CN118112683B - Method for acquiring global distribution of corona plasma parameters - Google Patents

Abstract

The invention discloses a method for acquiring the global distribution of corona plasma parameters. According to the method, a corona spectrum model Y=RX is constructed according to the physical condition of corona multi-slit observation and the value of the physical condition, each element R _ij in a response matrix R is calculated to obtain the response matrix R, spectrum coupling data obtained through corona multi-slit observation is decoupled through inversion calculation, and the global distribution of corona plasma parameters is obtained through the decoupled spectrum. The method can rapidly and accurately acquire the global distribution of key parameters such as corona plasma density, temperature, view direction speed and the like, plays a positive role in monitoring and forecasting space weather, and is beneficial to reducing economic loss caused by disastrous space weather.

Description

Methods for obtaining global distribution of coronal plasma parameters

Technical Field

The present invention belongs to the field of space astronomical remote sensing detection. Specifically, it relates to a method for obtaining the global distribution of coronal plasma parameters, as well as corresponding electronic equipment and computer-readable storage media, and a coronal spectrum decoupling method that can be used in the method. The present invention can be applied to achieve all-weather monitoring of global coronal physical properties and their evolution, and promote accurate space weather forecasting.

Background Art

The corona is the outermost atmosphere of the Sun, composed of plasma with temperatures as high as millions of degrees. The high-temperature corona inevitably expands outward, thus forming a solar wind that fills the interplanetary space. The corona also produces explosive activities such as coronal mass ejections and flares from time to time, driving large groups of plasma and high-energy particles into interplanetary space. Therefore, the physical properties of the coronal plasma largely determine the physical state of the heliospheric space environment. How to accurately and quickly obtain the global distribution of physical parameters such as coronal plasma density, temperature and radial velocity is very important for us to understand and predict the evolution of the Sun-Earth and even the entire heliospheric space environment.

To simultaneously obtain information such as the density, temperature, and radial velocity of the coronal plasma, it is usually necessary to use coronal spectral observations. However, existing spectral observations cannot obtain the global distribution of these physical parameters in a short period of time (within a few minutes). For example, solar spectrometers working in the extreme ultraviolet band, such as the CDS instrument on the European SOHO satellite and the EIS instrument on the Japanese Hinode satellite, use a slit scan to obtain the two-dimensional distribution of these physical parameters, but the field of view of such spectrometers is usually very small (about 300×300 arc seconds), and the scanning time is usually on the order of hours. The UVCS instrument on the SOHO satellite and the CoMP coronagraph operated by the National Center for Atmospheric Research in the United States have used spectral line observations in the far ultraviolet and near infrared bands to obtain coronal plasma parameters, respectively, but both can only observe the edge of the corona and cannot obtain information about the corona above the solar disk. The EVE instrument on the US SDO satellite can only obtain the extreme ultraviolet spectrum of the entire solar surface, without spatial resolution, and therefore cannot obtain the spatial distribution of coronal physical parameters. The sounding rocket carrying MOSES launched by the United States uses a seamless spectrometer, but it can only obtain radial velocity information, and the observation time of the sounding rocket is usually in the order of minutes, which cannot be observed for a long time. In summary, the existing technology cannot quickly obtain the global distribution of coronal plasma parameters, either it takes too long or it can only observe the edge of the corona.

Summary of the invention

The purpose of the present invention is to quickly and accurately obtain the global distribution of key parameters such as coronal plasma density, temperature, and radial velocity to solve the problems existing in the above-mentioned background technology.

To achieve the above objectives, in a first aspect, the present invention provides a method for decoupling a corona spectrum, comprising:

Acquire spectral coupling data obtained by coronal multi-slit observation; the observation area of coronal multi-slit observation is part or the entire full solar disk field of view, and the coronal multi-slit observation adopts multiple exposures of n slits, and multiple spectral coupling data are obtained by a single exposure, and each spectral coupling data includes spectral coupling data of n positions on the sun in the dispersion direction during a single exposure;

Determine the physical conditions and values of the coronal multi-slit observation; the physical conditions of the coronal multi-slit observation include the physical conditions of the coronal body and the physical conditions of the observation equipment; the physical conditions of the coronal body include but are not limited to the temperature, density, and radial velocity of the coronal body; the physical conditions of the observation equipment include but are not limited to the number of slits, the slit spacing, and the observation band of the observation equipment used for the coronal multi-slit observation;

According to the physical conditions and values of the coronal multi-slit observation, the coronal spectrum model Y=RX is constructed; among them,

Y is a spectrum coupling data matrix of M×1 dimensions corresponding to a single spectrum coupling data, wherein the row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation device, M represents the number of detector pixel positions, and the element yi of the observation spectrum pixel matrix _Y represents the spectrum coupling data at the i-th detector pixel position, i=1,2,…,M;

R is the response matrix corresponding to the observation band of the observation device, with the dimension of M×Q, its row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation device, the column position represents the value of the physical condition of the coronal multi-slit observation, Q is the number of values of the physical condition of the coronal multi-slit observation, and the element r _ij of the response matrix R represents the unit spectral coupling response at the i-th detector pixel position when the physical condition of the coronal multi-slit observation is equal to the value of the j-th column, j=1,2,…,Q;

X is the Q×1-dimensional coronal plasma radiation matrix, whose row positions correspond to the column positions of the same serial number in the response matrix R. The element _xj of the coronal plasma radiation matrix X represents the line-of-sight integrated radiation of the coronal plasma when the physical condition of the coronal multi-slit observation is equal to the value of the jth column of the response matrix R.

