Spectrograph slit is conventionally used to enhance the spectral resolution and manage how much light can be allowed to enter spectrograph.The narrow slit provides a higher resolution but sacrifices efficiency of spec...Spectrograph slit is conventionally used to enhance the spectral resolution and manage how much light can be allowed to enter spectrograph.The narrow slit provides a higher resolution but sacrifices efficiency of spectrograph and results in a low signal to noise ratio(S/N) spectra product.We take GuoShouJing telescope as an example and carry out a series of experiments to study how its 2/3 slit mode affects the precision of stellar radial velocity measurement and atmosphere parameters estimate.By transforming the resolution and adding a Gaussian White Noise to the extremely high quality spectra from the Sloan Digital Sky Survey,we generate synthetic stellar spectra of various brightness with different S/Ns.Comparing the measurements on these noise added spectra with the original high quality ones,we summarize the influences of the 2/3 slit mode on the measurement accuracy of stellar radial velocity and atmospheric parameters.展开更多
This paper presents a novel spectroscopic method for searching for supernova candidates from massive galaxy spectra,which is expected to be applied to the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAM...This paper presents a novel spectroscopic method for searching for supernova candidates from massive galaxy spectra,which is expected to be applied to the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST).This method includes mainly five steps.The first step is spectral preprocessing,including removing spectral noise using wavelet transform,spectral de-redshift,etc.The second step is decomposition of galactic spectra;we can get the galaxy component and supernova component and calculate the Supernova Statistical Characterization Vector (SNSCV) of each galaxy spectrum.The third step is to decrease samples in all the galaxy spectral datasets according to SNSCV of each spectrum,and to use the LOF (Local Outlier Factor)-based outlier detection algorithm to obtain the preliminary selected spectral data.The fourth step is template matching by cross-correlation,according to the matched results we get the secondary selected spectral data.Finally,we choose the final supernova candidates manually through checking the spectral features characteristic of a supernova.By the spectroscopic method proposed in this paper,thirty-six supernova candidates have been detected in a dataset including 294843 galaxy spectra from the Sloan Digital Sky Survey Data Release 7.Nine of these objects are detected first and the other twenty-seven have been reported in other publications (fifteen of which are detected and reported first by us).The twenty-four new super-nova candidates include twenty Ia type supernova candidates,three Ic type supernova candidates and one II type supernova candidate.展开更多
Carbon stars and DZ white dwarfs are two types of rare objects in the Galaxy.In this paper,we have applied the label propagation algorithm to search for these two types of stars from Data Release Eight(DR8)of the Sloa...Carbon stars and DZ white dwarfs are two types of rare objects in the Galaxy.In this paper,we have applied the label propagation algorithm to search for these two types of stars from Data Release Eight(DR8)of the Sloan Digital Sky Survey(SDSS),which is verified to be efcient by calculating precision and recall.From nearly two million spectra including stars,galaxies and QSOs,we have found 260 new carbon stars in which 96 stars have been identified as dwarfs and 7 identified as giants,and 11 composition spectrum systems(each of them consists of a white dwarf and a carbon star).Similarly,using the label propagation method,we have obtained 29 new DZ white dwarfs from SDSS DR8.Compared with PCA reconstructed spectra,the 29 findings are typical DZ white dwarfs.We have also investigated their proper motions by comparing them with proper motion distribution of 9,374 white dwarfs,and found that they satisfy the current observed white dwarfs by SDSS generally have large proper motions.In addition,we have estimated their efective temperatures by fitting the polynomial relationship between efective temperature and g-r color of known DZ white dwarfs,and found 12 of the 29 new DZ white dwarfs are cool,in which nine are between 6,000 K and 6,600 K,and three are below 6,000 K.展开更多
We introduce an algorithm to solve the block-edge problem taking advantage of the two diferent sky splitting functions:HTM and HEALPix.We make the cross-match with the two functions,and then we obtain the union set of...We introduce an algorithm to solve the block-edge problem taking advantage of the two diferent sky splitting functions:HTM and HEALPix.We make the cross-match with the two functions,and then we obtain the union set of the two diferent sets.We use the ThreadPool technique to speed up the cross-match.In this way improved accuracy can be obtained on the cross-match.Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs.We give some ideas about solving the many-for-one situation occurred in the cross-match.展开更多
