Code for Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks
Peng Jia
DOI:10.12149/101109
Paper Title:
Digital Twin of Atmospheric Turbulence Phase Screens Based On Deep Neural Networks
Publication:
Optics Express
This is a complied version of digital twin of atmospheric turbulence phase screens based on deep neural networks. It can only generate phase screens with 128*128 pixels. If you need some phase screen with specified properties, feel free to contact the corresponding author: Peng Jia from Taiyuan University of Techonology through his email: robinmartin20@gmail.com or robinmartin@126.com.
Dynamic Property and Magnetic Nonpotentiality of Two Types of Confined Solar Flares
Duan, Xuchun ; Li , Ting ; Jing, Qihang
DOI:10.12149/101103
We analyze 152 large confined flares (GOES class ≥M1.0 and ≤45◦ from disk center) during 2010−2019, and classify them into two types based on their different dynamic properties. “Type I” flares are atypical confined flares above the filaments, which are characterized by slipping motions of flare loops and ribbons and not associated with any eruption of a filament/flux rope. “Type II” flares are typical confined flares associated with the failed eruptions of the filaments/flux ropes, which can be explained by the classical 2D flare model. A total of 59 flares are “Type I” flares (about 40%) and 93 events are “Type II” flares (about 60%). There are significant differences in distributions of the total unsigned magnetic flux (ΦAR) of active regions (ARs) producing the two types of confined flares, with “Type I” confined flares from ARs with a larger ΦAR than “Type II”. We calculate the mean shear angle ΨHFED within the core of an AR prior to the flare onset, and find that it is slightly smaller for “Type I” flares than that for “Type II” events. The relative non-potentiality parameter ΨHFED/ΦAR has the best performance in distinguishing the two types of flares. About 73% of “Type I” confined flares have ΨHFED/ΦAR
Validations and corrections of the SFD and Planck maps
Sun ,Yang; Yuan, Haibo; Chen, Bingqiu
DOI:10.12149/101101
Precise correction of dust reddening is fundamental to obtain the intrinsic parameters of celestial objects. The Schlegel et al. (SFD) and the Planck 2D extinction maps are widely used for the reddening correction. In this work, using accurate reddening determinations of about two million stars from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) data release 5 (DR5) and Gaia DR2, we check and calibrate the SFD and Planck maps in the middle and high Galactic latitudes. The maps show similar precision in reddening correction. We find small yet significant spatially dependent biases for the four maps, which are similar between the SFD and Planck2014-R maps, and between the Planck2014-Tau and Planck2019-Tau maps. The biases show a clear dependence on the dust temperature and extinction for the SFD and Planck2014-R maps. While those of the Planck2014-Tau and Planck2019-Tau maps have a weak dependence on the dust temperature, they both strongly depend on the dust spectral index. Finally, we present corrections of the SFD and Planck extinction maps within the LAMOST footprint, along with empirical relations for corrections outside the LAMOST footprint. Our results provide important clues for the further improvement of the Galactic all-sky extinction maps and lay an significant foundation for the accurate extinction correction in the era of precision astronomy.
S-type stars discovered in Medium-Resolution Spectra of LAMOST DR9
Chen, Jing ; Luo, A-Li ; Li, Yin-Bi ; Chen, Xiang-Lei ; Wang, Rui ; Li, Shuo ; Du, Bing ; Ma, Xiao-Xiao
DOI:10.12149/101097
Paper Title:
S-type stars discovered in Medium-Resolution Spectra of LAMOST DR9
Publication:
arXiv e-prints
In this paper, we report on 606 S-type stars identified from Data Release 9 of the LAMOST medium-resolution spectroscopic (MRS) survey, and 539 of them are reported for the first time. The discovery of these stars is a three-step process, i.e., selecting with the ZrO band indices greater than 0.25, excluding non-S-type stars with the iterative Support Vector Machine method, and finally retaining stars with absolute bolometric magnitude larger than -7.1. The 606 stars are consistent with the distribution of known S-type stars in the color-magnitude diagram. We estimated the C/Os using the [C/Fe] and [O/Fe] provided by APOGEE and the MARCS model for S-type stars, respectively, and the results of the two methods show that C/Os of all stars are larger than 0.5. Both the locations on the color-magnitude diagram and C/Os further verify the nature of our S-type sample. Investigating the effect of TiO and atmospheric parameters on ZrO with the sample, we found that log g has a more significant impact on ZrO than Teff and [Fe/H], and both TiO and log g may negatively correlate with ZrO. According to the criterion of Tian et al. (2020), a total of 238 binary candidates were found by the zero-point-calibrated radial velocities from the officially released catalog of LAMOST MRS and the catalog of Zhang et al. (2021). A catalog of these 606 S-type stars is available from the following link https://doi.org/10.12149/101097.
An Empirical Template Library for FGK and Late-type A Stars Using LAMOST Observed Spectra
Du, Bing; Luo, A-Li ; Zuo, F. et al.