Calculate each element r _ij in the response matrix R to obtain the response matrix R;

The radiation matrix X of the coronal plasma is obtained by inverting the coronal spectrum model Y = RX. According to Y _s = R _s X, the spectrum data matrix Y _s of the s-th slit is obtained, where s = 1, 2, …, n, R _s is the response matrix of the s-th slit, with a dimension of M × Q. The element in the i-th row and j-th column of the response matrix R _s of the s-th slit is

Y-RX is calculated based on the radiation matrix X of the coronal plasma obtained by inversion calculation. Based on the calculation results of Y-RX, it is judged whether the response matrix R meets the spectral decoupling accuracy requirements. If not, the physical conditions and values of the coronal multi-slit observation are re-determined, and the coronal spectrum model is constructed and calculated and judged.

In some embodiments of the present invention, the redetermination of the physical conditions and values of the coronal multi-slit observation is carried out based on the decoupling accuracy and decoupling time of the coronal spectral decoupling.

In some embodiments of the present invention, each element r _ij in the calculated response matrix R is obtained based on the contribution function C(T, λ, _Ne ) in CHIANTI, an atomic physics database commonly used in the field of solar physics.

In some embodiments of the present invention, the inversion calculation of the coronal spectrum model Y=RX is to use a machine learning method to optimize the target Perform inversion calculation, where is the L2 norm of Y-RX, the second term is the L1 norm of X, and α is a hyperparameter in the machine learning method, which is used to control the sparsity of the solution. Further, the machine learning method is the LassoLars method in linear regression.

In a second aspect, the present invention provides a method for obtaining the global distribution of coronal plasma parameters. The method uses the spectrum obtained by the coronal spectral decoupling method to obtain the global distribution of coronal plasma parameters. The coronal plasma parameters include the density, temperature and radial velocity of the coronal plasma.

In some embodiments of the present invention, the observed spectral data obtained by coronal multi-slit observation is obtained by observing with multiple slits in the east-west direction.

In some embodiments of the present invention, during inversion, the density ranges from 10 ⁷ cm ^-3 to 10 ¹³ cm ^-3 , with a density interval of 0.5 (log N/cm ^-3 ); the temperature ranges from 10 ^5.0 K to 10 ^6.6 K, with a temperature interval of 0.1 (log T/K); the velocity ranges from -100 km/s to 100 km/s, with a value interval of 10 km/s; the number of slits ranges from 2 to 8; the slit spacing ranges from to The value interval is The observation band is to The preferred inversion is 5 slits with a slit spacing of or or or or

In a third aspect, the present invention provides an electronic device comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the coronal spectral decoupling method, or can execute the method for obtaining the global distribution of coronal plasma parameters.

In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the coronal spectral decoupling method, or implements the method for obtaining the global distribution of coronal plasma parameters.

The present invention has the following beneficial effects:

The present invention achieves the decoupling of spectral coupling data obtained by coronal multi-slit observations by inverting the constructed coronal spectral model, thereby being able to quickly and accurately obtain the global distribution of key parameters such as coronal plasma density, temperature, and radial velocity, which plays a positive role in promoting the monitoring and forecasting of space weather and helps to reduce the economic losses caused by catastrophic space weather.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG1 is a flow chart of a method for decoupling the coronal spectrum in one embodiment of the present invention.

FIG2 is a schematic diagram showing the principle of multi-slit observation of the coronal spectrum of the present invention.

FIG3 is a schematic diagram showing the principle of multi-slit observation of the coronal spectrum in one embodiment of the present invention.

FIG. 4 is a schematic diagram of a synthetic spectral response according to an embodiment of the present invention.

FIG. 5 is a spectrum diagram showing an example of the wavelength bands and effective areas used in one embodiment of the present invention.

FIG. 6 is a diagram showing an example of a profile of a spectrum actually synthesized from a PSI model in one embodiment of the present invention.

FIG. 7 is a comparison diagram of plasma diagnosis results in one embodiment of the present invention with reference truth values and decoupling results.

FIG. 8 is another comparison diagram of the plasma diagnosis result in one embodiment of the present invention with respect to the reference truth value and the decoupling result.

FIG. 9 is a schematic diagram of the composition of an electronic device in one embodiment of the present invention.

DETAILED DESCRIPTION

The following describes the embodiments of the present invention by specific examples, and those skilled in the art can easily understand other advantages and effects of the present invention from the contents disclosed in this specification. The present invention can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present invention. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

It should be noted that the illustrations provided in the following embodiments are only schematic illustrations of the basic concept of the present invention, and thus the drawings only show components related to the present invention rather than being drawn according to the number, shape and size of components in actual implementation. In actual implementation, the type, quantity and proportion of each component may be changed arbitrarily, and the component layout may also be more complicated.

In order to quickly and accurately obtain the global distribution of key parameters such as coronal plasma density, temperature, and radial velocity, the present invention first uses a global multi-slit design to obtain observations with a large field of view and higher time resolution, thereby realizing rapid observation of the global corona and obtaining its plasma information. However, on the one hand, from a technical perspective, it is difficult to achieve extremely narrowband filtering in the extreme ultraviolet band, resulting in the spectra from different slits obtained by the multi-slit design being coupled together. On the other hand, from a scientific perspective, simultaneous diagnosis of temperature, density, and radial velocity requires covering a certain band range. Even with extremely narrowband filtering, the bandwidth requirements of the observation band will also lead to spectral-image coupling in the multi-slit spectrum. Spectra with spectral-image coupling are difficult to carry out various plasma diagnoses and cannot obtain effective plasma information. Therefore, in conjunction with the coronal multi-slit observation method, the present invention provides a method for decoupling the coronal spectrum and a method for obtaining the global distribution of coronal plasma parameters, which decouples the observed, coupled total spectrum to obtain the contribution of each slit, and then obtains the spectral information of the global corona through various plasma diagnoses.

