CN113267455B - Fixed star parameter measuring method of large-scale astronomical telescope based on self-observation spectrum library - Google Patents
Fixed star parameter measuring method of large-scale astronomical telescope based on self-observation spectrum library Download PDFInfo
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Abstract
The invention provides a fixed star parameter measuring method of a large-scale astronomical telescope based on a self-observation spectrum library, which comprises the following steps: constructing an actual measurement spectrum library by using a theoretical spectrum library and other star tables and adopting a parameter marking transfer method; and the measured spectrum library is utilized to realize the parameter measurement of the observed spectrum by adopting a minimum chi-square linear interpolation method. The method for constructing the standard data set has good expansibility, and the constructed spectrum library has important value in the field of astronomy. The standard data set can play an important role in the fields of determination of physical parameters of spectrums, spectrum classification, star synthesis, spectrum teaching and the like.
Description
Technical Field
The invention relates to the technical field of astronomical optical telescopes, in particular to a fixed star parameter measuring method of a large-scale astronomical telescope based on a self-observation spectrum library.
Background
The atmospheric physical parameters of the stars mainly comprise effective temperature (Teff), surface gravity (log g), metal abundance ([ Fe/H ]), and the like, and are the basis for astronomers to research the structures, the kinematic rules, the chemical evolution and other aspects of the galaxy. With the development of large-scale sky-patrol projects, such as the snooker telescope (SDSS) in the united states and the ministry of guo (LAMOST) in china, automated star parameter measurement software has come into force.
There are many algorithms for estimating sidereal atmospheric physical parameters by spectra, and the algorithms are mainly classified into the following three categories:
(1) and (3) nearest neighbor matching, namely performing nearest neighbor matching on the spectrum to be detected and the theoretical spectrum, and determining the fixed star atmospheric physical parameters of the theoretical spectrum which is optimally matched as the atmospheric physical parameters of the spectrum to be detected. Common nearest neighbor matching methods include minimum chi-square value matching, cross correlation, bayesian, K-neighbor, and the like. Sidereal parameter measurement pipeline (sspp) of SDSS mainly employs a nearest neighbor matching algorithm.
(2) And a nonlinear regression method, namely establishing a mapping relation from the fixed star parameter to the parameter waveband spectrum, establishing a spectrum interpolation model, and enabling the spectrum generated by the interpolation model to be closest to the spectrum to be detected by searching the optimal parameter combination.
(3) Machine learning, training an Artificial Neural Network (ANN) with theoretical spectra or measured spectra of known parameters, and then using the trained network to estimate the parameters of the observed spectra.
In implementing the concept of the present invention, the inventors found that at least the following problems exist in the related art:
(1) the disadvantage of nearest neighbor matching: the nearest neighbor matching algorithm is the most common algorithm for measuring the star parameters and has good robustness. However, there are certain problems with the theoretical spectral library matching the observed spectrum. The theoretical spectral library is a calculation result based on a theoretical atmosphere model, and the atmosphere model is based on simplified processing and approximate assumptions of an actual physical process, such as assumptions of local thermodynamic equilibrium, plane parallelism, pressure broadening model assumptions and the like, and may be different from the actual physical process. In addition, the imperfection of the line table is a limitation of the theoretical spectrum library, and for a cold star with many molecular bands, the theoretical spectrum is difficult to ideally construct the actually observed spectral characteristics. Due to the limitation of a theoretical model, the space of star parameters acquired by astronomers is very limited and surrounds the sun-like star.
(2) Disadvantages of the non-linear regression method: first, building an interpolation model requires sufficient spatial sampling of the parameters, which is itself a very complex astronomical problem. Because of the limitations of the theoretical spectral library, it is impossible to construct all parameter spaces with the theoretical spectral library, and scientists have tried to build interpolation models after the actual measured spectrum and the theoretical spectrum complement each other. However, due to the limitation of the measured spectrum wavelength space, the built interpolation model has short spectrum wavelength coverage, and the application is very limited. In addition, the nearest neighbor parameters of the observed spectrum are found through an interpolation model, and the iteration to the local solution is easy. The problem of the algorithm iterating to a local solution can only be solved effectively if the initial assumption of the observed spectrum is given by (1).
