Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional meth...Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.展开更多
Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of t...Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.展开更多
With the application of advanced astronomical technologies, equipments and methods all over the world, astronomical observations cover the range from radio, infrared, visible light, ultraviolet, X-ray and gamma-ray ba...With the application of advanced astronomical technologies, equipments and methods all over the world, astronomical observations cover the range from radio, infrared, visible light, ultraviolet, X-ray and gamma-ray bands, and enter into the era of full wavelength astronomy. How to effectively integrate data from different ground- and space-based observation equipments, different observers, different bands and different observation times, requires data fusion technology. In this paper we introduce a cross-match tool that is developed in the Python language, is based on the PostgreSQL database and uses Q3C as the core index, facilitating the cross-match work of massive astronomical data. It provides four different cross- match functions, namely： （I） cross-match of the custom error range; （II） cross-match of catalog errors; （III） cross-match based on the elliptic error range; （IV） cross-match of the nearest neighbor algorithm. The resulting cross-matched set provides a good foundation for subsequent data mining and statistics based on multiwavelength data. The most advantageous aspect of this tool is a user-oriented tool applied locally by users. By means of this tool, users can easily create their own databases, manage their own data and cross- match databases according to their requirements. In addition, this tool is also able to transfer data from one database into another database. More importantly, it is easy to get started with the tool and it can be used by astronomers without writing any code.展开更多
We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU a...We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database.We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey(CRAFTS),which resulted in quasi-real-time processing.The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients(RRATs)and fast radio bursts(FRBs).We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band(UWB)receiver.GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB.GSP also discovered 13 new pulsars.We measured the computational efficiency of GSP to be~120 times faster than the original PRESTO and~60 times faster than an MPI-parallelized version of PRESTO.展开更多
The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In ...The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In this paper, the software-defined network technology is applied to the Xinjiang Astronomical Observatory Data Center Network(XAODCN). Specifically, a novel reconfiguration method is proposed to realise the software-defined Xinjiang Astronomical Observatory Data Center Network(SDXAO-DCN), and a network model is constructed. To overcome the congestion problem, a traffic load-balancing algorithm is designed for fast transmission of the service traffic by combining three factors: network structure, congestion level and transmission service. The proposed algorithm is compared with current commonly load-balancing algorithms which are used in data center to verify its efficiency. Simulation experiments show that the algorithm improved transmission performance and transmission quality for the SDXAO-DCN.展开更多
We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via...We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via HEASOFT),we extracted light curves for each observational ID and for their aggregation.Countrate histograms were fitted using various statistical distributions;fit quality was assessed by chi-squared and the Bayesian Information Criterion.The first observational segment is best described by a Gaussian distribution(χ^(2)=68.4;BIC=7651.2),and the second by a Poisson distribution(χ^(2)=33.5;BIC=4413.3).When all segments are combined,the lognormal model provides the superior fit(χ^(2)=541.9;BIC=34365.5),indicating that the full data set’s count rates exhibit the skewness expected from a multiplicative process.These findings demonstrate that while individual time intervals conform to discrete or symmetric statistics,the collective emission profile across multiple observations is better captured by a lognormal distribution,consistent with complex,compounded variability in GRB afterglows.展开更多
Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beam...Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beamoffset observation results,we obtain polarization profiles of 682 pulsars from observations by the Five-hundredmeter Aperture Spherical radio Telescope(FAST)duringthe Galactic Plane Pulsar Snapshot survey and other normal FAST projects.Among them,polarization profiles of about 460 pulsars are observed for the first time.The profiles exhibit diverse features.Some pulsars have a polarization position angle curve with a good S-shaped swing,some with orthogonal modes;some have components with highly linearly polarized components or strong circularly polarized components;some have a very wide profile,coming from an aligned rotator,and some have an interpulse from a perpendicular rotator;some wide profiles are caused by interstellar scattering.We derive geometric parameters for 190 pulsars from the S-shaped position angle curves or with orthogonal modes.We find that the linear and circular polarization or the widths of pulse profiles have various frequency dependencies.Pulsars with a large fraction of linear polarization are more likely to have a large Edot.展开更多