Example 1

This embodiment is used to explain in detail the coronal spectrum decoupling method of the present invention. As shown in FIG1 , the coronal spectrum decoupling method of the present invention in one embodiment specifically includes:

Step S100, obtaining spectral coupling data obtained by coronal multi-slit observation; the observation area of the coronal multi-slit observation is part of or the entire full-disk field of view, and the coronal multi-slit observation adopts multiple exposures of n slits, and multiple spectral coupling data are obtained by a single exposure, and each spectral coupling data includes the spectrum of n positions on the sun in the dispersion direction during a single exposure.

FIG2 is a schematic diagram of the principle of the multi-slit observation of the coronal spectrum in this embodiment. Referring to FIG2, the size of the full solar disk field of view 100 of the multi-slit observation of the coronal disk is f″×f″ (″ represents arc seconds). The multi-slit observation device of the coronal disk adopts a multi-slit observation structure 200 with n slits S1, S2, …, Sn, n ≥ 2, and the observation range covered by each slit is f″×p″, p″ is the detector pixel scale corresponding to the spatial resolution r″ of the multi-slit observation device of the coronal disk, p = r/2, and each exposure is a simultaneous exposure of n slits, and a total of 100 is required to scan the full solar disk field of view 100. exposures. If each exposure time is t seconds, then the time required to scan the entire field of view is approximately (Here, it is assumed that the slit movement and detector readout time are very short and do not need to be considered for the time being). If the slit spacing is i″ (i≤480″) in the full disk field of view 100, then the entire full disk field of view 100 will be divided into The size of each portion is f″×(i×n)″, as shown in 101 of FIG2 , the scanning step length in each portion is p″, and the number of scans is After that, a large offset is required. This offset is the step size between each large portion, which is (i×n)″-i″. Since coupling only occurs in the dispersion direction, in the direction perpendicular to the dispersion direction, there are detector pixels, and the entire full solar disk field of view is scanned in the above manner. spectral coupling data to be decoupled, each spectral coupling data includes spectra of n positions on the sun in the dispersion direction during a single exposure.

FIG3 is a schematic diagram of the principle of multi-slit observation of the coronal spectrum of this embodiment. In FIG3, the slits are oriented in an east-west direction (W-E), and there are five slits, which illustrates the situation where the light from two slits is superimposed on the spectrum diagram, where the slits are represented by S, and the subscripts correspond to their numbers (from 1 to 5). Lines of sight (LOS) is the line of sight direction. After the light in the line of sight direction passes through the slits, the light of different wavelengths is separated by a disperser (usually a diffraction grating) to form a spectrogram on the detector.

Referring to FIG3 , specifically, in this embodiment and some other embodiments of the present invention, the size of the entire full disk field of view is 2400″×2400″, and the five slits shown in FIG3 are used for coronal multi-slit observation. The spacing of the five slits in the global field of view is 40″, and the size of the large portion 101 is 2400″×200″. According to the corresponding relationship between the spacing of the slits in the global field of view and the spacing on the spectrum diagram, the slit spacing on the spectrum diagram is obtained as follows: If the spatial resolution in the dispersion direction of the disperser is 4", and the spatial resolution along the slit direction is 4", then the pixel scale is 2"×2", that is, the spatial resolution of the coronal multi-slit observation device is 4", and each slit moves 2" each time in the large portion 101. If the exposure time is about 1 second each time, at the spatial resolution, the entire solar disk can be quickly scanned in about 240 seconds, and after each conventional scan of 20 exposures, the five slits will have an overall large offset, and each slit moves 160". In other words, the entire field of view is divided into 12 large portions for scanning, and a total of 288,000 spectral coupling data to be decoupled are obtained. Each spectral coupling data y includes spectra at 5 different positions on the sun at the same exposure time, as shown in Figure 3. This approach can enhance the accuracy of the decoupled spectrum and minimize the influence of intensity differences on the decoupled spectrum.

Step S200, determining the physical conditions and values of the coronal multi-slit observation; the physical conditions of the coronal multi-slit observation include the physical conditions of the coronal body and the physical conditions of the observation equipment.

Referring to Figure 3, in each exposure, multiple beams of sunlight in the line of sight pass through the corresponding slits and fall on the detector after being split, so as to be detected by the detector, and the spectral coupling data of the multiple beams of sunlight are obtained. The spectral coupling data obtained in each exposure is related to the physical conditions of the coronal multi-slit observation, which includes the physical conditions of the observed object and the observation equipment.

In this embodiment and some other embodiments of the present invention, the physical conditions of the corona, that is, the physical conditions of the observed object, select the temperature, density, and radial velocity of the corona; the physical conditions of the observation equipment select the number of slits, the slit spacing, and the observation band of multi-slit observation.

Step S300, constructing a coronal spectrum model Y=RX according to the physical conditions and values of the coronal multi-slit observation.

