Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we c...Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we calculate the parameters of ionospheric waves by applying the MMEM to numerously temporally approximate and spatially close global-positioning-system radio occultation total electron content profile triples provided by the unique clustered satellites flight between years 2006 and 2007 right after the constellation observing system for meteorology, ionosphere, and climate（COSMIC） mission launch. The results show that the amplitude of ionospheric waves increases at the low and high latitudes（~0.15 TECU） and decreases in the mid-latitudes（~0.05 TECU）. The vertical wavelength of the ionospheric waves increases in the mid-latitudes（e.g., ~50 km at altitudes of 200–250 km） and decreases at the low and high latitudes（e.g., ~35 km at altitudes of 200–250 km）.The horizontal wavelength shows a similar result（e.g., ~1400 km in the mid-latitudes and ~800 km at the low and high latitudes）.展开更多
The Binary star DataBase(BDB, http://bdb.inasan.ru) combines data from catalogs of binary and multiple stars of all observational types. There is a number of ways for variable stars to form or to be a part of binary o...The Binary star DataBase(BDB, http://bdb.inasan.ru) combines data from catalogs of binary and multiple stars of all observational types. There is a number of ways for variable stars to form or to be a part of binary or multiple systems. We describe how such stars are represented in the database.展开更多
We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, US...We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, USNO, FIRST and ROSAT. We then studied the discrimination of quasars from stars and the classification of quasars, stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.展开更多
Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are ...Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.展开更多
A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters o...A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to- noise ratios （SNR） on the measurement of the stellar atmospheric parameters （effective temperature Teff, surface gravity log g, and metaUicity [Fe/H]）. We show that ULySS is reliable for determining these parameters with medium-resolution spectra （R ～2000）. Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope （LAMOST）. The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline （SSPP）, and we derived precisions of 167 K, 0.34dex, and 0.16dex for Teff, logg and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectral template library （Version 1.0） of LAMOST, and will be deployed as basic ingredients for the LAMOST automated parametrization pipeline.展开更多
基金Supported by the National Natural Science Foundation of China under Grant Nos 41774158,41474129 and 41704148the Chinese Meridian Projectthe Youth Innovation Promotion Association of the Chinese Academy of Sciences under Grant No2011324
文摘Extracting and parameterizing ionospheric waves globally and statistically is a longstanding problem. Based on the multichannel maximum entropy method（MMEM） used for studying ionospheric waves by previous work, we calculate the parameters of ionospheric waves by applying the MMEM to numerously temporally approximate and spatially close global-positioning-system radio occultation total electron content profile triples provided by the unique clustered satellites flight between years 2006 and 2007 right after the constellation observing system for meteorology, ionosphere, and climate（COSMIC） mission launch. The results show that the amplitude of ionospheric waves increases at the low and high latitudes（~0.15 TECU） and decreases in the mid-latitudes（~0.05 TECU）. The vertical wavelength of the ionospheric waves increases in the mid-latitudes（e.g., ~50 km at altitudes of 200–250 km） and decreases at the low and high latitudes（e.g., ~35 km at altitudes of 200–250 km）.The horizontal wavelength shows a similar result（e.g., ~1400 km in the mid-latitudes and ~800 km at the low and high latitudes）.
基金supportedby the Russian Foundation of Basic Researches,projects 16–07–1162 and 18–02–00890Funding for the DPAC has been provided by nationalinstitutions, in particular the institutions participating inthe Gaia Multilateral Agreement
文摘The Binary star DataBase(BDB, http://bdb.inasan.ru) combines data from catalogs of binary and multiple stars of all observational types. There is a number of ways for variable stars to form or to be a part of binary or multiple systems. We describe how such stars are represented in the database.
基金Supported by the National Natural Science Foundation of ChinaThis paper is funded by the National Natural Science Foundation of China under grant under GrantNos. 10473013, 90412016 and 10778724 by the 863 project under Grant No. 2006AA01A120
文摘We introduced a decision tree method called Random Forests for multiwavelength data classification. The data were adopted from different databases, including the Sloan Digital Sky Survey （SDSS） Data Release five, USNO, FIRST and ROSAT. We then studied the discrimination of quasars from stars and the classification of quasars, stars and galaxies with the sample from optical and radio bands and with that from optical and X-ray bands. Moreover, feature selection and feature weighting based on Random Forests were investigated. The performances based on different input patterns were compared. The experimental results show that the random forest method is an effective method for astronomical object classification and can be applied to other classification problems faced in astronomy. In addition, Random Forests will show its superiorities due to its own merits, e.g. classification, feature selection, feature weighting as well as outlier detection.
基金supported by the National Natural Science Foundation of China (Grant Nos. 61073145, 41140027 and 41210104028)the Shanxi Province Natural Science Foundation (No. 2012011011-4)+1 种基金Scientific and Technological Innovation Programs of Higher Education Institutions in Shanxi, China (No. 20121011)the Shanxi Province Science Foundation for Youths (No. 2012021015-4)
文摘Effective extraction of data association rules can provide a reliable basis for classification of stellar spectra. The concept of stellar spectrum weighted itemsets and stellar spectrum weighted association rules are introduced, and the weight of a single property in the stellar spectrum is determined by information entropy. On that basis, a method is presented to mine the association rules of a stellar spectrum based on the weighted frequent pattern tree. Important properties of the spectral line are highlighted using this method. At the same time, the waveform of the whole spectrum is taken into account. The experimental results show that the data association rules of a stellar spectrum mined with this method are consistent with the main features of stellar spectral types.
基金Supported by the National Natural Science Foundation of China(Grant Nos. 10973021, 10778626 and 10933001)the National Basic Research Development Program of China (Grant No. 2007CB815404)the China Scholarship Council (CSC) (Grant No. 2007104275)
文摘A number of spectroscopic surveys have been carried out or are planned to study the origin of the Milky Way. Their exploitation requires reliable automated methods and softwares to measure the fundamental parameters of the stars. Adopting the ULySS package, we have tested the effect of different resolutions and signal-to- noise ratios （SNR） on the measurement of the stellar atmospheric parameters （effective temperature Teff, surface gravity log g, and metaUicity [Fe/H]）. We show that ULySS is reliable for determining these parameters with medium-resolution spectra （R ～2000）. Then, we applied the method to measure the parameters of 771 stars selected in the commissioning database of the Guoshoujing Telescope （LAMOST）. The results were compared with the SDSS/SEGUE Stellar Parameter Pipeline （SSPP）, and we derived precisions of 167 K, 0.34dex, and 0.16dex for Teff, logg and [Fe/H] respectively. Furthermore, 120 of these stars are selected to construct the primary stellar spectral template library （Version 1.0） of LAMOST, and will be deployed as basic ingredients for the LAMOST automated parametrization pipeline.