(3) Disadvantages of machine learning: machine learning algorithms still rely on a set of data sets of labeled parameters, which is a problem of its own, and still a problem with standard data sets. The network trained by the theoretical spectrum may not be able to predict the parameters of the measured spectrum well. The actual measurement spectrum is used for training the network, the influence of the selected sample is large, and if the network is trained according to natural data distribution, the parameter prediction deviation of the special star with small occupation ratio is large. The application of the algorithm in the field of astronomy is still relatively limited.
In conclusion, the problem of the star parameter measurement algorithm is the problem of the standard data set. Standard data sets are a major and difficult problem in the field of astronomical research. Besides, the computation time of mass spectra is also an important issue to be solved. The astrolastic spectral parameter measurements of SDSS are still on the order of hundreds of thousands, so SSPP does not design a data-stream based operational model. The star spectrum of LAMOST is in the order of several million, and the operational efficiency of star parameter measurement is a problem to be solved.
Disclosure of Invention
In view of the above, the main objective of the present invention is to provide a method for measuring star parameters of a large-scale astronomical telescope based on a self-observation spectrum library, so as to partially solve at least one of the above technical problems.
In order to achieve the aim, the invention provides a method for measuring the star parameter of a large-scale astronomical telescope based on a self-observation spectrum library, which comprises the following steps:
constructing an actual measurement spectrum library by using a theoretical spectrum library and other star tables by adopting a parameter marking transfer method;
and the actually measured spectrum library is utilized to realize the parameter measurement of the observed spectrum by adopting a minimum chi-square linear interpolation method.
The measuring method further comprises the step of realizing multi-process distribution of data and storage of data results through the MySQL database, so that automatic measurement and analysis of massive spectrums are realized.
And when the user operates the field, the user only needs to specify a server number, a starting process number and an ending process number.
In a parameter space with small difference between a theoretical spectrum and an actually measured spectrum, the theoretical spectrum is taken as a center, a cluster of spectrums close to the theoretical spectrum are clustered to obtain a clustering center, and a theoretical spectrum parameter mark is transferred to the clustering center.
In the parameter space with large difference between the theoretical spectrum and the actual spectrum in a certain waveband, parameters determined by other high-resolution telescopes in other wavebands are utilized to carry out parameter marking transfer.
The parameter mark transfer method is characterized in that the same atmospheric physical parameters of the same star are assumed to be possessed at different spectral bands; for the spectrum with marked parameters, a set of high-quality actually-measured spectrum library is constructed by utilizing spectral clustering analysis in adjacent parameter spaces, and the parameter marks are obtained through statistics.
Wherein, the using the actually measured spectrum library to realize the parameter measurement of the observed spectrum by adopting the least chi-square linear interpolation method further comprises: and determining the parameters of any one of the stellar spectrums by utilizing the actually measured spectrum library through template matching.
Wherein the sidereal parameters include information of effective temperature, surface gravity, metal abundance and alpha element abundance.
Wherein, the spectrum is obtained by Guojintelescope observation.
Based on the technical scheme, compared with the prior art, the method for measuring the star parameter of the large-scale astronomical telescope based on the self-observation spectrum library has at least one of the following beneficial effects:
1. the method for constructing the standard data set has good expansibility, and the constructed spectrum library has important value in the field of astronomy. The standard data set can play an important role in the fields of determination of physical parameters of spectrums, spectrum classification, star synthesis, spectrum teaching and the like.
2. The data processing efficiency of the large-scale astronomical telescope is greatly improved based on the data flow processing mode of the database. The spectrum analysis of millions or even tens of millions can be completed in a short time, and the data release task of a large-scale tour project can be completed.