This paper presents a database of the spectroscopic-and photometric-spectral energy distributions(spec-SEDs and phot-SEDs respectively)of the progenitors of core-collapse supernovae(CCSNe).Both binary-and single-star ...This paper presents a database of the spectroscopic-and photometric-spectral energy distributions(spec-SEDs and phot-SEDs respectively)of the progenitors of core-collapse supernovae(CCSNe).Both binary-and single-star progenitors are included in the database.The database covers the initial metallicity(Z)range of 0.0001-0.03,mass range of 8-25 M⊙,binary mass ratio range of 0-1,and orbital period range of 0.1-10000 d.The low-resolution spec-SEDs and phot-SEDs of single-and binary-star CCSN progenitors are included in the database.These data can be used for studying the basic parameters,e.g.,metallicity,age,and initial and final masses of CCSN progenitors.It can also be used for studying the effects of different factors on the determination of parameters of CCSN progenitors.When the database is utilized for fitting the SEDs of binary-star CCSN progenitors,it is strongly suggested to determine the metallicity and orbital period in advance,but this is not necessary for single-star progenitors.展开更多
We present the database of maser sources in H2 O, OH and Si O lines that can be used to identify and study variable stars at evolved stages. Detecting the maser emission in H2 O, OH and Si O molecules toward infrared-...We present the database of maser sources in H2 O, OH and Si O lines that can be used to identify and study variable stars at evolved stages. Detecting the maser emission in H2 O, OH and Si O molecules toward infrared-excess objects is one of the methods for identifing long-period variables(LPVs, including miras and semiregulars), because these stars exhibit maser activity in their circumstellar shells. Our sample contains 1803 known LPV objects. Forty-six percent of these stars(832 objects) manifest maser emission in the line of at least one molecule: H2 O, OH or Si O. We use the database of circumstellar masers in order to search for LPVs which are not included in the General Catalogue of Variable Stars(GCVS). Our database contains 4806 objects(3866 objects without associations in GCVS) with maser detection in at least one molecule. Therefore it is possible to use the database in order to locate and study the large sample of LPV stars. The database can be accessed at http://maserdb.net.展开更多
We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital we...We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital weighting techniques to plot the 2D pattern of the PAF.The radio frequency part of the demonstrator includes a 4×4 linearly polarized microstrip antenna array,all of which is connected in series with a low-noise amplifier.The signals from the central 4×2 array elements are injected into a radio frequency system-on-chip digital board,which can receive eight inputs with a bandwidth of 512 MHz.Combining the principle of undersampling,the beamforming is completed at a frequency of 1.25 GHz for the offline data,and a 2D image of the beam is plotted using beam scanning technology.展开更多
天文观测数据是天文研究的基础,但传统的集中式数据检索方法已难以满足日益增长的海量天文数据的高性能检索和查询需求.提出了一种基于Elastic Search分布式搜索引擎,通过River机制对现有的海量FITS(Flexible Image Transport System)...天文观测数据是天文研究的基础,但传统的集中式数据检索方法已难以满足日益增长的海量天文数据的高性能检索和查询需求.提出了一种基于Elastic Search分布式搜索引擎,通过River机制对现有的海量FITS(Flexible Image Transport System)数据进行索引构建,从而实现海量FITS数据高效检索的方法,并讨论了其中的近实时检索和查询的关键技术.实测结果表明,在百万到千万级的天文数据量下,该方法可获得极高的检索性能,并能够很方便地集成到现有的天文数据归档系统中,完全可以满足当前国内各类望远镜系统天文数据的归档要求.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
先进天基太阳天文台(Advanced Space-based Solar Observatory,ASO-S)卫星是我国首颗太阳观测卫星,主要观测太阳耀斑和日冕物质抛射以及产生它们的磁场结构.ASO-S卫星的科学应用系统是科学卫星工程的6大系统之一,它连接科学用户和卫星数...先进天基太阳天文台(Advanced Space-based Solar Observatory,ASO-S)卫星是我国首颗太阳观测卫星,主要观测太阳耀斑和日冕物质抛射以及产生它们的磁场结构.ASO-S卫星的科学应用系统是科学卫星工程的6大系统之一,它连接科学用户和卫星数据,为将卫星的科学数据转化为科学成果提供保障.科学应用系统的数据库是连接软件与海量数据的枢纽,为科学数据生产和用户服务及运行提供数据层的支撑.介绍了科学应用系统的数据库架构设计、数据库的选择以及数据库性能优化和表样例.这里的数据库包括观测计划、工程参数、运维日志、科学数据、定标数据和特征事件识别等数据库.这些数据库的建设将为ASO-S卫星工程科学应用系统的顺利运行提供数据支撑,也可以为未来其他科学卫星类似数据库的搭建提供参考和借鉴.展开更多
