A task execution method, device, storage medium and electronic device

Abstract

The present specification provides a task execution method, device, storage medium and electronic device, which can determine a first distribution based on a pre-stored multivariate Gaussian distribution function, determine a second distribution based on a chord-integrated forward model and the first distribution, and perform a Bayesian inversion operation according to the first distribution and the second distribution in response to an acquired operation instruction to obtain a third distribution. By acquiring the actual chord-integrated measurement signal of the target plasma and the actual point measurement values ​​at some positions, the actual physical field information corresponding to each position of the target plasma can be determined according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement values, and the task can be executed according to the actual physical field information.

Description

Technical Field

[0001] This specification relates to the field of nuclear fusion, and in particular to a task execution method, device, storage medium and electronic device. Background Art

[0002] In recent years, nuclear fusion technology has made significant progress. In the process of studying nuclear fusion, the density, temperature and other physical information of plasma at some positions in the nuclear fusion reaction can be measured by nuclear fusion measurement systems (such as point measurement systems (such as bent crystal spectrometers, Thomson laser interferometer measurement systems), chord integral measurement systems (such as radio frequency wave analyzers)) to obtain measurement signals. For example, Stokes scattered light signals and anti-Stokes scattered light signals can be obtained by Thomson laser interferometer measurement systems, and then, physical information such as density and temperature of plasma can be obtained by analyzing and processing the measurement signals.

[0003] At present, Bayesian inversion can be performed based on the measurement signals at some positions of the plasma, so as to invert the information of the entire physical field of the plasma (density field, temperature field, etc.), so as to better control the nuclear fusion reaction. In this process, in order to obtain more abundant information about the physical field of the plasma, the point measurement signal measured by the point measurement system and the chord integral measurement signal measured by the chord integral measurement system can be referred to, so as to invert the entire physical field of the plasma based on these two signals.

[0004] However, the existing Bayesian inversion based on point measurement signals and chord-integrated measurement signals is less efficient. Summary of the invention

[0005] This specification provides a task execution method, device, storage medium and electronic device to partially solve the above-mentioned problems existing in the prior art.

[0006] This manual adopts the following technical solutions:

[0007] This specification provides a task execution method, including:

[0008] Read pre-stored multivariate Gaussian distribution functions and chord-integrated forward models;

[0009] Based on the multivariate Gaussian distribution function, determine, as a first distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known; and, based on the chord-integrated forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution;

[0010] In response to the acquired operation instruction, a Bayesian inversion operation corresponding to the operation instruction is performed according to the first distribution and the second distribution, so as to obtain, as a third distribution, a probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that a chord-integrated measurement signal for the plasma to be measured and a point measurement value at a partial position of the plasma to be measured are obtained;

[0011] An actual chord-integrated measurement signal for a target plasma and an actual point measurement value at a partial position of the target plasma are obtained to determine actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement value, and perform a task according to the actual physical field information.

[0012] Optionally, based on the multivariate Gaussian distribution function, determining the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the position of the part of the plasma to be measured is known, as the first distribution, specifically includes:

[0013] Based on the multivariate Gaussian distribution function, a first target distribution and a second target distribution are determined, wherein the first target distribution is used to characterize a preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the measured plasma, and the second target distribution is used to characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma;

[0014] determining a joint distribution of the first target distribution and the second target distribution;

[0015] Based on the joint distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured is determined as the first distribution, assuming that the point measurement value at the position of the part of the plasma to be measured is known.

[0016] Optionally, based on the joint distribution, determining the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the position of the part of the plasma to be measured is known, as the first distribution, specifically includes:

[0017] Determining a first error distribution, the first error distribution is used to characterize the probability distribution that error information of each point measurement value at a partial position of the plasma to be measured obtained by assuming point measurement conforms to;

[0018] Based on the joint distribution and the first error distribution, a probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured is determined as a first distribution, assuming that the point measurement value at the position of the part of the plasma to be measured is known.

[0019] Optionally, based on the chord-integrated forward model and the first distribution, determining, as the second distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, specifically includes:

[0020] Based on the chord-integrated forward model and the first distribution, determining a second error distribution that is satisfied by error information between each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal, assuming that corresponding physical field information at each position of the plasma to be measured is satisfied by the first distribution;

[0021] According to the second error distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution is determined as a second distribution.

[0022] Optionally, the method further comprises:

[0023] Sampling is performed from the third distribution, and physical field information corresponding to at least a portion of the sampled target plasma is displayed in a visualization interface.

