在天体物理研究中,准确扣除星际消光与红化的影响对于光学和近红外观测至关重要.恒星的星际红化信息是揭示其内秉性质的关键.中国空间站望远镜(Chinese Space Station Telescope,CSST)的光学巡天项目将为科学家提供海量的恒星无缝光谱数...在天体物理研究中,准确扣除星际消光与红化的影响对于光学和近红外观测至关重要.恒星的星际红化信息是揭示其内秉性质的关键.中国空间站望远镜(Chinese Space Station Telescope,CSST)的光学巡天项目将为科学家提供海量的恒星无缝光谱数据,而基于这些数据测量恒星的红化信息,对于进一步测定恒星参数和理解银河系的性质具有重要意义.提出了一种基于随机森林回归的机器学习方法,该方法以光谱的归一化流量为输入参数来训练恒星的内秉颜色,旨在精确估计CSST低分辨率光谱中的恒星红化值.利用下一代恒星光谱库(Next Generation Stellar Spectral Library,NGSL)模拟CSST低分辨率光谱,并预测了所提方法的精度,同时探讨了不同波段和有效温度对结果精度的影响.基于CSST不同波段的无缝光谱所得到的恒星红化值E((g-i)g i、分别为g、i波段星等)与真实值的比较结果显示,在光谱信噪比为100时,GU波段的平均误差为0.0005 mag,标准差为0.0272 mag;GV波段的平均误差为0.0008 mag,标准差为0.0286 mag;GI波段的平均误差为0.0008 mag,标准差为0.0271 mag;全波段的平均误差为0.0003 mag,标准差为0.0252 mag.此方法作为CSST科学预研究的一部分,未来可直接应用于CSST数据,为CSST的科学研究提供基础支持.展开更多
We present a spectroscopic and photometric study of HIP 12653 to investigate its magnetic cycle and differential rotation.Using HARPS archival spectra matched with MARCS-AMBRE theoretical templates,we derive the stell...We present a spectroscopic and photometric study of HIP 12653 to investigate its magnetic cycle and differential rotation.Using HARPS archival spectra matched with MARCS-AMBRE theoretical templates,we derive the stellar parameters(Teff,logg,FeH,and vsini)of the target.The S-index,an activity indicator based on the emission of the CaⅡH&K lines,is fitted to determine the magnetic cycle and rotation periods.We refine the magnetic cycle period to 5799.20±0.88 days and suggest the existence of a secondary,shorter cycle of674.6922±0.0098 days,making HIP 12653 the youngest star known to exhibit such a short activity cycle.During the minimum activity phase,a rotation period of 4.8 days is estimated.This is notably different from the 7 day period obtained when measurements during minimum activity are excluded,suggesting that these two periods are rotation periods at different latitudes.To explore this hypothesis,we introduce a novel light curve fitting method that incorporates multiple harmonics to model different spot configurations.Applied to synthetic light curves,the method recovers at least two rotation periods close to the true input values(within three times their uncertainties)in 92.1%of cases.The inferred rotation shear shows a median deviation of 0.0011±0.0003 and a standard deviation of 0.0177±0.0002 from the true value.Applying this approach to TESS photometric data from 2018 to2023,we detect three distinct rotation periods—4.8 days,5.7 days,and 7.7 days,(along with a signal at 3.75 days interpreted as its first harmonic)—consistent with spots located at different latitudes.Assuming a solar-like differential rotation,we estimate an inclination of 34.0°±1.8°and a rotational shear ofα=0.38±0.01.These results confirm the 4.8 day period and demonstrate that differential rotation can be constrained by tracking rotation period changes across different phases of the magnetic cycle.展开更多
Stellar atmospheric parameters and elemental abundances are traditionally determined using template matching techniques based on high-resolution spectra.However,these methods are sensitive to noise and unsuitable for ...Stellar atmospheric parameters and elemental abundances are traditionally determined using template matching techniques based on high-resolution spectra.However,these methods are sensitive to noise and unsuitable for ultra-low-resolution data.Given that the Chinese Space Station Telescope(CSST)will acquire large volumes of ultra-low-resolution spectra,developing effective methods for ultra-low-resolution spectral analysis is crucial.In this work,we investigated the Fully Connected Residual Network(FCResNet)for simultaneously estimating atmospheric parameters(T_(eff),log g,[Fe/H])and elemental abundances([C/Fe],[N/Fe],[Mg/Fe]).We trained and evaluated FCResNet using CSST-like spectra(R~200)generated by degrading LAMOST spectra(R~1800),with reference labels from APOGEE.FCResNet significantly outperforms traditional machine learning methods(KNN,XGBoost,S VR)and CNN in prediction precision.For spectra with the g-band signal-tonoise ratio greater than 20,FCResNet achieves precisions of 78 K,0.15 dex,0.08 dex,0.05 dex,0.10 dex,and0.05 dex for T_(eff),log g,[Fe/H],[C/Fe],[N/Fe]and[Mg/Fe],respectively,on the test set.FCResNet processes one million spectra in only 42 s while maintaining a simple architecture with only 348 KB model size.These results suggest that FCResNet is a practical and promising tool for processing the large volume of ultra-lowresolution spectra that will be obtained by CSST in the future.展开更多
