom cluster s3, and output the number of cold atom clusters s3 and the temperature of the cold atom clusters s3.

[0065] A simulation control system for cold atom group detection based on virtual reality, the system includes: a data acquisition module, a model building module and an early warning module;

[0066] The data acquisition module includes a storage unit and a classification unit. By extracting the experimental equipment work log in the cold atom group detection experiment and the cold atom group data corresponding to the experimental equipment work log, a cold atom group detection experiment database is constructed; according to the types of cold atom groups, a cold atom group type set is constructed;

[0067] The model building module includes a model unit and an update unit, which are used to build a parameter model of the cold atomic cluster;

[0068] The early warning module includes an evaluation unit and a query unit, which obtains the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculates the evaluation value of the real-time laser parameters; through the parameter model of the cold atom cluster, it assists the experimenters in finding the optimal laser parameters and magnetic field parameters.

[0069] Preferably, the data acquisition module includes a storage unit and a classification unit:

[0070] A storage unit constructs a cold atom cluster detection experiment database by extracting the experimental equipment work log and the cold atom cluster data corresponding to the experimental equipment work log in the cold atom cluster detection experiment; the experimental equipment work log records laser parameters and magnetic field parameters, the laser parameters include laser frequency values ​​and light intensity values, and the magnetic field parameters are magnetic field intensity values; the cold atom cluster data include cold atom cluster parameters and cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of cold atom clusters;

[0071] Classification unit, according to the type of cold atom group, construct the type set of cold atom group: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

[0072] Preferably, the model building module includes a model unit and an update unit;

[0073] Model unit, based on the cold atom cluster detection experimental database, constructs cold atom clusters i Parameter model: M = α 1 p 1 +α 2 G+α 3 p 3 +β 1 , T = α 4 p 1 +α 5 e -G +α 6 p 3 +β 2 , where M represents the cold atomic group s i The number of1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 represents the model coefficient, G represents the light intensity value, p 1 、p 3 They represent the detuning effect index of the laser frequency value and the magnetic field intensity value respectively; T represents the cold atomic cluster s i The temperature of the laser frequency value; the detuning amount influences the index: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value; the magnetic field strength value affects the index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i Preset critical value of magnetic field strength in detection experiment; continuously update model coefficient α 1 , α 2 , α 3 , α 4 , α 5 , α 6 , β 1 , β 2 , until the optimal model coefficients are found;

[0074] Update the unit by extracting cold atomic groups s i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data; the cold atom cluster s is calculated. i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' n Represents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual temperature value of the cold atom cluster s i The predicted value of the number of cold atom clusters si When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

[0075] Preferably, the early warning module includes an evaluation unit and a query unit;

[0076] The evaluation unit obtains the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculates the evaluation value of the real-time laser parameter: h = |fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, an early warning is issued, and the experimenter is prompted to change the laser frequency value; otherwise, the cold atom cluster parameters are predicted;

[0077] The query unit extracts the parameter model of the corresponding cold atom cluster based on the real-time cold atom cluster characteristic data, obtains the predicted value of the cold atom cluster parameters, and assists the experimenters in finding the optimal laser parameters and magnetic field parameters.

[0078] 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.

[0079] 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. A simulation control method for cold atom group detection based on virtual reality, characterized in that: The method comprises the following steps: Step S1: extracting the experimental equipment work log and the cold atom group data corresponding to the experimental equipment work log in the cold atom group detection experiment, and constructing a cold atom group detection experiment database; constructing a cold atom group type set according to the types of cold atom groups; Step S2: constructing a parameter model of cold atom clusters based on the cold atom cluster detection experimental database; Step S3: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameters; assist the experimenter in finding the optimal laser parameters and magnetic field parameters through the parameter model of the cold atom cluster.

2. The simulation control method for cold atom group detection based on virtual reality according to claim 1, characterized in that: The specific implementation process of step S1 includes: Step S1.1: extract the experimental equipment work log in the cold atom cluster detection experiment and the cold atom cluster data corresponding to the experimental equipment work log, and construct a cold atom cluster detection experiment database; the experimental equipment work log records the laser parameters and magnetic field parameters, the laser parameters include the laser frequency value and the light intensity value, and the magnetic field parameters are the magnetic field intensity value; the cold atom cluster data include cold atom cluster parameters and cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of the cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of the cold atom clusters; Step S1.2: According to the types of cold atomic groups, construct a cold atomic group type set: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

3. The simulation control method for cold atom group detection based on virtual reality according to claim 2, characterized in that: The specific implementation process of step S2 includes: Step S2.1: Construct cold atom cluster s based on the cold atom cluster detection experimental database i Parameter model: M = α1p1 + α2G + α3p3 + β1, T = α4p1 + α5e -G +α6p3+β2, where M represents the cold atomic group s i , α1, α2, α3, α4, α5, α6, β1, β2 represent the model coefficients, G represents the light intensity value, p1 and p3 represent the detuning influence index of the laser frequency value and the influence index of the magnetic field intensity value respectively; T represents the cold atomic group s i Temperature; Detuning effect index of laser frequency value: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value of Magnetic field strength value influence index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i The preset critical value of the magnetic field strength value in the detection experiment; Step S2.2: Continuously update the model coefficients α1, α2, α3, α4, α5, α6, β1, β2 until the optimal model coefficients are found: Extracting cold radicals i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data; Calculate cold clusters i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' n Represents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual value of temperature; The model coefficients are continuously updated until the cold cluster s i The predicted value of the number of cold atom clusters s i When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

4. The simulation control method for cold atom group detection based on virtual reality according to claim 3, characterized in that: The specific implementation process of step S3 includes: Step S3.1: Acquire the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculate the evaluation value of the real-time laser parameter: h = |fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, issue an early warning and prompt the experimenter to change the laser frequency value; otherwise, predict the cold atom cluster parameters; Step S3.2: Based on the real-time cold cluster characteristic data, extract the corresponding cold cluster parameter model, obtain the cold cluster parameter prediction value, and assist the experimenter in finding the optimal laser parameters and magnetic field parameters.

