分类： 天文学 >> 天体物理学 提交时间： 2016-05-05
摘要： The Large sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) general survey is a spectroscopic survey that will eventually cover approximately half of the celestial sphere and collect 10 million spectra of stars, galaxies and QSOs. Objects in both the pilot survey and the first year regular survey are included in the LAMOST DR1. The pilot survey started in October 2011 and ended in June 2012, and the data have been released to the public as the LAMOST Pilot Data Release in August 2012. The regular survey started in September 2012, and completed its first year of operation in June 2013. The LAMOST DR1 includes a total of 1202 plates containing 2 955 336 spectra, of which 1 790 879 spectra have observed signalto-noise ratio (SNR) ≥ 10. All data with SNR ≥ 2 are formally released as LAMOST DR1 under the LAMOST data policy. This data release contains a total of 2 204 696 spectra, of which 1 944 329 are stellar spectra, 12 082 are galaxy spectra and 5017 are quasars. The DR1 not only includes spectra, but also three stellar catalogs with measured parameters: late A,FGK-type stars with high quality spectra (1 061 918 entries), A-type stars (100 073 entries), and M-type stars (121 522 entries). This paper introduces the survey design, the observational and instrumental limitations, data reduction and analysis, and some caveats. A description of the FITS structure of spectral files and parameter catalogs is also provided.
分类： 物理学 >> 地球物理学、天文学和天体物理学 提交时间： 2023-12-15 合作期刊: 《Research in Astronomy and Astrophysics》
摘要： We present an updated catalog of 46,753 radial velocity (RV) standard stars selected from the APOGEE DR17. These stars cover the Northern and Southern Hemispheres almost evenly, with 62% being red giants and 38% being main sequence stars. These RV standard stars are stable on a baseline longer than 200 days (with 54% longer than one year and 10% longer than five years) with a median stability better than 215 m s−1. The average number of observations of those stars is 5 and each observation is required to have signal-to-noise ratio greater than 50 and RV measurement error smaller than 500 m s−1. Based on the new APOGEE RV standard star catalog, we have checked the RV zero-points (RVZPs) for current large-scale stellar spectroscopic surveys including RAVE, LAMOST, GALAH and Gaia. By careful analysis, we estimate their mean RVZP to be +0.149 km s−1, +4.574 km s−1 (for LRS), −0.031 km s−1 and +0.014 km s−1, respectively, for the four surveys. In the RAVE, LAMOST (for MRS), GALAH and Gaia surveys, RVZP exhibits a systematic trend with stellar parameters (mainly [Fe/H], Teff, log g, GBP − GRP and GRVS). The corrections to those small but clear RVZPs are of vital importance for these massive spectroscopic surveys in various studies that require extremely high RV accuracies.
分类： 天文学 >> 天文学 提交时间： 2024-05-10 合作期刊: 《Research in Astronomy and Astrophysics》
摘要： This study introduces a novel convolutional neural network, the WISE Galaxy Classification Network (WGC), for classifying spiral and elliptical galaxies using Wide-field Infrared Survey Explorer (WISE) images. WGC attains an accuracy of 89.03%, surpassing the combined use of K-means or SVM with the Color–Color method in more accurately identifying galaxy morphologies. The enhanced variant, WGC_mag, integrates magnitude parameters with image features, further boosting the accuracy to 89.89%. The research also delves into the criteria for galaxy classification, discovering that WGC primarily categorizes dust-rich images as elliptical galaxies, corresponding to their lower star formation rates, and classifies less dusty images as spiral galaxies. The paper explores the consistency and complementarity of WISE infrared images with SDSS optical images in galaxy morphology classification. The SDSS Galaxy Classification Network (SGC), trained on SDSS images, achieved an accuracy of 94.64%. The accuracy reached 99.30% when predictions from SGC and WGC were consistent. Leveraging the complementarity of features in WISE and SDSS images, a novel variant of a classifier, namely the Multi-band Galaxy Morphology Integrated Classifier, has been developed. This classifier elevates the overall prediction accuracy to 95.39%. Lastly, the versatility of WGC was validated in other data sets. On the HyperLEDA data set, the distinction between elliptical galaxies and Sc, Scd and Sd spiral galaxies was most pronounced, achieving an accuracy of 90%, surpassing the classification results of the Galaxy Zoo 2 labeled WISE data set. This research not only demonstrates the effectiveness of WISE images in galaxy morphology classification but also represents an attempt to integrate multi-band astronomical data to enhance understanding of galaxy structures and evolution.
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