[0024] This specification provides a task execution device, including:

[0025] Reading module: used to read pre-stored multivariate Gaussian distribution functions and chord integral forward models;

[0026] A first determination module is used to determine, based on a multivariate Gaussian distribution function, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known, as a first distribution; and, based on the chord-integrated forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution;

[0027] A second determination module is configured to respond to the acquired operation instruction and perform a Bayesian inversion operation corresponding to the operation instruction according to the first distribution and the second distribution, so as to obtain, as a third distribution, a probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that a chord-integrated measurement signal for the plasma to be measured and a point measurement value at a partial position of the plasma to be measured are obtained;

[0028] An execution module is used to obtain an actual chord-integrated measurement signal for a target plasma and an actual point measurement value at a partial position of the target plasma, so as to determine the actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement value, and perform a task according to the actual physical field information.

[0029] Optionally, the first determining module is specifically configured to:

[0030] Based on the multivariate Gaussian distribution function, a first target distribution and a second target distribution are determined, wherein the first target distribution is used to characterize a preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the measured plasma, and the second target distribution is used to characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma;

[0031] determining a joint distribution of the first target distribution and the second target distribution;

[0032] Based on the joint distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured is determined as the first distribution, assuming that the point measurement value at the position of the part of the plasma to be measured is known.

[0033] Optionally, the first determining module is specifically configured to:

[0034] Determining a first error distribution, the first error distribution is used to characterize the probability distribution that error information of each point measurement value at a partial position of the plasma to be measured obtained by assuming point measurement conforms to;

[0035] Based on the joint distribution and the first error distribution, a probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured is determined as a first distribution, assuming that the point measurement value at the position of the part of the plasma to be measured is known.

[0036] This specification provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned task execution method is implemented.

[0037] This specification provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned task execution method when executing the program.

[0038] At least one of the above technical solutions adopted in this specification can achieve the following beneficial effects:

[0039] The task execution method provided in this specification can determine the first distribution based on a pre-stored multivariate Gaussian distribution function, determine the second distribution based on a chord-integrated forward model and the first distribution, and perform a Bayesian inversion operation according to the first distribution and the second distribution in response to the acquired operation instruction to obtain a third distribution. By acquiring the actual chord-integrated measurement signal of the target plasma and the actual point measurement values ​​at some positions, the actual physical field information corresponding to each position of the target plasma can be determined according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement values, and the task can be executed according to the actual physical field information.

[0040] It can be seen from this that in the process of inverting the physical field information corresponding to each position of the target plasma based on the chord-integrated measurement signal and the point measurement value, it is only necessary to determine the first distribution that each value of the physical field information corresponding to each position of the plasma to be measured conforms to when the point measurement value is known based on the preset multivariate Gaussian distribution function, and then determine the second distribution based on the first distribution and the preset chord-integrated forward model, so as to perform Bayesian inversion based on the first distribution and the second distribution, and determine the actual physical field information based on the third distribution obtained by the Bayesian inversion. That is, in the process of Bayesian inversion, there is no need to perform inversion by establishing a complex point measurement forward model, but the point measurement value can be directly introduced into the first distribution in the form of a multivariate Gaussian distribution for subsequent Bayesian inversion, thereby greatly improving the efficiency of Bayesian inversion. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] The drawings described herein are used to provide a further understanding of this specification and constitute a part of this specification. The illustrative embodiments and descriptions of this specification are used to explain this specification and do not constitute an improper limitation on this specification. In the drawings:

[0042] Figure 1 A flowchart of a task execution method provided in this specification;

[0043] Figure 2 A schematic diagram of the overall process of task execution provided in this manual;

[0044] Figure 3 A schematic diagram of a task execution device provided in this specification;

[0045] Figure 4 A method corresponding to the Figure 1 Schematic diagram of the structure of an electronic device. DETAILED DESCRIPTION

[0046] In order to make the purpose, technical solutions and advantages of this specification more clear, the technical solutions of this specification will be clearly and completely described below in combination with the specific embodiments of this specification and the corresponding drawings. Obviously, the described embodiments are only part of the embodiments of this specification, not all of them. Based on the embodiments in this specification, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this specification.

[0047] In recent years, nuclear fusion technology has made significant progress. In the process of studying nuclear fusion, the density, temperature and other physical information of plasma at some positions in the nuclear fusion reaction can be measured by nuclear fusion measurement systems (such as point measurement systems (such as bent crystal spectrometers, Thomson laser interferometer measurement systems), chord integral measurement systems (such as radio frequency wave analyzers)) to obtain measurement signals. For example, Stokes scattered light signals and anti-Stokes scattered light signals can be obtained by Thomson laser interferometer measurement systems, and then, physical information such as density and temperature of plasma can be obtained by analyzing and processing the measurement signals.