Drawings
FIG. 1 is a sample LAMOST cold star spectrum template constructed based on BT-Settl spectrum according to an embodiment of the present invention;
FIG. 2 is a sample spectrum template constructed by transferring APOGEE-Payne parameter labels to a resolution spectrum in LAMOS T according to an embodiment of the present invention;
fig. 3 is a database field of control parameter measurement pipeline according to an embodiment of the present invention.
Detailed Description
Based on the problems existing in the prior art, the technical problems to be solved by the invention are as follows:
(1) standard data set missing problem under theoretical model imperfection condition
Due to the imperfection of the theoretical model, the space of parameters that astronomers can obtain is very limited. Such as SDSS and LAMOST, only release star parameters of the FGK type. With the development of the cold star theoretical model, LAMOST starts to release a part of cold star parameters in this year. In the absence of the standard data set, it is very difficult to construct a set of standard data set, and the parameter markers of a star are determined by analyzing information of a plurality of wave bands of the star in combination with data resources of all astronomical telescopes internationally. Parameter flag transfer opens a window to solve the standard dataset missing problem. In a parameter space with smaller difference between a theoretical spectrum and an actually measured spectrum, the characteristic gradient of the believed theoretical spectrum can be selected, the cluster of actually measured spectra similar to the characteristics can be marked by the parameters of the theoretical spectrum, the cluster of actually measured spectra close to the theoretical spectrum is clustered by taking the theoretical spectrum as the center to obtain a clustering center, and the theoretical spectrum parameter mark is transferred to the clustering center, so that the constructed data set still retains the actually measured spectrum characteristics, and the problem of incomplete theoretical spectrum characteristics is solved. And (3) aiming at the parameter space with larger difference between the theoretical spectrum and the measured spectrum in the wave band, carrying out parameter marking transfer by using the parameters determined by other high-resolution telescopes in other wave bands. The method is mainly characterized in that the same star has the same atmospheric physical parameters in different spectral bands. For the spectrum with marked parameters, a set of high-quality actually measured spectrum library is constructed by utilizing spectral clustering analysis in the adjacent parameter space, and the parameter marks are obtained through statistics. Compared with the actually measured spectrum library collected by single observation, the spectrum library constructed by the method eliminates the influence of accidental factors of single observation.
(2) Data consistency problem for star parameter measurements
A data-driven stellar spectral parameter measurement method needs a set of spectral library with known parameters, and parameter information of any observation spectrum is determined by comparing the spectral library with the known parameters or by machine learning and other methods. The spectral library of known parameters must be consistent with the observed spectrum, otherwise determining the parameters of the observed spectrum from the spectral library of known parameters may introduce large errors. The data consistency mainly comprises consistency of resolution of the two sets of spectrums, consistency of wavelength coverage of the two sets of spectrums and consistency of spectral characteristics presented by the two sets of spectrums. For a theoretical spectrum library, the consistency of the resolution can be adjusted to be basically consistent through a convolution function, and the wavelength coverage range can generally cover the wave band of the observed spectrum. But because of the theoretical assumptions and imperfections in the line tables, the spectral characteristics of the theoretical spectra do not coincide with those of the measured spectra in certain bands. The measured spectrum library is limited by the observation instrument, such as the MILES and ELODIE measured spectrum library, and the wavelength coverage range of the spectrum is 390-680 nm. If the LAMOST spectrum needs to be matched with the two sets of actually measured spectrum libraries through a template, the own observed spectrum needs to be cut off, and the spectrum information of the red end is lost. The measured spectrum library constructed based on own observation can well solve the problem of data inconsistency, can ensure the consistency of spectral resolution, can also maximally utilize the information of the observed spectrum, and does not need overlong truncation to ensure the consistency of wavelength.
(3) Computation time problem of mass data
With the increase of astronomical data volume, the traditional manual interaction method is impossible to determine the parameters of the stars, and how to quickly and effectively complete the automatic analysis and measurement of the tens of millions of magnitude of stars is a problem to be solved by the invention. A data driving mode based on MySQL is designed, multi-batch parallel computation is realized through multi-process computation, the parameter computation efficiency of the stellar spectrum can be greatly improved, and the computation time is reduced.