Wherein, Y is a spectrum coupling data matrix of M×1 dimensions corresponding to a single spectrum coupling data, and its row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation device, M represents the number of detector pixel positions, and the element _yi of the observation spectrum pixel matrix Y represents the spectrum coupling data at the i-th detector pixel position, i=1,2,…,M. For example, in the embodiment shown in FIG3 , each exposure obtains a spectrum coupling two-dimensional image obtained by splitting sunlight through five slits in the line of sight on the detector, and each row of the image is a single spectrum coupling data, which is the corresponding spectrum coupling data matrix after transposition.

R is the response matrix corresponding to the observation band of the observation equipment, with dimension M×Q. Its row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation equipment, and the column position represents the value of the physical condition of the coronal multi-slit observation. Q is the number of values of the physical condition of the coronal multi-slit observation. The element r _ij of the response matrix R represents the spectral coupling response of unit radiation at the i-th detector pixel position when the physical condition of the coronal multi-slit observation is equal to the value of the j-th column, j=1,2,…,Q.

The response matrix is actually the spectral response under different physical conditions of coronal multi-slit observations (different coronal plasma temperatures, densities, radial velocities, observation bands, slit spacings, and slits). As shown in Figure 4, we show the outline of the response matrix of multiple slits with a specific slit spacing in a specific observation band at a specific temperature, density, and radial velocity. Different colors represent different slits.

Specifically, this embodiment selects the temperature, density, and radial velocity of the corona as the corona physical conditions, and selects the number of slits, the slit spacing, and the observation band of the multi-slit observation as the physical conditions of the observation equipment. The element r _ij of the response matrix R represents the spectral response of a unit radiation amount of sunlight at a certain wavelength (corresponding to the detector pixel position) within the observation band after passing through a certain slit with a specific slit spacing of the observation equipment under the conditions of a certain temperature, density, and radial velocity of the corona, or the spectral response at a specific detector pixel position. If the number of values of the temperature, density, and radial velocity of the corona are Q _T , Q _N , and Q _V , respectively, and the number of slits of the observation equipment is Q _S , then the physical condition of the multi-slit observation of the corona is a combination of all the physical condition values, and its number is The specific range and interval of the values of the corona's temperature, density, and radial velocity are related.

X is a Q×1-dimensional coronal plasma radiation matrix, whose row positions correspond to the column positions of the same sequence number in the response matrix R. The element _xj of the coronal plasma radiation matrix X represents the line-of-sight integrated radiation of the coronal plasma when the physical condition of the coronal multi-slit observation is equal to the value of the j-th column of the response matrix R. The line-of-sight integrated radiation of the coronal plasma is the radiation of the corona in the line of sight column . The physical definition is _Ne represents the electron density, and dl represents the line-of-sight integration unit.

Step S400: Calculate each element r _ij in the response matrix R to obtain the response matrix R.

Calculating each element r _ij in the response matrix R is to calculate the spectral response at each detector pixel position under each specific physical condition.

Specifically, if the physical conditions corresponding to the 1000th column of the response matrix R are that the temperature of the corona is 10 ^5.0 K, the density is 10 ⁷ cm ^-3 , the radial velocity is 100 km/s, and the distance between the slits is The element _r1000,1000 of the response matrix R represents the spectral response at the 1000th position of the detector pixel under the physical conditions corresponding to the 1000th column position.

In this embodiment and some other embodiments of the present invention, the calculation of each element r _ij in the response matrix R is based on the contribution function in the atomic physics database CHIANTI of the solar physics software SSW (see the website https://www.mssl.ucl.ac.uk/surf/sswdoc/ , abbreviation of SolarSoftWare). The characteristic spectral line response of a single ion under given coronal multi-slit observation physical conditions is first calculated, and then based on the characteristic spectral line response of the single ion under given coronal multi-slit observation physical conditions, the characteristic spectral line response profile of the single ion under given coronal multi-slit observation physical conditions is calculated. Finally, the characteristic spectral line responses of all single ions under given coronal multi-slit observation physical conditions are synthesized to obtain the synthetic spectral response of the coronal plasma under given coronal multi-slit observation physical conditions, so that the value of the element r _ij can be obtained from the synthetic spectral response according to the definition of the response matrix R.

First, the characteristic spectral line response of a single ion under the given physical conditions of coronal multi-slit observation is calculated. Specifically, the contribution function generated in the atomic physics database CHIANTI is related to the temperature T and density N of the coronal plasma. Based on the contribution function, the characteristic spectral line response _IR (λ) of a single ion L can be calculated, _IR (λ) = Ab (L) C (T, λ, _Ne ), T represents the temperature, λ represents the characteristic spectral line wavelength of the single ion L, _Ne is the electron density related to the plasma density N, and Ab (L) represents the element abundance of a single ion L. The element abundance of a single ion directly provided by the atomic physics database CHIANTI can be used. By the way, the photon intensity I (λ) of a spectral line in the spectrum can be obtained by the characteristic spectral line response _IR (λ) of a single ion L, I (λ) = _IR (λ) EM, EM (emission measure) is the above-mentioned integrated radiation of the coronal plasma line of sight, and the formula form is consistent with the coronal spectrum model Y = RX.