[0048] At present, Bayesian inversion can be performed based on the measurement signals at some positions of the plasma, so as to invert the information of the entire physical field of the plasma (density field, temperature field, etc.), so as to better control the nuclear fusion reaction. In this process, in order to obtain more abundant information about the physical field of the plasma, the point measurement signal measured by the point measurement system and the chord integral measurement signal measured by the chord integral measurement system can be referred to, so as to invert the entire physical field of the plasma based on these two signals. However, the existing Bayesian inversion based on point measurement signals and chord integral measurement signals is inefficient.

[0049] Therefore, this specification provides a task execution method, which can effectively solve the problems in the prior art.

[0050] The technical solutions provided by the embodiments of this specification are described in detail below in conjunction with the accompanying drawings.

[0051] Figure 1 A flowchart of a task execution method provided in this specification includes the following steps:

[0052] S101: Reading pre-stored multivariate Gaussian distribution function and chord integral forward model.

[0053] S102: Based on the multivariate Gaussian distribution function, determine, as a first distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known; and, based on the chord-integral forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integral measurement signal obtained by performing chord-integral measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured is known to conform to the first distribution.

[0054] The execution subject of the task execution method involved in this specification can be a terminal device such as a desktop computer, a laptop computer, or a client installed in the terminal device, or a server. The following only takes the server as the execution subject as an example to illustrate the task execution method in the embodiment of this specification.

[0055] In this specification, the server may first determine the probability distribution (i.e., the third distribution) of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that the chord-integrated measurement signal of the plasma to be measured and the point measurement values ​​at some positions are known. Then, the actual chord-integrated measurement signal of the target plasma and the actual point measurement values ​​at some positions of the plasma obtained may be used to determine the actual physical field information corresponding to each position of the target plasma based on the third distribution when the actual chord-integrated measurement signal of the target plasma and the actual point measurement values ​​at some positions are known.

[0056] In the above content, the plasma to be measured is a general term for plasma, and can also be understood as a random plasma assumed to exist, while the target plasma can refer to the specified plasma for which the overall physical field information is actually to be Bayesianly inverted.

[0057] Specifically, the server may first read the pre-stored multivariate Gaussian distribution function and the chord integral forward model, wherein the chord integral forward model may characterize the mathematical relationship that can convert physical quantities (such as density values, temperature values, etc.) into theoretical chord integral measurement signals.

[0058] Then, based on the multivariate Gaussian distribution function, the server can determine the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the position of the part of the plasma to be measured is known, as the first distribution.

[0059] The physical field information may refer to the density field information, temperature field information, magnetic field information, etc. of the plasma. The point measurement value may refer to the density value, temperature value, etc. of the plasma at a certain position. For example, a point measurement method may be used to measure the plasma by a Langmuir probe to obtain the point measurement value at a certain position of the plasma. Of course, this is a unified explanation of the physical field information and point measurement values ​​of each plasma, which can be applied to the plasma to be measured and the target plasma mentioned in this specification.

[0060] In the process of determining the first distribution, the server can first determine the first target distribution and the second target distribution based on the multivariate Gaussian distribution function. The first target distribution can be used to characterize the preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, and it can often be preliminarily estimated that each value of the corresponding physical field information at each position of the plasma to be measured obeys the mean , the covariance is The multivariate Gaussian distribution is used as the first target distribution. The first target distribution can be specifically referred to the following formula:

[0061]

[0062] in, can be used to characterize the first target distribution, It can be used to characterize the position information of the plasma to be tested. It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. can be used to characterize the mean of the first target distribution, can be used to characterize the covariance of the first target distribution, where and It can be determined based on experience. Usually it can be set to 0. Different values ​​can be set for different types of plasmas to be tested (such as plasmas to be tested in low confinement mode and plasmas to be tested in high confinement mode). .

[0063] In addition, the second target distribution can be used to characterize the probability distribution of the measured values ​​of each point obtained by performing point measurement at the part of the plasma to be measured. It can often be assumed that the measured values ​​of each point obtained by performing point measurement at the part of the plasma to be measured obey the mean , the covariance is The multivariate Gaussian distribution is used as the second target distribution. The second target distribution can be specifically referred to the following formula:

[0064]

[0065] in, can be used to characterize the second target distribution, It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. It can be used to characterize the position information of the part of the plasma to be measured. Can be used to characterize the mean of the second target distribution, can be used to characterize the covariance of the second target distribution, and It can be determined based on experience. Usually it can be set to 0. Correspondingly, for different types of plasma (such as plasma to be tested in low confinement mode and plasma to be tested in high confinement mode), different values ​​can be set accordingly. .

[0066] Then, the joint distribution of the first target distribution and the second target distribution can be determined. The specific joint distribution can be referred to as follows:

[0067]

[0068] in, It can be used to characterize the joint distribution of the first target distribution and the second target distribution. It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. Can be used to characterize the mean of the second target distribution, can be used to characterize the covariance of the second target distribution, It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. can be used to characterize the mean of the first target distribution, can be used to characterize the covariance of the first target distribution, Can be used to characterize and The cross covariance matrix between .