We combine K-nearest neighbors(KNN)with a genetic algorithm(GA)for photometric redshift estimation of quasars,short for GeneticKNN,which is a weighted KNN approach supported by a GA.This approach has two improvements ...We combine K-nearest neighbors(KNN)with a genetic algorithm(GA)for photometric redshift estimation of quasars,short for GeneticKNN,which is a weighted KNN approach supported by a GA.This approach has two improvements compared to KNN:one is the feature weighted by GA;the other is that the predicted redshift is not the redshift average of K neighbors but the weighted average of median and mean of redshifts for K neighbors,i.e.p×zmedian+(1-p)×zmean.Based on the SDSS and SDSS-WISE quasar samples,we explore the performance of GeneticKNN for photometric redshift estimation,comparing with the other six traditional machine learning methods,i.e.the least absolute shrinkage and selection operator(LASSO),support vector regression(SVR),multi-layer perceptrons(MLP),XGBoost,KNN and random forest.KNN and random forest show their superiority.Considering the easy implementation of KNN,we make improvement on KNN as GeneticKNN and apply GeneticKNN on photometric redshift estimation of quasars.Finally the performance of GeneticKNN is better than that of LASSO,SVR,MLP,XGBoost,KNN and random forest for all cases.Moreover the accuracy is better with the additional WISE magnitudes for the same method.展开更多
基金supported by the National Natural Science Foundation of China(NSFC,Grant Nos.12273077,72101068,12373110,and 12103070)National Key Research and Development Program of China under grants(2022YFF0712400,2022YFF0711500)+2 种基金the 14th Five-year Informatization Plan of Chinese Academy of Sciences(CAS-WX2021SF-0204)supported by Astronomical Big Data Joint Research Centerco-founded by National Astronomical Observatories,Chinese Academy of Sciences and Alibaba Cloud。
文摘Astronomical knowledge entities,such as celestial object identifiers,are crucial for literature retrieval and knowledge graph construction,and other research and applications in the field of astronomy.Traditional methods of extracting knowledge entities from texts face numerous challenging obstacles that are difficult to overcome.Consequently,there is a pressing need for improved methods to efficiently extract them.This study explores the potential of pre-trained Large Language Models(LLMs)to perform astronomical knowledge entity extraction(KEE)task from astrophysical journal articles using prompts.We propose a prompting strategy called PromptKEE,which includes five prompt elements,and design eight combination prompts based on them.We select four representative LLMs(Llama-2-70B,GPT-3.5,GPT-4,and Claude 2)and attempt to extract the most typical astronomical knowledge entities,celestial object identifiers and telescope names,from astronomical journal articles using these eight combination prompts.To accommodate their token limitations,we construct two data sets:the full texts and paragraph collections of 30 articles.Leveraging the eight prompts,we test on full texts with GPT-4and Claude 2,on paragraph collections with all LLMs.The experimental results demonstrate that pre-trained LLMs show significant potential in performing KEE tasks,but their performance varies on the two data sets.Furthermore,we analyze some important factors that influence the performance of LLMs in entity extraction and provide insights for future KEE tasks in astrophysical articles using LLMs.Finally,compared to other methods of KEE,LLMs exhibit strong competitiveness in multiple aspects.
基金supported by the National Key R&D Program of China (Nos. 2022YFF0711502 and 2021YFC2203502)the National Natural Science Foundation of China (NSFC)(12173077 and 12003062)+6 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region (2022D14020)the Tianshan Talent Project of Xinjiang Uygur Autonomous Region(2022TSYCCX0095)the Scientific Instrument Developing Project of the Chinese Academy of Sciences (grant No. PTYQ2022YZZD01)China National Astronomical Data Center (NADC)the Operation,Maintenance and Upgrading Fund for Astronomical Telescopes and Facility Instruments,budgeted from the Ministry of Finance of China (MOF)and administrated by the Chinese Academy of Sciences (CAS)Natural Science Foundation of Xinjiang Uygur Autonomous Region (2022D01A360)supported by Astronomical Big Data Joint Research Center,co-founded by National Astronomical Observatories,Chinese Academy of Sciences。
文摘Cross-matching is a key technique to achieve fusion of multi-band astronomical catalogs. Due to different equipment such as various astronomical telescopes, the existence of measurement errors, and proper motions of the celestial bodies, the same celestial object will have different positions in different catalogs, making it difficult to integrate multi-band or full-band astronomical data. In this study, we propose an online cross-matching method based on pseudo-spherical indexing techniques and develop a service combining with high performance computing system(Taurus) to improve cross-matching efficiency, which is designed for the Data Center of Xinjiang Astronomical Observatory. Specifically, we use Quad Tree Cube to divide the spherical blocks of the celestial object and map the 2D space composed of R.A. and decl. to 1D space and achieve correspondence between real celestial objects and spherical patches. Finally, we verify the performance of the service using Gaia 3 and PPMXL catalogs. Meanwhile, we send the matching results to VO tools-Topcat and Aladin respectively to get visual results. The experimental results show that the service effectively solves the speed bottleneck problem of crossmatching caused by frequent I/O, and significantly improves the retrieval and matching speed of massive astronomical data.