Secondly, based on the characteristic spectral line response of a single ion under given coronal multi-slit observation physical conditions, the characteristic spectral line response profile of a single ion under given coronal multi-slit observation physical conditions is calculated. In this embodiment and some other embodiments of the present invention, the characteristic spectral line response profile of a single ion under given coronal multi-slit observation physical conditions is calculated based on the Gaussian profile assumption, and its expression is:

Where x is the wavelength on the spectrum, corresponding to the detector pixel position; E(x) is the effective area of the observation device detector corresponding to a certain wavelength x (for the specific effective area curve, refer to the dotted line in Figure 3), which is a known observation device parameter; I _peak is the peak value of the characteristic spectral line response, v is the line-of-sight velocity, so the line-of-sight velocity v is associated with the response matrix, σ represents the broadening, thermal broadening and non-thermal broadening of the observation device, Δλ _inter ()) is the slit position, and in this embodiment and some other embodiments, the slit spacing is taken as The slit position is obviously a function of the slit number), that is, Δλ _inter (S) = 1.02 × n _slit , where n _slit is the slit number. When substituted into the above formula, it is taken as 0, 1, 2, 3, 4, corresponding to the 1st, 2nd, 3rd, 4th, and 5th slits respectively. For example, when n _slit = 1, it corresponds to the 2nd slit. Based on the above Gaussian profile formula, the spectral line response profile of a spectral line from the second slit is calculated. Compared with the spectral line from the first slit, it will be overall translated to the "right" (translation direction, or the direction of increasing wavelength) on the detector. As shown in Figure 4.

The broadening of the observation device, thermal broadening and non-thermal broadening contribute to the broadening of the Gaussian profile. The FWHM (full width at half maximum) Δλ of the Gaussian profile is shown as follows:

Where λ _I is the full width at half maximum (FWHM) of the observation device, specifically: λ ₀ is the stationary wavelength, i.e. the wavelength without Doppler shift, and Res is the spectral resolution of the observation equipment;

is the thermal broadening term, c is the speed of light, _Ti is the temperature of the corresponding ion, _mi is the mass of the corresponding ion, and _kB is the Boltzmann constant; is the non-thermal broadening term, ξ is the non-thermal velocity, which is related to temperature, but can be considered a constant within a certain temperature range, generally taken as 15km/s for the coronal temperature. After obtaining Δλ based on the broadening, thermal broadening and non-thermal broadening of the observation equipment, we have The σ in the above Gaussian profile I(x) can be obtained.

At this point, the characteristic spectral line response profile of any single ion under the given coronal multi-slit observation physical conditions can be obtained, and then the characteristic spectral line response profiles of all single ions under the given coronal multi-slit observation physical conditions can be superimposed to synthesize the synthetic spectral response of the coronal plasma under the given coronal multi-slit observation physical conditions. The synthetic spectral response corresponds to a column in the response matrix R, and the column position of the column corresponds to the given coronal multi-slit observation physical conditions used in the above calculations. Therefore, according to the definition of the response matrix R, the value of the element r _ij is obtained from the synthetic spectral response.

By traversing all the physical conditions of coronal multi-slit observation involved in the response matrix R and performing the above calculations, the complete response matrix R can be obtained.

Step S500, performing inversion calculation on the coronal spectrum model Y=RX to obtain the decoupled spectrum data of each slit.

Since the coronal spectrum model Y=RX is an underdetermined matrix, we use machine learning methods to solve it, for example, the LassoLars (Lasso Least angle Regressions) method in linear regression. In this embodiment, that is, in some other embodiments of the present invention, the inversion calculation of the coronal spectrum model Y=RX is to use machine learning methods to optimize the target Perform inversion calculation, where is the L2 norm of Y-RX, the second term is the L1 norm of X, and α is a hyperparameter in the machine learning method, which is used to control the sparsity of the solution.

The radiation matrix X of the coronal plasma is obtained by inverting the coronal spectrum model Y = RX. According to Y _s = R _s X, the spectrum data matrix Y _s of the s-th slit is obtained, where s = 1, 2, …, n, R _s is the response matrix of the s-th slit, with a dimension of M × Q. The element in the i-th row and j-th column of the response matrix R _s of the s-th slit is

Step S600, calculate Y-RX according to the radiation matrix X of the coronal plasma obtained by inversion calculation, and judge whether the response matrix R meets the spectral decoupling accuracy requirement according to the calculation result of Y-RX. If not, redefine the physical conditions and values of the coronal multi-slit observation, and construct the coronal spectrum model and perform calculation judgment, as shown by the dotted line in Figure 1.

In this embodiment and some other embodiments of the present invention, it is determined whether the response matrix R meets the spectral decoupling accuracy requirement based on the optimization judgment condition ||Y-RX||<β. If not, the physical conditions and values of the coronal multi-slit observation are re-determined, and the coronal spectrum model is constructed and calculated and judged. β is the spectral decoupling accuracy threshold, which can be pre-set based on experience or adjusted during the inversion process.

Example 2

This embodiment is used to explain in detail the method for obtaining the global distribution of coronal plasma parameters of the present invention. This embodiment is based on the coronal spectrum decoupling method in Example 1. By selecting the most appropriate parameters to obtain the most optimized decoupling results, the global distribution of coronal plasma parameters can be accurately and quickly obtained. The coronal plasma parameters include the density, temperature and radial velocity of the coronal plasma. The contents described in detail in Example 1 will not be described in detail in this embodiment.

This embodiment adopts the same method of corona multi-slit observation as in Embodiment 1, and can quickly scan the entire solar field in about 240 seconds. In addition, as shown in FIG3 , the slit direction in this embodiment is also different from that of the traditional slit. The traditional slit is generally in a north-south direction by default, and since the solar active regions are generally distributed in the middle and low latitudes, and there is no difference in longitude, in order to avoid the influence of multiple active regions on spectral observation, the slit design in an east-west direction is adopted in this embodiment.

In order to quickly and accurately obtain the global distribution of key parameters such as coronal plasma density, temperature, and radial velocity, this embodiment tests the parameter ranges of a large number of different response functions, and finally obtains a set of optimal inversion parameters to obtain the most optimized results.