[0069] Based on the joint distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured can be determined as the first distribution, assuming that the point measurement value at the position of the part of the plasma to be measured is known. Of course, when determining the first distribution, it is often necessary to consider the systematic error information (such as calculation error, regularization error, etc.), then, the first distribution can be specifically referred to the following formula:

[0070]

[0071] in, can be used to characterize the first distribution, Can be used to characterize system error information, It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. Can be used to characterize the mean of the second target distribution, can be used to characterize the covariance of the second target distribution, It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. can be used to characterize the mean of the first target distribution, can be used to characterize the covariance of the first target distribution, Can be used to characterize and The cross covariance matrix between .

[0072] In addition, due to and Usually set to 0, then the first distribution can refer to the following formula:

[0073]

[0074] in, can be used to characterize the first distribution, Can be used to characterize system error information, It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. can be used to characterize the covariance of the second target distribution, It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. can be used to characterize the covariance of the first target distribution, Can be used to characterize and The cross covariance matrix between .

[0075] It should be noted that, since there is often a certain error between the point measurement value obtained during point measurement and the true value, in the process of determining the first distribution, the first distribution can also be determined based on the error information of the corresponding point measurement.

[0076] Specifically, a first error distribution may be determined first, wherein the first error distribution is used to characterize the probability distribution conformed to by the error information of each point measurement value at a partial position of the plasma to be measured, which is assumed to be obtained by point measurement. The first error distribution may specifically refer to the following formula:

[0077]

[0078] in, It can be used to characterize the error information of the point measurement value at a part of the position of the plasma to be measured obtained by point measurement. The mean used to characterize the first error distribution, Used to characterize the variance of the first error distribution.

[0079] Then, the first distribution can be determined based on the joint distribution and the first error distribution. The first distribution can refer to the following formula:

[0080]

[0081]

[0082] in, can be used to characterize the first distribution, Can be used to characterize system error information, The variance used to characterize the first error distribution, It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. can be used to characterize the covariance of the second target distribution, It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. can be used to characterize the covariance of the first target distribution, Can be used to characterize and The cross-covariance matrix between can be used to characterize the mean of the first distribution, The covariance used to characterize the first distribution.

[0083] Expand the first distribution into a probability density formula, which can be specifically referred to as follows:

[0084]

[0085] in, can be used to characterize the first distribution, It can be used to characterize the system error information, and m can be used to characterize the dimension of the plasma physical field information to be measured. can be used to characterize the mean of the first distribution, The covariance used to characterize the first distribution, It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. It can be used to characterize the point measurement value obtained by performing point measurement at a part of the plasma to be measured.

[0086] After determining the first distribution, based on the chord-integrated forward model and the first distribution, it is possible to determine the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, and use it as the second distribution.

[0087] Specifically, based on the chord-integrated forward model and the first distribution, a second error distribution can be determined that conforms to the error information between each chord-integrated measurement signal and the corresponding theoretical chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution.

[0088] The relationship between the chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal can be specifically referred to the following formula:

[0089]

[0090] in, It can be used to characterize the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured. can be used to characterize the chord integral forward model operator, can be used to characterize the mean of the first distribution, It can be used to characterize the theoretical chord-integrated measurement signal determined by the chord-integrated forward model. It can be used to characterize the error information between the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured and the corresponding theoretical chord-integrated measurement signal.

[0091] Furthermore, based on the chord-integrated forward model and the first distribution, it is assumed that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, and the error information between each chord-integrated measurement signal and the corresponding theoretical chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured conforms to the mean of 0 and the variance of The Gaussian distribution of , that is, the second error distribution can be specifically referred to the following formula:

[0092]

[0093] in, It can be used to characterize the error information between the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured and the corresponding theoretical chord-integrated measurement signal. can be used to characterize the mean of the second error distribution, can be used to characterize the variance of the second error distribution.

[0094] Then, based on the second error distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution can be determined as the second distribution.

[0095] Specifically, when it is known that the physical field information corresponding to each position of the plasma to be measured conforms to the first distribution, the probability distribution (second distribution) of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured can be represented by a second error distribution, which can be specifically referred to the following formula:

[0096]

[0097] in, can be used to characterize the second distribution, It can be used to characterize the second error distribution, that is, when it is known that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured obeys the distribution of the error information between the chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal.

[0098] The second error distribution can be Expanded into a probability density formula, please refer to the following formula for details:

[0099]

[0100] in, It can be used to characterize the error information between the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured and the corresponding theoretical chord-integrated measurement signal. can be used to characterize the variance of the second error distribution, and k can be used to characterize the dimension of the error information between the chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal.