利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带...利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带来的影响,在数据预处理阶段将3个分量的数据统一标准化至[0,1]区间.利用第k个最近邻点距离方法分析了1046颗恒星样本在标准化无量纲3D速度空间的分布特征,再根据第k个最近邻点距离随k值的变化趋势确定了DBSCAN聚类算法的输入参数(Eps,MinPts),最后利用DBSCAN聚类算法分离出497颗3D运动学成员星.分析结果表明得到的3D运动学成员星是可靠的.展开更多
基金Funding for the TESS mission is provided by the NASA Explorer Program。
文摘We present a spectroscopic and photometric study of HIP 12653 to investigate its magnetic cycle and differential rotation.Using HARPS archival spectra matched with MARCS-AMBRE theoretical templates,we derive the stellar parameters(Teff,logg,FeH,and vsini)of the target.The S-index,an activity indicator based on the emission of the CaⅡH&K lines,is fitted to determine the magnetic cycle and rotation periods.We refine the magnetic cycle period to 5799.20±0.88 days and suggest the existence of a secondary,shorter cycle of674.6922±0.0098 days,making HIP 12653 the youngest star known to exhibit such a short activity cycle.During the minimum activity phase,a rotation period of 4.8 days is estimated.This is notably different from the 7 day period obtained when measurements during minimum activity are excluded,suggesting that these two periods are rotation periods at different latitudes.To explore this hypothesis,we introduce a novel light curve fitting method that incorporates multiple harmonics to model different spot configurations.Applied to synthetic light curves,the method recovers at least two rotation periods close to the true input values(within three times their uncertainties)in 92.1%of cases.The inferred rotation shear shows a median deviation of 0.0011±0.0003 and a standard deviation of 0.0177±0.0002 from the true value.Applying this approach to TESS photometric data from 2018 to2023,we detect three distinct rotation periods—4.8 days,5.7 days,and 7.7 days,(along with a signal at 3.75 days interpreted as its first harmonic)—consistent with spots located at different latitudes.Assuming a solar-like differential rotation,we estimate an inclination of 34.0°±1.8°and a rotational shear ofα=0.38±0.01.These results confirm the 4.8 day period and demonstrate that differential rotation can be constrained by tracking rotation period changes across different phases of the magnetic cycle.
基金supported by the National Astronomical Observatories of Chinese Academy of Sciences(No.E4ZR0516)the National Natural Science Foundation of China(12273078,12273075 and 12411530071)+2 种基金support from Royal Society IECNSFC233140 exchange grantFunding for the Project has been provided by the National Development and Reform CommissionFunding for the Sloan Digital Sky Survey IV has been provided by the Alfred P.Sloan Foundation,the U.S.Department of Energy Office of Science,and the Participating Institutions。
文摘Stellar atmospheric parameters and elemental abundances are traditionally determined using template matching techniques based on high-resolution spectra.However,these methods are sensitive to noise and unsuitable for ultra-low-resolution data.Given that the Chinese Space Station Telescope(CSST)will acquire large volumes of ultra-low-resolution spectra,developing effective methods for ultra-low-resolution spectral analysis is crucial.In this work,we investigated the Fully Connected Residual Network(FCResNet)for simultaneously estimating atmospheric parameters(T_(eff),log g,[Fe/H])and elemental abundances([C/Fe],[N/Fe],[Mg/Fe]).We trained and evaluated FCResNet using CSST-like spectra(R~200)generated by degrading LAMOST spectra(R~1800),with reference labels from APOGEE.FCResNet significantly outperforms traditional machine learning methods(KNN,XGBoost,S VR)and CNN in prediction precision.For spectra with the g-band signal-tonoise ratio greater than 20,FCResNet achieves precisions of 78 K,0.15 dex,0.08 dex,0.05 dex,0.10 dex,and0.05 dex for T_(eff),log g,[Fe/H],[C/Fe],[N/Fe]and[Mg/Fe],respectively,on the test set.FCResNet processes one million spectra in only 42 s while maintaining a simple architecture with only 348 KB model size.These results suggest that FCResNet is a practical and promising tool for processing the large volume of ultra-lowresolution spectra that will be obtained by CSST in the future.
文摘利用疏散星团NGC 188所在天区的1046颗恒星样本的高精度3维(3D)运动学数据(自行和视向速度)测试了DBSCAN(Density-Based Spatial Clustering of Applications with Noise)聚类算法的成员判定效果.为了避免自行和视向速度的单位不一致带来的影响,在数据预处理阶段将3个分量的数据统一标准化至[0,1]区间.利用第k个最近邻点距离方法分析了1046颗恒星样本在标准化无量纲3D速度空间的分布特征,再根据第k个最近邻点距离随k值的变化趋势确定了DBSCAN聚类算法的输入参数(Eps,MinPts),最后利用DBSCAN聚类算法分离出497颗3D运动学成员星.分析结果表明得到的3D运动学成员星是可靠的.