The first thing to explain is the spectral resolution, or the broadening of the observation equipment. After testing, it was found that the spectral resolution has a certain lower limit. When the spectral resolution is lower than 1000, it is not possible to decouple well, because when the resolution is low, many spectral lines are difficult to distinguish, and the superposition of 5 slits makes it even more difficult to separate them, so we finally chose a resolution of about 2000.

The second is the selection of the observation band and target spectral line. The goal of this embodiment is to diagnose the coronal plasma (temperature, density and radial velocity) and obtain the global distribution of coronal plasma parameters. After testing based on experience, this embodiment selected ( Angstrom) band, as shown in Figure 5, Figure 5 shows the active zone spectrum of the effective area coupling, the band is The horizontal axis is wavelength, where the solid black lines mark the six spectral lines of interest for plasma diagnosis, and the solid gray lines mark other weak lines. The dotted line marks the outline of the effective area, the left vertical axis represents the value of the light intensity, and the right vertical axis represents the value of the effective area. The screening criteria for the target spectral lines in the observation band are first the spectral line intensity, which needs to be a strong line, and secondly, try to select spectral lines with large spacing between each other. Therefore, this embodiment combines the observation results of Hinode/EIS, the PSI model, and the spectral line intensity under different DEMs (active area, static area), and finally The band screens out six strong lines, namely and

Third, the selection of the slit spacing value. This embodiment tests the degree of contamination of the strong line under different slit spacing values (inter-slit spacing) on the spectrum. The slit spacing used in the test is The interval is 0.01. Selecting the appropriate slit spacing value can minimize the spectral overlap of different slits, making the decoupling process easier and more accurate. After testing, the optimal slit spacing is or or or However, because we have 6 strong lines, we need to do a series of plasma diagnostics. The slit spacing is also a function of the slit separation on the sky plane, which affects the scanning pattern. Therefore, we need to make some trade-offs and choose the best one after comprehensive consideration. By selecting this slit spacing, the entire solar field can be quickly scanned in 240 seconds.

Fourth, the value of the physical conditions for coronal multi-slit observations. The selection of the physical conditions for coronal multi-slit observations includes the value range and the value interval. The test found that the inversion cannot accept values with too small intervals, which first affects the accuracy of the results and secondly increases the inversion time. The temperature coverage range also requires different tests. It is not just necessary to cover the temperature of several target strong lines, so it is necessary to test an optimal temperature upper and lower limits within a certain range. The radial velocity range is estimated to get a rough range, and then repeated inversions are performed to get an optimal radial velocity range. The density can take the typical solar density upper and lower limits, but the specific value also needs to be tested. In the end, we chose a density range of 10 ⁷ cm ^-3 to 10 ¹³ cm ^-3 , with an interval of 0.5 (logN/cm ^-3 )); a velocity range of -100 to 100km/s, with an interval of 10km/s, and a temperature range of 10 ^5.0 K to 10 ^6.6 K, with an interval of 0.1 (logT/K). In the Lassolar method mentioned in Example 1, there is a super constant α which also needs to be tested to obtain an optimal value. Through testing, we found that the optimal value range is roughly between 10 ^-4 and 10 ^-6 .

The above parameters are the best combination of parameters obtained after global trade-offs, which results in the best decoupling results.

In addition, the spectral coupling data obtained by the multi-slit observation of the corona in this embodiment is one of using actual observation data, and another method is to use the data of the global coronal magnetohydrodynamic model developed by Predictive Science Inc. PSI, from which the spectral lines in the observation band are synthesized as the reference truth. Although there are actually hundreds or thousands of spectral lines in this observation band, there are only dozens of strong lines, so the interaction between them is mainly considered. Further, on the basis of the reference truth, Poisson noise is added to simulate the actual observation situation, and the spectral coupling data matrix Y can be obtained. This embodiment uses the above-mentioned simulated spectral coupling data matrix Y to test the superiority and reliability of the method of the present invention. Figure 6 is an example of the profile of the spectrum actually synthesized from the model of PSI company in the present invention. Three typical solar regions are: active region, quiet region, and limb, and their specific locations are marked in Figure 3. These spectral line profiles give 5 slit-image coupled spectra (dashed lines), the green solid line and the red solid line are the true value (True) and decoupling result (Inv) of a single slit contribution, respectively. The three figures from top to bottom correspond to the 3rd, 4th, and 1st slits, respectively. The horizontal and vertical axes are the same as Figure 5, representing wavelength and photon intensity, respectively.

Obtain global distribution of coronal plasma parameters, specifically, through accurate information on each specific spectral line ( and ), which enables a range of plasma diagnostics to be performed, consisting of and The global density distribution map can be obtained by comparing the ratio of Fe The global radial velocity distribution map (the first row in Figure 8) can be obtained by The global temperature distribution map can be obtained (the second row of Figure 8).

FIG7 is a comparison of the plasma diagnosis results of the present invention for the reference true value (True, first column) and the decoupled result (inverted, second column), and the third column is the JPDF (Joint Probability Distribution function). The global spectral line intensity distribution diagram, the second line The global spectral line intensity distribution diagram is shown in Figure 1. The x-axis and y-axis of the JPDF in the first and second rows are the true intensity and inverted intensity, respectively, which quantify the difference between the two. The third row is the global density distribution diagram obtained by the ratio of the above two. The x-axis of the JPDF is the logarithm of The strength ( The y-axis is the percentage error, which depicts the difference between the reference truth and the decoupled result.