[0101] The relationship between the chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the theoretical chord-integrated measurement signal is: ,Right now, , it can be determined that, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, the probability distribution (second distribution) of each chord-integrated measurement signal is obtained by performing chord-integrated measurement on the plasma to be measured. The probability density formula of the second distribution can be specifically referred to as follows:

[0102]

[0103] in, can be used to characterize the second distribution, Can be used to characterize system error information, It can be used to characterize the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured. It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. can be used to characterize the chord integral forward model operator, can be used to characterize the mean of the first distribution, It can be used to characterize the theoretical chord-integrated measurement signal determined by the chord-integrated forward model. can be used to characterize the variance of the second error distribution, and k can be used to characterize the dimension of the chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured.

[0104] S103: In response to the acquired operation instruction, a Bayesian inversion operation corresponding to the operation instruction is performed according to the first distribution and the second distribution, so as to obtain, as a third distribution, the probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that a chord-integrated measurement signal for the plasma to be measured and a point measurement value at a partial position of the plasma to be measured are obtained.

[0105] In this specification, the server can respond to the acquired operation instruction and perform the Bayesian inversion operation corresponding to the operation instruction based on the first distribution and the second distribution determined above. That is, based on the Bayesian theorem, the probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured can be obtained under the assumption that the chord integral measurement signal for the plasma to be measured and the point measurement value at the position of the part of the plasma to be measured are obtained, as the third distribution, and the third distribution can be specifically referred to the following formula:

[0106]

[0107] in, can be used to characterize the third distribution, can be used to characterize the second distribution, can be used to characterize the first distribution.

[0108] Furthermore, the probability density formula of the third distribution can be determined according to the probability density formula of the first distribution and the probability density formula of the second distribution. The specific details can be referred to as follows:

[0109]

[0110] in, can be used to characterize the third distribution, can be used to characterize the second distribution, can be used to characterize the first distribution, Can be used to characterize system error information, It can be used to characterize the chord-integrated measurement signal obtained by chord-integrated measurement of the plasma to be measured. It can be used to characterize the physical field information corresponding to each position of the plasma to be tested. It can be used to characterize the point measurement value obtained by point measurement at a part of the plasma to be measured. can be used to characterize the chord integral forward model operator, can be used to characterize the mean of the first distribution, The covariance used to characterize the first distribution, It can be used to characterize the theoretical chord-integrated measurement signal determined by the chord-integrated forward model. can be used to characterize the variance of the second error distribution.

[0111] From this we can see that , that is, the third distribution has a mean of , the covariance is The multivariate normal distribution of .

[0112]

[0113]

[0114] in, can be used to characterize the mean of the third distribution, can be used to characterize the covariance of the third distribution, can be used to characterize the chord integral forward model operator, can be used to characterize the mean of the first distribution, The covariance used to characterize the first distribution, It can be used to characterize the theoretical chord-integrated measurement signal determined by the chord-integrated forward model. can be used to characterize the variance of the second error distribution.

[0115] S104: Acquire an actual chord-integrated measurement signal for a target plasma and actual point measurement values ​​at partial positions of the target plasma, so as to determine actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement values, and perform a task according to the actual physical field information.

[0116] The server can obtain the actual chord-integrated measurement signal for the target plasma and the actual point measurement value at the partial position of the target plasma. Accordingly, after obtaining the actual chord-integrated measurement signal for the target plasma and the actual point measurement value at the partial position of the target plasma, the actual physical field information corresponding to each position of the target plasma can be determined based on the third distribution determined above when the actual chord-integrated measurement signal for the target plasma and the actual point measurement value at the partial position of the target plasma are known.

[0117] For example, the maximum a posteriori estimation method (MAP estimation method) can be used to determine the physical field information that maximizes the probability density function value corresponding to the third distribution when the actual chord-integrated measurement signal of the target plasma and the actual point measurement value at the partial position of the target plasma are known, and then it can be used as the actual physical field information of the target plasma derived by Bayesian inversion. Of course, after determining the actual physical field information of the target plasma, the determined actual physical field information can be displayed in a visual interface by means such as a heat map for easy viewing.

[0118] Furthermore, tasks can be executed based on the actual physical field information of the target plasma derived from Bayesian inversion. For example, the magnetic field configuration of the nuclear fusion reaction device and the fuel injection strategy can be adjusted based on the actual physical field information of the target plasma derived from Bayesian inversion, so as to better control the occurrence of nuclear fusion reactions.

[0119] Of course, in this specification, sampling can also be performed from the third distribution, and then the physical field information corresponding to at least a portion of the sampled target plasma position can be displayed in the visualization interface. For example, a random sampling method can be used to sample from the third distribution, so that the physical field information corresponding to at least a portion of the target plasma position can be sampled, and then the sampled data can be statistically analyzed and displayed in the visualization interface in a manner such as a curve chart.