基金funded by the National Key Basic Research Program of China (2014CB845700)the National Natural Science Foundation of China (NSFC, Grant Nos. 61272272, 11178021 and 11033001)NSFC-Texas A&M University Joint Research Program (No. 11411120219)
文摘With the application of advanced astronomical technologies, equipments and methods all over the world, astronomical observations cover the range from radio, infrared, visible light, ultraviolet, X-ray and gamma-ray bands, and enter into the era of full wavelength astronomy. How to effectively integrate data from different ground- and space-based observation equipments, different observers, different bands and different observation times, requires data fusion technology. In this paper we introduce a cross-match tool that is developed in the Python language, is based on the PostgreSQL database and uses Q3C as the core index, facilitating the cross-match work of massive astronomical data. It provides four different cross- match functions, namely： （I） cross-match of the custom error range; （II） cross-match of catalog errors; （III） cross-match based on the elliptic error range; （IV） cross-match of the nearest neighbor algorithm. The resulting cross-matched set provides a good foundation for subsequent data mining and statistics based on multiwavelength data. The most advantageous aspect of this tool is a user-oriented tool applied locally by users. By means of this tool, users can easily create their own databases, manage their own data and cross- match databases according to their requirements. In addition, this tool is also able to transfer data from one database into another database. More importantly, it is easy to get started with the tool and it can be used by astronomers without writing any code.
基金supported by the National Natural Science Foundation of China(NSFCGrant Nos.11988101,11725313,11690024,12041303,U1731238,U2031117,U1831131 and U1831207)+2 种基金supported by the Science and Technology Foundation of Guizhou Province(No.LKS[2010]38)support by the Youth Innovation Promotion Association CAS(id.2021055)cultivation project for FAST scientific payoff and research achievement of CAMS-CAS。
文摘We developed a GPU based single-pulse search pipeline(GSP)with a candidate-archiving database.Largely based upon the infrastructure of the open source PulsaR Exploration and Search Toolkit(PRESTO),GSP implements GPU acceleration of the de-dispersion and integrates a candidate-archiving database.We applied GSP to the data streams from the Commensal Radio Astronomy FAST Survey(CRAFTS),which resulted in quasi-real-time processing.The integrated candidate database facilitates synergistic usage of multiple machine-learning tools and thus improves efficient identification of radio pulsars such as rotating radio transients(RRATs)and fast radio bursts(FRBs).We first tested GSP on pilot CRAFTS observations with the FAST Ultra-Wide Band(UWB)receiver.GSP detected all pulsars known from the the Parkes multibeam pulsar survey in the corresponding sky area covered by the FAST-UWB.GSP also discovered 13 new pulsars.We measured the computational efficiency of GSP to be~120 times faster than the original PRESTO and~60 times faster than an MPI-parallelized version of PRESTO.
基金supported by National Key R&D Program of China No.2021YFC2203502the National Natural Science Foundation of China (NSFC)(11803080,12173077,11873082,12003062)+2 种基金the Tianshan Innovation Team Plan of Xinjiang Uygur Autonomous Region (2022D14020)the Youth Innovation Promotion Association CASNational Key R&D Program of China No.2018 YFA0404704。
文摘The Xinjiang Astronomical Observatory Data Center faces issues related to delay-affected services. As a result, these services cannot be implemented in a timely manner due to the overloading of transmission links. In this paper, the software-defined network technology is applied to the Xinjiang Astronomical Observatory Data Center Network(XAODCN). Specifically, a novel reconfiguration method is proposed to realise the software-defined Xinjiang Astronomical Observatory Data Center Network(SDXAO-DCN), and a network model is constructed. To overcome the congestion problem, a traffic load-balancing algorithm is designed for fast transmission of the service traffic by combining three factors: network structure, congestion level and transmission service. The proposed algorithm is compared with current commonly load-balancing algorithms which are used in data center to verify its efficiency. Simulation experiments show that the algorithm improved transmission performance and transmission quality for the SDXAO-DCN.