Figure 8 is the same as Figure 7, but the first row is the global line-of-sight velocity ( Velocity) distribution, and the second line is the global temperature distribution (Weighted T). The horizontal axis of the JPDF of both is the same as that of Figure 7. The vertical axis of the JPDF corresponding to the radial velocity is the difference between the reference true value and the decoupling result, and that of the temperature is the percentage error.

In general, Figure 7 shows a comparison of spectra from three typical regions of the Sun, where True and Inv represent the reference truth and the decoupled result. It can be seen that the two are very consistent. The first column of Figures 7 and 8 shows a series of plasma diagnostic results (reference truth) in the model, including temperature, density and radial velocity. The second column shows the results of plasma diagnostics using the decoupled spectrum, and the third column shows the comparison between the two. For example, the first and second rows of Figure 7 show and The global intensity map of this density diagnostic line pair, the x and y axes of the third column correspond to the reference truth and the decoupling result, respectively. The third row of Figure 7 is a density map obtained by using the ratio of the intensity of the first and second rows. The third column shows the density percentage difference (y axis) between the reference truth and the decoupling result. Intensity variation (x-axis). The layout of Figure 7 is the same but the plasma parameters are changed to velocity and temperature, respectively. These results show that the results in the model are highly consistent with the results obtained by decoupling, indicating that we can provide a reliable method to quickly obtain global coronal plasma parameters.

The method of this embodiment constructs a coronal spectral model Y=RX according to the physical conditions and values of coronal multi-slit observations, calculates each element r _ij in the response matrix R to obtain the response matrix R, decouples the spectral coupling data obtained from the coronal multi-slit observations through inversion calculations, and obtains the global distribution of coronal plasma parameters through the decoupled spectra.

Example 3

In this embodiment, an electronic device is provided, as shown in Figure 9, and the electronic device includes at least one processor and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by at least one processor, and the instructions are executed by at least one processor so that the at least one processor can execute the above-mentioned coronal spectral decoupling method or the method for obtaining the global distribution of coronal plasma parameters.

Among them, the memory and the processor are connected in a bus manner, and the bus may include any number of interconnected buses and bridges, and the bus connects various circuits of one or more processors and memories together. The bus can also connect various other circuits such as peripheral devices, voltage regulators, and power management circuits through interfaces, which are all well known in the art. The interface provides an interface between the bus and the transceiver, such as a communication interface and a user interface. The transceiver can be one element or multiple elements, such as multiple receivers and transmitters, providing a unit for communicating with various other devices on a transmission medium. The data processed by the processor is transmitted on a wireless medium through an antenna, and further, the antenna also receives data and transmits the data to the processor.

The processor is responsible for managing the bus and general processing, and can also provide various functions, including timing, peripheral interfaces, voltage regulation, power management, and other control functions. Memory can be used to store data used by the processor when performing operations.

Example 4

In this embodiment, a computer-readable storage medium is provided, which stores a computer program. When the computer program is executed by a processor, it implements the above-mentioned coronal spectral decoupling method or the method embodiment for obtaining the global distribution of coronal plasma parameters.

Those skilled in the art can understand from the above description that all or part of the steps in the above-mentioned embodiment method can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a device (which can be a single-chip microcomputer, chip, etc.) or a processor (processor) execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes but is not limited to various media that can store program codes, such as USB flash drives, mobile hard disks, magnetic storage devices, and optical storage devices.

Space weather generated by solar activity (coronal mass ejections, flares, solar wind, etc.) can cause damage to human activities such as aerospace, communications, navigation, and electricity, so there is a saying that the corona is the source of space weather. The method provided by the present invention can decouple the extreme ultraviolet multi-slit spectrum and can quickly and accurately obtain the global distribution of key parameters of coronal plasma density, temperature, and radial velocity. Using the method of the present invention, all-weather monitoring of the physical properties and evolution of the global corona and promoting accurate prediction of space weather can be achieved.

This is reflected in three aspects: (1) Compared with MOSES, which can only obtain the radial velocity information of the corona, we can obtain the global distribution map of the coronal density, temperature, and radial velocity of the corona, which can provide important constraints for the origin and propagation model of coronal mass ejections (CMEs). In addition, using this method, the acquisition time of global plasma parameters will be reduced to a few minutes compared to the hours of traditional single-slit, and we are expected to conduct regular monitoring of the radial velocity of CMEs in the initial propagation stage. This is critical for accurately predicting whether and when CMEs will hit the Earth/planet. (2) The solar wind is also an important factor affecting the solar-terrestrial space environment. The corona temperature and radial velocity are critical for the identification of the solar wind source region. Using this method, we can obtain the global distribution of these parameters every few minutes, based on which we can efficiently identify the location of the solar wind source region on the solar disk. (3) Spectral observations in local areas show that parameters such as the radial velocity of the coronal spectrum may be significantly enhanced a few hours before the flare occurs. Our method can provide the radial velocity and its time evolution on the entire solar disk, based on which we can achieve efficient prediction of flares.

Those of ordinary skill in the art should further appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

The descriptions of the processes or structures corresponding to the above-mentioned figures have different emphases. For parts that are not described in detail in a certain process or structure, please refer to the relevant descriptions of other processes or structures.

The above embodiments are merely illustrative of the principles and effects of the present application and are not intended to limit the present application. Anyone familiar with the technology may modify or change the above embodiments without violating the spirit and scope of the present application. Therefore, all equivalent modifications or changes made by a person of ordinary skill in the art without departing from the spirit and technical ideas disclosed in the present application shall still be covered by the claims of the present application.