[0120] In addition, the actual physical field information of the target plasma obtained by Bayesian inversion can be verified according to the physical field information corresponding to at least part of the sampled target plasma. For example, if the physical field information with the highest frequency in the sampling process matches the actual physical field information of the target plasma obtained by Bayesian inversion, the better the effect of Bayesian inversion is.

[0121] In order to further illustrate the above task execution method, the following will be explained in the form of a legend. For details, please refer to the following Figure 2 .

[0122] Figure 2 A schematic diagram of the overall task execution process provided in this manual.

[0123] Depend on Figure 2 It can be seen that in the process of performing Bayesian inversion to obtain the actual physical field information corresponding to each position of the target plasma, the actual point measurement value at the partial position of the target plasma and the actual chord-integrated measurement signal of the target plasma can be obtained based on the determined third distribution to determine the actual physical field information corresponding to each position of the target plasma when the actual point measurement value at the partial position of the target plasma and the actual chord-integrated measurement signal of the target plasma are known, and then the task can be performed according to the actual physical field information corresponding to each position of the target plasma. Of course, in order to determine the third distribution, the first distribution and the second distribution can be determined first, and then the corresponding Bayesian inversion operation can be performed according to the first distribution and the second distribution to determine the third distribution.

[0124] In the process of determining the first distribution, a joint distribution of the two can be determined based on a first target distribution that can characterize a preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the measured plasma and a second target distribution that can characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma. Then, based on the joint distribution, a probability distribution of each value of the corresponding physical field information at each position of the measured plasma can be determined when the point measurement value at the partial position of the measured plasma is known, that is, the first distribution.

[0125] In the process of determining the second distribution, based on the chord-integrated forward model and the first distribution, a second error distribution that is consistent with the error information between each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal can be determined. Furthermore, based on the second error distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, i.e., a second distribution, can be determined.

[0126] Accordingly, after determining the first distribution and the second distribution, a corresponding Bayesian inversion operation can be performed to determine a third distribution. Based on the third distribution, the actual point measurement values ​​at the target plasma portion and the actual chord-integrated measurement signals of the target plasma can be obtained to determine the actual physical field information corresponding to each position of the target plasma when the actual point measurement values ​​at the target plasma portion and the actual chord-integrated measurement signals of the target plasma are known, so as to perform the corresponding task.

[0127] It can be seen from this that in the process of inverting the physical field information corresponding to each position of the target plasma based on the chord-integrated measurement signal and the point measurement value, it is only necessary to determine the first distribution that each value of the physical field information corresponding to each position of the plasma to be measured conforms to when the point measurement value is known based on the preset multivariate Gaussian distribution function, and then determine the second distribution based on the first distribution and the preset chord-integrated forward model, so as to perform Bayesian inversion based on the first distribution and the second distribution, and determine the actual physical field information based on the third distribution obtained by the Bayesian inversion. That is, in the process of Bayesian inversion, there is no need to perform inversion by establishing a complex point measurement forward model, but the point measurement value can be directly introduced into the first distribution in the form of a multivariate Gaussian distribution for subsequent Bayesian inversion, thereby greatly improving the efficiency of Bayesian inversion.

[0128] The above are one or more implementation methods of this specification. Based on the same idea, this specification also provides a corresponding task execution device, such as Figure 3 shown.

[0129] Figure 3 A schematic diagram of a task execution device provided for this specification includes:

[0130] Reading module 301: used to read pre-stored multivariate Gaussian distribution function and chord integral forward model;

[0131] The first determination module 302 is used to determine, based on a multivariate Gaussian distribution function, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known, as a first distribution, and, based on the chord-integrated forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution;

[0132] The second determination module 303 is used to respond to the acquired operation instruction and perform the Bayesian inversion operation corresponding to the operation instruction according to the first distribution and the second distribution, so as to obtain the probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured under the assumption that the chord-integrated measurement signal of the plasma to be measured and the point measurement value at the partial position of the plasma to be measured are obtained, as the third distribution;

[0133] Execution module 304: used to obtain an actual chord-integrated measurement signal for a target plasma and an actual point measurement value at a partial position of the target plasma, so as to determine the actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement value, and perform a task according to the actual physical field information.

[0134] Optionally, the first determining module 302 is specifically configured to:

[0135] Based on a multivariate Gaussian distribution function, a first target distribution and a second target distribution are determined, wherein the first target distribution is used to characterize a preliminary estimate of the probability distribution of each value of the physical field information at each position of the measured plasma, and the second target distribution is used to characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma; a joint distribution of the first target distribution and the second target distribution is determined; based on the joint distribution, the probability distribution of each value of the physical field information at each position of the measured plasma is determined as a first distribution, assuming that the point measurement value at the partial position of the measured plasma is known.