文摘We perform a time-resolved statistical study of GRB 221009A’s X-ray emission using Swift XRT Photon Counting and Windowed Timing data.After standard reduction(barycentric correction,pile-up,background subtraction via HEASOFT),we extracted light curves for each observational ID and for their aggregation.Countrate histograms were fitted using various statistical distributions;fit quality was assessed by chi-squared and the Bayesian Information Criterion.The first observational segment is best described by a Gaussian distribution(χ^(2)=68.4;BIC=7651.2),and the second by a Poisson distribution(χ^(2)=33.5;BIC=4413.3).When all segments are combined,the lognormal model provides the superior fit(χ^(2)=541.9;BIC=34365.5),indicating that the full data set’s count rates exhibit the skewness expected from a multiplicative process.These findings demonstrate that while individual time intervals conform to discrete or symmetric statistics,the collective emission profile across multiple observations is better captured by a lognormal distribution,consistent with complex,compounded variability in GRB afterglows.
基金supported by the National Natural Science Foundation of China(NSFC,grant Nos.11988101 and 11833009),supported by the National Natural Science Foundation of China(NSFC,grant No.U2031115)supported by the National Key R&D Program of China(No.2021YFA1600401 and 2021YFA1600400)+1 种基金National Natural Science Foundation of China(NSFC,grant Nos.11873058 and 12133004)the National SKA program of China(No.2020SKA0120200)。
文摘Pulsar polarization profiles form a very basic database for understanding the emission processes in a pulsar magnetosphere.After careful polarization calibration of the 19-beam L-band receiver and verification of beamoffset observation results,we obtain polarization profiles of 682 pulsars from observations by the Five-hundredmeter Aperture Spherical radio Telescope(FAST)duringthe Galactic Plane Pulsar Snapshot survey and other normal FAST projects.Among them,polarization profiles of about 460 pulsars are observed for the first time.The profiles exhibit diverse features.Some pulsars have a polarization position angle curve with a good S-shaped swing,some with orthogonal modes;some have components with highly linearly polarized components or strong circularly polarized components;some have a very wide profile,coming from an aligned rotator,and some have an interpulse from a perpendicular rotator;some wide profiles are caused by interstellar scattering.We derive geometric parameters for 190 pulsars from the S-shaped position angle curves or with orthogonal modes.We find that the linear and circular polarization or the widths of pulse profiles have various frequency dependencies.Pulsars with a large fraction of linear polarization are more likely to have a large Edot.
基金supported by the National Natural Science Foundation of China(Grant No.11863002)Sino-German Cooperation Project(Grant No.GZ 1284)Yunnan Academician Workstation of Wang Jingxiu(Grant No.202005AF150025)。
文摘This paper presents a database of the spectroscopic-and photometric-spectral energy distributions(spec-SEDs and phot-SEDs respectively)of the progenitors of core-collapse supernovae(CCSNe).Both binary-and single-star progenitors are included in the database.The database covers the initial metallicity(Z)range of 0.0001-0.03,mass range of 8-25 M⊙,binary mass ratio range of 0-1,and orbital period range of 0.1-10000 d.The low-resolution spec-SEDs and phot-SEDs of single-and binary-star CCSN progenitors are included in the database.These data can be used for studying the basic parameters,e.g.,metallicity,age,and initial and final masses of CCSN progenitors.It can also be used for studying the effects of different factors on the determination of parameters of CCSN progenitors.When the database is utilized for fitting the SEDs of binary-star CCSN progenitors,it is strongly suggested to determine the metallicity and orbital period in advance,but this is not necessary for single-star progenitors.
基金funded by the Russian Foundationfor Basic Research through research project 18-32-00605supported by Russian Science Foundation grant18-12-00193supported by Act 211 of theGovernment of the Russian Federation, agreement No.02.A03.21.0006
文摘We present the database of maser sources in H2 O, OH and Si O lines that can be used to identify and study variable stars at evolved stages. Detecting the maser emission in H2 O, OH and Si O molecules toward infrared-excess objects is one of the methods for identifing long-period variables(LPVs, including miras and semiregulars), because these stars exhibit maser activity in their circumstellar shells. Our sample contains 1803 known LPV objects. Forty-six percent of these stars(832 objects) manifest maser emission in the line of at least one molecule: H2 O, OH or Si O. We use the database of circumstellar masers in order to search for LPVs which are not included in the General Catalogue of Variable Stars(GCVS). Our database contains 4806 objects(3866 objects without associations in GCVS) with maser detection in at least one molecule. Therefore it is possible to use the database in order to locate and study the large sample of LPV stars. The database can be accessed at http://maserdb.net.