Claims (10)

1. A coronal spectral decoupling method for obtaining the global distribution of coronal plasma parameters, comprising: Acquire spectral coupling data obtained by coronal multi-slit observation; the observation area of coronal multi-slit observation is part or the entire full solar disk field of view, and the coronal multi-slit observation adopts multiple exposures of n slits, and multiple spectral coupling data are obtained by a single exposure, and each spectral coupling data includes spectral coupling data of n positions on the sun in the dispersion direction during a single exposure; Determine the physical conditions and values of the coronal multi-slit observation; the physical conditions of the coronal multi-slit observation include the physical conditions of the coronal body and the physical conditions of the observation equipment; the physical conditions of the coronal body include but are not limited to the temperature, density, and radial velocity of the coronal body; the physical conditions of the observation equipment include but are not limited to the number of slits, the slit spacing, and the observation band of the observation equipment used for the coronal multi-slit observation; According to the physical conditions and values of the coronal multi-slit observation, the coronal spectrum model Y=RX is constructed; among them, Y is a spectrum coupling data matrix of M×1 dimensions corresponding to a single spectrum coupling data, wherein the row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation device, M represents the number of detector pixel positions, and the element yi of the observation spectrum pixel matrix _Y represents the spectrum coupling data at the i-th detector pixel position, i=1, 2, ..., M; R is the response matrix corresponding to the observation band of the observation device, with a dimension of M×Q, wherein the row position represents the detector pixel position corresponding to the wavelength in the observation band of the observation device, the column position represents the value of the physical condition of the coronal multi-slit observation, Q is the number of values of the physical condition of the coronal multi-slit observation, and the element r _ij of the response matrix R represents the unit spectral coupling response at the i-th detector pixel position when the physical condition of the coronal multi-slit observation is equal to the value of the i-th column, j=1, 2, ..., Q; X is the Q×1-dimensional coronal plasma radiation matrix, whose row positions correspond to the column positions of the same serial number in the response matrix R. The element _xj of the coronal plasma radiation matrix X represents the line-of-sight integrated radiation of the coronal plasma when the physical conditions of the coronal multi-slit observation are equal to the value of the column of the response matrix R; Calculate each element r _ij in the response matrix R to obtain the response matrix R; The radiation matrix X of the coronal plasma is obtained by inverting the coronal spectrum model Y = RX. According to Y _s = R _s X, the spectrum data matrix Y _s of the s-th slit is obtained, where S = 1, 2, ..., n, R _s is the response matrix of the s-th slit, with a dimension of M × Q. The elements of the i-th row and column of the response matrix R _s of the s-th slit are According to the radiation matrix X of the coronal plasma obtained by inversion calculation, Y-RX is calculated. According to the calculation results of Y-RX, it is judged whether the response matrix R meets the spectral decoupling accuracy requirements. If not, the physical conditions and values of the coronal multi-slit observation are re-determined, and the coronal spectrum model is constructed and calculated and judged. 2. The method for decoupling the coronal spectrum according to claim 1, wherein: The redetermination of the physical conditions and values of the coronal multi-slit observation is carried out based on the decoupling accuracy and decoupling time of the coronal spectral decoupling. 3. The method for decoupling the coronal spectrum according to claim 1, wherein: Each element r _ij in the calculation response matrix R is obtained based on the contribution function C(T, λ, _Ne ) in the atomic physics database CHIANTI which is commonly used in the field of solar physics. 4. The method for decoupling the coronal spectrum according to claim 1, wherein: The inversion calculation of the corona spectrum model Y=RX is to use a machine learning method to optimize the target Perform inversion calculation, where is the L2 norm of Y-RX, the second term is the L1 norm of X, and α is a hyperparameter in the machine learning method, which is used to control the sparsity of the solution. 5. The method for decoupling the coronal spectrum according to claim 4, wherein: The machine learning method is the LassoLars method in linear regression. 6. A method for obtaining the global distribution of coronal plasma parameters, characterized in that the spectrum obtained by the coronal spectral decoupling method as described in one of claims 1 to 5 is used to obtain the global distribution of coronal plasma parameters, wherein the coronal plasma parameters include the density, temperature and radial velocity of the coronal plasma. 7. The method for obtaining global distribution of coronal plasma parameters as claimed in claim 6, wherein: The observational spectral data obtained by coronal multi-slit observations are obtained using multiple slit observations in the east-west direction. 8. The method for obtaining global distribution of coronal plasma parameters as claimed in claim 6, wherein during inversion, The density range is from 10 ⁷ cm ^-3 to 10 ¹³ cm ^-3 , and the interval of density is 0.5 (logN/cm ^-3 ); The temperature range is from 10 ⁵ K to 10 ^6.6 K, and the temperature interval is 0.1 (logT/K); The speed range is from -100km/s to 100km/s, with an interval of 10km/s; The range of the number of slits is 2-8; the range of the slit spacing is to The value interval is 0.01; The observation band is to The preferred inversion is 5 slits with a slit spacing of or or or or 9. An electronic device comprising: at least one processor; and, a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor so that the at least one processor can execute the coronal spectral decoupling method described in any one of claims 1-5, or can execute the method for obtaining the global distribution of coronal plasma parameters described in any one of claims 6-8. 10. A computer-readable storage medium storing a computer program, wherein the computer program, when executed by a processor, implements the coronal spectral decoupling method described in any one of claims 1-5, or can execute the method for obtaining the global distribution of coronal plasma parameters described in any one of claims 6-8.