[0136] Optionally, the first determining module 302 is specifically configured to:

[0137] A first error distribution is determined, where the first error distribution is used to characterize a probability distribution conforming to error information of point measurement values ​​at partial positions of the plasma to be measured, assuming that point measurement is obtained; based on the joint distribution and the first error distribution, a probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement values ​​at the partial positions of the plasma to be measured are known, is determined as the first distribution.

[0138] Optionally, the first determining module 302 is specifically configured to:

[0139] Based on the chord-integrated forward model and the first distribution, a second error distribution is determined, which is satisfied by the error information between each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution; based on the second error distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, is determined as a second distribution.

[0140] Optionally, the device further comprises: a display module 305;

[0141] The display module 305 is specifically used to: sample from the third distribution, and display the sampled physical field information corresponding to at least a part of the position of the target plasma in a visual interface.

[0142] This specification also provides a computer-readable storage medium, which stores a computer program, which can be used to execute the above Figure 1 The task execution method shown.

[0143] This manual also provides Figure 4 The one shown corresponds to Figure 1 A schematic diagram of the electronic device. Figure 4 As shown, at the hardware level, the electronic device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory, and may also include other hardware required for the business. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to achieve the above Figure 1 The task execution method shown.

[0144] Of course, in addition to software implementation, this specification does not exclude other implementation methods, such as logic devices or a combination of software and hardware, etc., that is to say, the executor of the following processing flow is not limited to each logic unit, but can also be hardware or logic devices.

[0145] In the 1990s, it was very clear whether the improvement of a technology was hardware improvement (for example, improvement of the circuit structure of diodes, transistors, switches, etc.) or software improvement (improvement of the method flow). However, with the development of technology, many improvements of the method flow today can be regarded as direct improvements of the hardware circuit structure. Designers almost always obtain the corresponding hardware circuit structure by programming the improved method flow into the hardware circuit. Therefore, it cannot be said that the improvement of a method flow cannot be implemented with hardware entity modules. For example, a programmable logic device (PLD) (such as a field programmable gate array (FPGA)) is such an integrated circuit whose logical function is determined by the user's programming of the device. Designers can "integrate" a digital system on a PLD by programming it themselves, without having to ask chip manufacturers to design and make dedicated integrated circuit chips. Moreover, nowadays, instead of manually making integrated circuit chips, this kind of programming is mostly implemented by "logic compiler" software, which is similar to the software compiler used when developing and writing programs, and the original code before compilation must also be written in a specific programming language, which is called hardware description language (HDL). There is not only one kind of HDL, but many kinds, such as ABEL (Advanced Boolean Expression Language), AHDL (Altera Hardware Description Language), Confluence, CUPL (Cornell University Programming Language), HDCal, JHDL (Java Hardware Description Language), Lava, Lola, MyHDL, PALASM, RHDL (Ruby Hardware Description Language), etc. The most commonly used ones are VHDL (Very-High-Speed ​​Integrated Circuit Hardware Description Language) and Verilog. Those skilled in the art should also know that it is only necessary to program the method flow slightly in the above-mentioned hardware description languages ​​and program it into the integrated circuit, and then it is easy to obtain the hardware circuit that implements the logic method flow.

[0146] The controller may be implemented in any suitable manner, for example, the controller may take the form of a microprocessor or processor and a computer-readable medium storing a computer-readable program code (e.g., software or firmware) executable by the (micro)processor, a logic gate, a switch, an application-specific integrated circuit (ASIC), a programmable logic controller, and an embedded microcontroller, examples of which include but are not limited to the following microcontrollers: ARC 625D, Atmel AT91SAM, Microchip PIC18F26K20, and Silicone Labs C8051F320, and the memory controller may also be implemented as part of the control logic of the memory. It is also known to those skilled in the art that, in addition to implementing the controller in a purely computer-readable program code manner, the controller may be implemented in the form of a logic gate, a switch, an application-specific integrated circuit, a programmable logic controller, and an embedded microcontroller by logically programming the method steps. Therefore, such a controller may be considered as a hardware component, and the devices for implementing various functions included therein may also be considered as structures within the hardware component. Or even, the devices for implementing various functions may be considered as both software modules for implementing the method and structures within the hardware component.

[0147] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0148] For the convenience of description, the above device is described in various units according to their functions. Of course, when implementing this specification, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0149] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems, or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0150] This specification is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of this specification. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0151] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0152] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0153] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0154] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0155] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0156] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity 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, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0157] It should be understood by those skilled in the art that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, this specification may take the form of a complete hardware embodiment, a complete software embodiment or an embodiment combining software and hardware. Moreover, this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] This specification may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. This specification may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0159] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0160] The above description is only an embodiment of the present specification and is not intended to limit the present specification. For those skilled in the art, the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present specification shall be included in the scope of the claims of the present specification.