In order to solve the technical problem, the invention discloses a method for measuring the stellar spectral parameters based on a self-constructed spectral library, wherein the system constructs an actual measurement spectral library based on own observation data by methods such as parameter mark transfer and the like; determining atmospheric physical parameters of any observation spectrum by using a self-constructed actual measurement spectrum library; and a plurality of general computers are used for realizing the automatic determination of the tens of millions of fixed star parameters by utilizing multi-process calculation. The method comprises the following steps: constructing an actual measurement spectrum library by using a theoretical spectrum library and other star tables by adopting a parameter marking transfer method; the measured spectrum library is utilized to realize the parameter measurement of the observed spectrum by adopting a minimum chi-square linear interpolation method; and multi-process distribution of data and storage of data results are realized through the MySQL database, so that automatic measurement and analysis of mass spectra are realized. The invention passes the data test of a GuoSaint telescope (LAMOST), and the method is applied to the parameter measurement of tens of millions of stellar spectrums of LAMOST.
Under the condition that a theoretical model is incomplete, an actual measurement spectrum library is constructed through a parameter marking transfer method; the fixed star parameter measurement is carried out by utilizing the observed actually measured spectrum library, so that the problem of inconsistent data in the parameter measurement is solved; a data stream processing mode based on a database is designed, and the problem of data distribution of a plurality of calculation tasks of massive spectrums is solved.
In order that the objects, technical solutions and advantages of the present invention will become more apparent, the present invention will be further described in detail with reference to the accompanying drawings in conjunction with the following specific embodiments.
The invention discloses a fixed star parameter measuring method of a large-scale astronomical telescope based on a self-observation spectrum library, which comprises the following steps:
step 1: constructing an actual measurement spectrum library by using a theoretical spectrum library and other star tables by adopting a parameter marking transfer method;
according to a further embodiment of the present invention, the construction of the library of measured spectra is a long-lasting task. With continuous observation of a large-scale astronomical telescope, mass data accumulated day and month is the premise for constructing an actual measurement spectrum library. A method for constructing the actually measured spectrum by parameter marking transfer is provided to solve the problem of how to construct the actually measured spectrum library under the condition that a theoretical model is incomplete. In a parameter space with smaller difference between a theoretical spectrum and an actually measured spectrum, the theoretical spectrum is taken as a center, a cluster of spectra close to the theoretical spectrum is clustered to obtain a clustering center, and a theoretical spectrum parameter mark is transferred to the clustering center. And aiming at the parameter space with larger difference between the theoretical spectrum and the measured spectrum in the wave band, parameter marking transfer is carried out by using parameters determined by other high-resolution telescopes in other wave bands. The method is mainly characterized in that the same star has the same atmospheric physical parameters in different spectral bands. For the spectrum with marked parameters, a set of high-quality actually-measured spectrum library is constructed by utilizing spectral clustering analysis in adjacent parameter spaces, and the parameter marks are obtained through statistics.
An example of an actually measured spectrum constructed based on the BT-Settl theoretical spectrum is shown in FIG. 1, wherein a dotted line is a clustering center spectrum of the LAMOST low-resolution spectrum, and a solid line is the BT-Settl theoretical spectrum. It can be seen that there is still a little difference between the actual measurement and the theory, because the molecular band structure of the cold star is complex, so that the theoretical spectrum calculation has many challenges.
By using the parameter mark transfer method, a spectrum library with more parameter marks can be constructed. FIG. 2 shows an example of the measured spectrum constructed by transfer labeling of APOGEE-Payne parameters onto the resolution spectrum in LAMOST. The solid line spectrum is the cluster center of the LAMOST spectrum in the near parameter space. The parameters are from the parameter tag of APOGEE-Payne. It can be seen from the figure that in addition to the three basic parameters Teff, log g and [ Fe/H ], the information of the abundance of alpha element [ A/Fe ] is also added.