The spatial distributions of old neutron stars (NSs) with ages 109 to 1010 yr in our Galaxy are investigated by Monte Carlo simulation under two different initial random velocity models.It is found that the scale heig...The spatial distributions of old neutron stars (NSs) with ages 109 to 1010 yr in our Galaxy are investigated by Monte Carlo simulation under two different initial random velocity models.It is found that the scale heights of the distribution increase with the Galactic radial distance.The location of the peak of the NS distribution is closer to the Galactic center than that of their progenitors.The results from our detailed numerical analysis reveal that there is resemblance between the simulated old NS distribution and the structure of the observed HI disk.展开更多
Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In th...Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In this paper,we propose a novel automated approximate nearest neighbor search method based on unsupervised hashing learning for rare spectra retrieval.The proposed method employs a multilayer neural network using autoencoders as the local compact feature extractors.Autoencoders are trained with a non-gradient learning algorithm with graph Laplace regularization.This algorithm also simplifies the tuning of network architecture hyperparameters and the learning control hyperparameters.Meanwhile,the graph Laplace regularization can enhance the robustness by reducing the sensibility to noise.The proposed model is data-driven;thus,it can be viewed as a general-purpose retrieval model.The proposed model is evaluated in experiments and real-world applications where rare Otype stars and their subclass are retrieved from the dataset obtained from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(Guo Shoujing Telescope).The experimental and application results show that the proposed model outperformed the baseline methods,demonstrating the effectiveness of the proposed method in rare spectra retrieval tasks.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.11203045)
文摘Spectrograph slit is conventionally used to enhance the spectral resolution and manage how much light can be allowed to enter spectrograph.The narrow slit provides a higher resolution but sacrifices efficiency of spectrograph and results in a low signal to noise ratio(S/N) spectra product.We take GuoShouJing telescope as an example and carry out a series of experiments to study how its 2/3 slit mode affects the precision of stellar radial velocity measurement and atmosphere parameters estimate.By transforming the resolution and adding a Gaussian White Noise to the extremely high quality spectra from the Sloan Digital Sky Survey,we generate synthetic stellar spectra of various brightness with different S/Ns.Comparing the measurements on these noise added spectra with the original high quality ones,we summarize the influences of the 2/3 slit mode on the measurement accuracy of stellar radial velocity and atmospheric parameters.
基金supported by the National Natural Science Foundation of China (Grant Nos. 60773040,10973021)
文摘This paper presents a novel spectroscopic method for searching for supernova candidates from massive galaxy spectra,which is expected to be applied to the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST).This method includes mainly five steps.The first step is spectral preprocessing,including removing spectral noise using wavelet transform,spectral de-redshift,etc.The second step is decomposition of galactic spectra;we can get the galaxy component and supernova component and calculate the Supernova Statistical Characterization Vector (SNSCV) of each galaxy spectrum.The third step is to decrease samples in all the galaxy spectral datasets according to SNSCV of each spectrum,and to use the LOF (Local Outlier Factor)-based outlier detection algorithm to obtain the preliminary selected spectral data.The fourth step is template matching by cross-correlation,according to the matched results we get the secondary selected spectral data.Finally,we choose the final supernova candidates manually through checking the spectral features characteristic of a supernova.By the spectroscopic method proposed in this paper,thirty-six supernova candidates have been detected in a dataset including 294843 galaxy spectra from the Sloan Digital Sky Survey Data Release 7.Nine of these objects are detected first and the other twenty-seven have been reported in other publications (fifteen of which are detected and reported first by us).The twenty-four new super-nova candidates include twenty Ia type supernova candidates,three Ic type supernova candidates and one II type supernova candidate.