基金funded by the National Key R&D Program of China under No.2022YFC2205300the National Natural Science Foundation of China(NSFC,grant Nos.12073067 and 11973078)the Chinese Academy of Sciences(CAS)“Light of West China”Program under No.2022-XBQNXZ012 and No.2020-XBQNXZ-018。
文摘We introduce the structure of a radio astronomy phased array feeds(PAF)beamforming demonstrator.In a laboratory environment,we have demonstrated beamforming on a received 1.25 GHz sinusoidal signal and used digital weighting techniques to plot the 2D pattern of the PAF.The radio frequency part of the demonstrator includes a 4×4 linearly polarized microstrip antenna array,all of which is connected in series with a low-noise amplifier.The signals from the central 4×2 array elements are injected into a radio frequency system-on-chip digital board,which can receive eight inputs with a bandwidth of 512 MHz.Combining the principle of undersampling,the beamforming is completed at a frequency of 1.25 GHz for the offline data,and a 2D image of the beam is plotted using beam scanning technology.
文摘天文观测数据是天文研究的基础,但传统的集中式数据检索方法已难以满足日益增长的海量天文数据的高性能检索和查询需求.提出了一种基于Elastic Search分布式搜索引擎,通过River机制对现有的海量FITS(Flexible Image Transport System)数据进行索引构建,从而实现海量FITS数据高效检索的方法,并讨论了其中的近实时检索和查询的关键技术.实测结果表明,在百万到千万级的天文数据量下,该方法可获得极高的检索性能,并能够很方便地集成到现有的天文数据归档系统中,完全可以满足当前国内各类望远镜系统天文数据的归档要求.
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.
文摘先进天基太阳天文台(Advanced Space-based Solar Observatory,ASO-S)卫星是我国首颗太阳观测卫星,主要观测太阳耀斑和日冕物质抛射以及产生它们的磁场结构.ASO-S卫星的科学应用系统是科学卫星工程的6大系统之一,它连接科学用户和卫星数据,为将卫星的科学数据转化为科学成果提供保障.科学应用系统的数据库是连接软件与海量数据的枢纽,为科学数据生产和用户服务及运行提供数据层的支撑.介绍了科学应用系统的数据库架构设计、数据库的选择以及数据库性能优化和表样例.这里的数据库包括观测计划、工程参数、运维日志、科学数据、定标数据和特征事件识别等数据库.这些数据库的建设将为ASO-S卫星工程科学应用系统的顺利运行提供数据支撑,也可以为未来其他科学卫星类似数据库的搭建提供参考和借鉴.
基金the National Key R&D Program of China(Grant No.2018YFB 1702703)funded by the National Natural Science Foundation of China(Grant Nos.11873066,U1531122 and U1731109)+3 种基金Funding for the Sloan Digital Sky Survey(SDSS)Ⅳhas been provided by the Alfred P.Sloan Foundationthe U.S.Department of Energy Office of Science,and the Participating Institutionssupport and resources from the Center for High-Performance Computing at the University of UtahThe Wide-field Infrared Survey Explorer(WISE)is a joint project of the University of California,Los Angeles,and the Jet Propulsion Laboratory/California Institute of Technology,funded by the National Aeronautics and Space Administration。
文摘We combine K-nearest neighbors(KNN)with a genetic algorithm(GA)for photometric redshift estimation of quasars,short for GeneticKNN,which is a weighted KNN approach supported by a GA.This approach has two improvements compared to KNN:one is the feature weighted by GA;the other is that the predicted redshift is not the redshift average of K neighbors but the weighted average of median and mean of redshifts for K neighbors,i.e.p×zmedian+(1-p)×zmean.Based on the SDSS and SDSS-WISE quasar samples,we explore the performance of GeneticKNN for photometric redshift estimation,comparing with the other six traditional machine learning methods,i.e.the least absolute shrinkage and selection operator(LASSO),support vector regression(SVR),multi-layer perceptrons(MLP),XGBoost,KNN and random forest.KNN and random forest show their superiority.Considering the easy implementation of KNN,we make improvement on KNN as GeneticKNN and apply GeneticKNN on photometric redshift estimation of quasars.Finally the performance of GeneticKNN is better than that of LASSO,SVR,MLP,XGBoost,KNN and random forest for all cases.Moreover the accuracy is better with the additional WISE magnitudes for the same method.