5. A simulation control system for cold atom group detection based on virtual reality, characterized in that: The system comprises: a data acquisition module, a model building module and an early warning module; The data acquisition module includes a storage unit and a classification unit, and constructs a cold atom group detection experiment database by extracting the experimental equipment work log in the cold atom group detection experiment and the cold atom group data corresponding to the experimental equipment work log; constructs a cold atom group type set according to the types of cold atom groups; The model building module includes a model unit and an update unit, which are used to build a parameter model of the cold atomic group; The early warning module includes an evaluation unit and a query unit, which obtains real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, calculates the evaluation value of the real-time laser parameters; and assists experimenters in finding the optimal laser parameters and magnetic field parameters through the parameter model of the cold atom cluster.

6. The simulation control system for cold atom group detection based on virtual reality according to claim 5, characterized in that: The data acquisition module includes a storage unit and a classification unit: The storage unit constructs a cold atom cluster detection experiment database by extracting the experimental equipment work log in the cold atom cluster detection experiment and the cold atom cluster data corresponding to the experimental equipment work log; the experimental equipment work log records the laser parameters and the magnetic field parameters, the laser parameters include the laser frequency value and the light intensity value, and the magnetic field parameters are the magnetic field intensity value; the cold atom cluster data include the cold atom cluster parameters and the cold atom cluster characteristic data, the cold atom parameters include the number of cold atom clusters and the temperature of the cold atom clusters, and the cold atom cluster characteristic data include the type of cold atom clusters and the transition frequency value of the cold atom clusters; The classification unit constructs a cold atom group type set according to the type of cold atom group: S = {s i |i∈[1,I]}, where s i represents the i-th cold atomic cluster, and I represents the total number of cold atomic cluster types in the cold atomic cluster detection experiment database.

7. The simulation control system for cold atom group detection based on virtual reality according to claim 6, characterized in that: The model building module includes a model unit and an update unit; The model unit constructs a cold atom cluster s based on the cold atom cluster detection experimental database. i Parameter model: M = α1p1 + α2G + α3p3 + β1, T = α4p1 + α5e -G +α6p3+β2, where M represents the cold atomic group s i , α1, α2, α3, α4, α5, α6, β1, β2 represent the model coefficients, G represents the light intensity value, p1 and p3 represent the detuning influence index of the laser frequency value and the influence index of the magnetic field intensity value respectively; T represents the cold atomic group s i The temperature of the laser frequency value; the detuning amount influences the index: Where f represents the cold atomic group s i The laser frequency value of the experimental equipment in the detection experiment, |fF| represents the cold atomic cluster s i The detuning value of the laser frequency in the detection experiment; F represents the cold atom cluster s i The transition frequency value; the magnetic field strength value affects the index: Where E represents the magnetic field strength value, E max represents cold atomic clusters i The preset critical value of the magnetic field strength value in the detection experiment; the model coefficients α1, α2, α3, α4, α5, α6, β1, β2 are continuously updated until the optimal model coefficients are found; The updating unit extracts cold atomic groups s i The historical data of laser parameters, magnetic field parameters and cold atom cluster parameters of the detection experiment are used as training data; the cold atom cluster s is calculated. i The parameter model predictions of the cold atom cluster s i Fitted values ​​of actual values ​​of parameters: Where N represents the total number of training data, M n The cold atom group s represents the nth training data i The number of predicted values, M' n Represents the cold atomic cluster s in the nth training data i The actual value of the number, T n The cold atom group s represents the nth training data i The predicted temperature value, T' n Represents the cold atomic cluster s in the nth training data i The actual temperature value of the cold atom cluster s i The predicted value of the number of cold atom clusters s i When the fitting value MK of the number of actual values ​​reaches the minimum, the training is stopped and the optimal model coefficients are obtained.

8. The simulation control system for cold atom group detection based on virtual reality according to claim 7, characterized in that: The early warning module includes an evaluation unit and a query unit; The evaluation unit obtains the real-time cold atom cluster characteristic data, real-time laser parameters and real-time magnetic field parameters in the virtual reality experiment, and calculates the evaluation value of the real-time laser parameter: h=|fF| / F; if the evaluation value of the real-time laser parameter is greater than the evaluation threshold, an early warning is issued, and the experimenter is prompted to change the laser frequency value; otherwise, the cold atom cluster parameters are predicted; The query unit extracts the parameter model of the corresponding cold atom cluster based on the real-time cold atom cluster characteristic data, obtains the predicted value of the cold atom cluster parameters, and assists the experimenter in finding the optimal laser parameters and magnetic field parameters.

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