基金funded by the National Natural Science Foundation of China(Grant Nos.10973021 and 11303036)SDSS-III has been provided by the Alfred P.Sloan Foundation+2 种基金the Participating Institutionsthe National Science Foundationthe U.S.Department of Energy Ofce of Science
文摘Carbon stars and DZ white dwarfs are two types of rare objects in the Galaxy.In this paper,we have applied the label propagation algorithm to search for these two types of stars from Data Release Eight(DR8)of the Sloan Digital Sky Survey(SDSS),which is verified to be efcient by calculating precision and recall.From nearly two million spectra including stars,galaxies and QSOs,we have found 260 new carbon stars in which 96 stars have been identified as dwarfs and 7 identified as giants,and 11 composition spectrum systems(each of them consists of a white dwarf and a carbon star).Similarly,using the label propagation method,we have obtained 29 new DZ white dwarfs from SDSS DR8.Compared with PCA reconstructed spectra,the 29 findings are typical DZ white dwarfs.We have also investigated their proper motions by comparing them with proper motion distribution of 9,374 white dwarfs,and found that they satisfy the current observed white dwarfs by SDSS generally have large proper motions.In addition,we have estimated their efective temperatures by fitting the polynomial relationship between efective temperature and g-r color of known DZ white dwarfs,and found 12 of the 29 new DZ white dwarfs are cool,in which nine are between 6,000 K and 6,600 K,and three are below 6,000 K.
基金supported by the National Natural Science Foundation of China(Grant Nos.10973021,11078013 and 11233004)
文摘We introduce an algorithm to solve the block-edge problem taking advantage of the two diferent sky splitting functions:HTM and HEALPix.We make the cross-match with the two functions,and then we obtain the union set of the two diferent sets.We use the ThreadPool technique to speed up the cross-match.In this way improved accuracy can be obtained on the cross-match.Our experiments show that this algorithm has a remarkable performance superiority compared with the previous ones and can be applied to the cross-match between large-scale catalogs.We give some ideas about solving the many-for-one situation occurred in the cross-match.
基金supported by the National Natural Science Foundation of China (Grant Nos. 10903010,10778611,10773017,10973021 and10573026)the National Basic Research Program of China (Grant No.2009CB824800)
文摘The spatial distributions of old neutron stars (NSs) with ages 109 to 1010 yr in our Galaxy are investigated by Monte Carlo simulation under two different initial random velocity models.It is found that the scale heights of the distribution increase with the Galactic radial distance.The location of the peak of the NS distribution is closer to the Galactic center than that of their progenitors.The results from our detailed numerical analysis reveal that there is resemblance between the simulated old NS distribution and the structure of the observed HI disk.
基金supported by the Postdoctoral Science Foundation of China(Grant No.2020M682348)the Key Research Foundation of Henan Higher Education Institutions(Grant No.21A520002)+1 种基金the National Key Research and Development Program of China(Grant No.2018AAA0100203)the Joint Research Fund in Astronomy(Grant No.U1531242)under a cooperative agreement between the National Natural Science Foundation of China and the Chinese Academy of Sciences(CAS)。
文摘Searching for rare astronomical objects based on spectral data is similar to finding needles in a haystack owing to their rarity and the immense data volume gathered from large astronomical spectroscopic surveys.In this paper,we propose a novel automated approximate nearest neighbor search method based on unsupervised hashing learning for rare spectra retrieval.The proposed method employs a multilayer neural network using autoencoders as the local compact feature extractors.Autoencoders are trained with a non-gradient learning algorithm with graph Laplace regularization.This algorithm also simplifies the tuning of network architecture hyperparameters and the learning control hyperparameters.Meanwhile,the graph Laplace regularization can enhance the robustness by reducing the sensibility to noise.The proposed model is data-driven;thus,it can be viewed as a general-purpose retrieval model.The proposed model is evaluated in experiments and real-world applications where rare Otype stars and their subclass are retrieved from the dataset obtained from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope(Guo Shoujing Telescope).The experimental and application results show that the proposed model outperformed the baseline methods,demonstrating the effectiveness of the proposed method in rare spectra retrieval tasks.