Claims

1. A task execution method, characterized in that: include: Read pre-stored multivariate Gaussian distribution functions and chord-integrated forward models; Based on the multivariate Gaussian distribution function, determine, as a first distribution, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known; and, based on the chord-integrated forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution; In response to the acquired operation instruction, performing a Bayesian inversion operation corresponding to the operation instruction on the first distribution and the second distribution, so as to obtain, as a third distribution, a probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that a chord-integrated measurement signal for the plasma to be measured and a point measurement value at a partial position of the plasma to be measured are obtained; Acquire an actual chord-integrated measurement signal for a target plasma and an actual point measurement value for a portion of the target plasma, so as to determine actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement value, and perform a task according to the actual physical field information; Wherein, determining the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the position of the part of the plasma to be measured is known, as the first distribution, specifically includes: Based on the multivariate Gaussian distribution function, a first target distribution and a second target distribution are determined, wherein the first target distribution is used to characterize a preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the measured plasma, and the second target distribution is used to characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma; determining a joint distribution of the first target distribution and the second target distribution; Determining a first error distribution, the first error distribution is used to characterize the probability distribution that error information of each point measurement value at a partial position of the plasma to be measured obtained by assuming point measurement conforms to; Based on the joint distribution and the first error distribution, determining, as a first distribution, probability distributions of values ​​of the corresponding physical field information at various positions of the plasma to be measured, assuming that the point measurement values ​​at the positions of the partial plasma to be measured are known; Among them, performing the task according to the actual physical field information specifically includes: According to the actual physical field information, the magnetic field configuration and / or fuel injection strategy of the nuclear fusion reaction device is adjusted.

2. The method according to claim 1, characterized in that Based on the chord-integrated forward model and the first distribution, determining, as a second distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution, specifically includes: Based on the chord-integrated forward model and the first distribution, determining a second error distribution that is satisfied by error information between each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured and the corresponding theoretical chord-integrated measurement signal, assuming that corresponding physical field information at each position of the plasma to be measured is satisfied by the first distribution; According to the second error distribution, a probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution is determined as a second distribution.

3. The method according to claim 1, characterized in that The method further comprises: Sampling is performed from the third distribution, and physical field information corresponding to at least a portion of the sampled target plasma is displayed in a visualization interface.

4. A task execution device, characterized in that: include: Reading module: used to read pre-stored multivariate Gaussian distribution functions and chord integral forward models; A first determination module is used to determine, based on a multivariate Gaussian distribution function, the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known, as a first distribution; and, based on the chord-integrated forward model and the first distribution, determine, as a second distribution, the probability distribution of each chord-integrated measurement signal obtained by performing chord-integrated measurement on the plasma to be measured, assuming that the corresponding physical field information at each position of the plasma to be measured conforms to the first distribution; A second determination module is configured to, in response to the acquired operation instruction, perform a Bayesian inversion operation corresponding to the operation instruction on the first distribution and the second distribution, so as to obtain, as a third distribution, a probability distribution of each value of the physical field information corresponding to each position of the plasma to be measured, assuming that a chord-integrated measurement signal for the plasma to be measured and a point measurement value at a partial position of the plasma to be measured are obtained; An execution module: used for acquiring an actual chord-integrated measurement signal for a target plasma and an actual point measurement value for a portion of the target plasma, so as to determine actual physical field information corresponding to each position of the target plasma according to the third distribution, the actual chord-integrated measurement signal and the actual point measurement value, and perform a task according to the actual physical field information; The first determination module is specifically used to: determine a first target distribution and a second target distribution based on a multivariate Gaussian distribution function, wherein the first target distribution is used to characterize a preliminary estimate of the probability distribution of each value of the corresponding physical field information at each position of the measured plasma, and the second target distribution is used to characterize the probability distribution of each point measurement value obtained by performing point measurement at a partial position of the measured plasma; determine the joint distribution of the first target distribution and the second target distribution; Determine a first error distribution, where the first error distribution is used to characterize the probability distribution that error information of each point measurement value at a partial position of the plasma to be measured obtained by assuming point measurement conforms to; based on the joint distribution and the first error distribution, determine the probability distribution of each value of the corresponding physical field information at each position of the plasma to be measured, assuming that the point measurement value at the partial position of the plasma to be measured is known, as the first distribution; The execution module is specifically used to adjust the magnetic field configuration and / or fuel injection strategy of the nuclear fusion reaction device according to the actual physical field information.

5. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method described in any one of claims 1 to 3 is implemented.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the program, the method described in any one of claims 1 to 3 is implemented.

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