Step 2: and the measured spectrum library is utilized to realize the parameter measurement of the observed spectrum by adopting a minimum chi-square linear interpolation method.
According to a further embodiment of the invention, the parameters of any one of the stellar spectrums are determined through template matching by using the constructed spectrum library. By adopting a chi-square linear interpolation algorithm, more accurate parameters can be obtained compared with the parameters directly matched to the grid points. Compared with a machine learning algorithm which needs large sample training, the algorithm is more direct and robust.
The measuring method disclosed by the invention also comprises the step of realizing multi-process distribution of data and storage of data results through the MySQL database, thereby realizing automatic measurement and analysis of mass spectra.
According to the further embodiment of the invention, a data stream processing mode based on a database is designed, and the problem of data distribution of a plurality of calculation tasks of mass spectra is solved. Meanwhile, the storage of the calculation result is facilitated. Fig. 3 shows the fields in the database that control the flow of data. Where server _ num indicates that the spectrum was computed by that machine and pro _ num indicates that the spectrum was computed by that process. The database-based data stream processing is simple and efficient to realize, and the data stream control is orderly. When the user runs the parameter measurement pipeline, the user only needs to specify the server number, the starting process number and the ending process number, for example, the python program is run under linux: nopuphon batch _ run _ last. py 0110 &, where the first 0 is the starting process number, 11 is the last process number to start, and the last 0 is the 1 st machine. After the instruction is operated, the 1 st machine starts 12 processes to perform mutually independent operation, and each spectrum corresponds to a unique (process number and machine number), so that the orderliness of calculated data is ensured.
The above-mentioned embodiments are intended to illustrate the objects, technical solutions and advantages of the present invention in further detail, and it should be understood that the above-mentioned embodiments are only exemplary embodiments of the present invention and are not intended to limit the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (6)
1. A fixed star parameter measuring method of a large-scale astronomical telescope based on a self-observation spectrum library is characterized by comprising the following steps:
constructing an actual measurement spectrum library by using a theoretical spectrum library and other star tables by adopting a parameter marking transfer method;
the measured spectrum library is utilized to realize the parameter measurement of the observed spectrum by adopting a minimum chi-square linear interpolation method;
the parameter mark transfer method includes that the same atmospheric physical parameters of the same star are assumed to be possessed by the same star in different spectral bands; for the spectrum with marked parameters, a set of high-quality actually measured spectrum library is constructed by utilizing spectral clustering analysis in adjacent parameter spaces and the parameter marks are obtained through statistics;
in a parameter space with small difference between a theoretical spectrum and an actually measured spectrum, clustering a cluster of spectra close to the theoretical spectrum by taking the theoretical spectrum as a center to obtain a clustering center, and transferring a theoretical spectrum parameter mark to the clustering center;
in the parameter space with large difference between the theoretical spectrum and the actual spectrum in a certain waveband, parameters determined by other high-resolution telescopes in other wavebands are utilized to carry out parameter marking transfer.
2. The method for measuring the sidereal parameters according to claim 1, further comprising the step of realizing multi-process distribution of data and storage of data results through a MySQL database, so as to realize automatic measurement and analysis of massive spectra.
3. The sidereal parameter measurement method according to claim 2, wherein the database includes a field for controlling data flow, and a user only needs to specify a server number, a start process number and an end process number when operating the field.
4. The method for measuring star parameters of claim 1, wherein said using the measured spectrum library to perform observed spectrum parameter measurement by using the least chi-squared linear interpolation method further comprises: and determining the parameters of any one of the stellar spectrums by utilizing the actually measured spectrum library through template matching.
5. The method of measuring the star parameters of claim 1, wherein the star parameters comprise information of effective temperature, surface gravity, metal abundance and alpha element abundance.
6. The method of measuring star parameters of claim 1, wherein the spectra are obtained by observation through a GuoSaizhiu telescope.
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