DOI:10.12149/101093
We present an empirical stellar spectra library created using spectra from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR5. This library represents a uniform data set ranging from 3750 through 8500K in effective temperature (Teff), from −2.5 through +1.0 dex in metallicity ([Fe/H]), and from 0 to 5.0 dex in gravity (log g). The spectra in the library have resolutions R∼1800, with well-calibrated fluxes and rest-framed wavelengths. Using a large number of red stars observed by LAMOST, we generated denser K-type templates to fill in data missing from current empirical spectral libraries, particularly the late K type. For K giants, we calibrated the spectroscopic surface gravities against the asteroseismic surface gravities. To verify the reliability of the parameters labeled for this library, we performed an internal cross-validation using a χ2 minimization method to interpolate the parameters of each individual spectrum using the remaining spectra in the library. We obtained precisions of 41 K, 0.11 dex, and 0.05 dex for Teff, log g, and [Fe/H], respectively, which means the templates are labeled with correct stellar parameters. Through external comparisons, we confirmed that measurements of the stellar parameters through this library can achieve accuracies of approximately 125 K in Teff, 0.1 dex in [Fe/H] and 0.20 dex in log g without systematic offset. This empirical library is useful for stellar parameter measurements because it has large parameter coverage and full wavelength coverage from 3800 to 8900 Å.
Objective Separation between CP1 and CP2 Based on Feature Extraction with Machine Learning
Shang, Lun-Hua ; Luo, A. -Li ; Wang, Liang ; Qin, Li ; Du, Bing ; He, Xu-Jiang ; Cui, Xiang-Qun ; Zhao, Yong-Heng ; Zhu, Ri-Hong ; Zhi, Qi-Jun
DOI:10.12149/101091
Paper Title:
Objective Separation between CP1 and CP2 Based on Feature Extraction with Machine Learning
Publication:
The Astrophysical Journal Supplement Series
In the eighth data release (DR8) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope, more than 318,740 low-resolution stellar spectra with types from B to early F and signal-to-noise ratios >50 were released. With this large volume of the early-type stars, we tried machine-learning algorithms to search for class-one and class-two chemical peculiars (CP1 and CP2), and to detect spectral features to distinguish the two classes in low-resolution spectra. We selected the XGBoost algorithm after comparing the classification efficiency of three machine-learning ensemble algorithms. Using XGBoost followed by the visual investigation, we presented a catalog of 20,694 sources, including 17,986 CP1 and 2708 CP2, in which 6917 CP1 and 1652 CP2 are newly discovered. We also list the spectral features to separate CP1 from CP2 discovered through XGBoost. The stellar parameters (including effective temperature (T eff), surface gravity (log g), metallicity [Fe/H]), the spatial distribution in Galactic coordinates, and the color magnitude were provided for all of the entries of the catalog. The T eff for CP1 distributes from ~6000 to ~8500 K, while for CP2 it distributes from ~7000 to ~13,700 K. The log g of CP1 ranges from 2.8 to 4.8 dex, peaking at 4.5 dex, and of CP2 it ranges from 2.0 to 5.0 dex, peaking at 3.6 dex, respectively. The [Fe/H] of CP1 and CP2 are from -1.4 to 0.4 dex, and the [Fe/H] of CP1 are on average higher than that of CP2. Almost all of the targets in our sample locate around the Galactic plane.
Beyond Spectroscopy. I. Metallicities, Distances, and Age Estimates for Over 20 Million Stars from SMSS DR2 and Gaia EDR3
Huang, Yang ; Beers, Timothy C. ; Wolf, Christian ; Lee, Young Sun ; Onken, Christopher A. ; Yuan, Haibo ; Shank, Derek ; Zhang, Huawei ; Wang, Chun ; Shi, Jianrong ; Fan, Zhou
DOI:10.12149/101073
Paper Title:
Beyond Spectroscopy. I. Metallicities, Distances, and Age Estimates for Over 20 Million Stars from SMSS DR2 and Gaia EDR3
Publication:
The Astrophysical Journal
Accurate determinations of stellar parameters and distances for large complete samples of stars are keys for conducting detailed studies of the formation and evolution of our Galaxy. Here we present stellar atmospheric parameters (effective temperature, luminosity classifications, and metallicity) estimates for some 24 million stars determined from the stellar colors of SMSS DR2 and Gaia EDR3, based on training data sets with available spectroscopic measurements from previous high/medium/low-resolution spectroscopic surveys. The number of stars with photometric-metallicity estimates is 4-5 times larger than that collected by the current largest spectroscopic survey to date-LAMOST-over the course of the past decade. External checks indicate that the precision of the photometric-metallicity estimates are quite high, comparable to or slightly better than that derived from spectroscopy, with typical values around 0.05-0.15 dex for both dwarf and giant stars with [Fe/H] > -2.01.0, 0.10-0.20 dex for giant stars with -2.0 < [Fe/H] ≤ -1.0, and 0.20-0.25 dex for giant stars with [Fe/H] ≤ -2.0, and include estimates for stars as metal-poor as [Fe/H] ~ -3.5, substantially lower than previous photometric techniques. Photometric-metallicity estimates are obtained for an unprecedented number of metal-poor stars, including a total of over three million metal-poor (MP; [Fe/H] ≤ -1.0) stars, over half a million very metal-poor (VMP; [Fe/H] ≤ -2.0) stars, and over 25,000 extremely metal-poor (EMP; [Fe/H] ≤ -3.0) stars. Moreover, distances are determined for over 20 million stars in our sample. For the over 18 million sample stars with accurate Gaia parallaxes, stellar ages are estimated by comparing with theoretical isochrones. Astrometric information is provided for the stars in our catalog, along with radial velocities for ~10% of our sample stars, taken from completed/ongoing large-scale spectroscopic surveys.
A New Magnetic Parameter of Active Regions Distinguishing Large Eruptive and Confined Solar Flares
Li, Ting ; Sun, Xudong ; Hou, Yijun ; Chen, Anqin ; Yang, Shuhong ; Zhang, Jun
DOI:10.12149/101087
Paper Title:
A New Magnetic Parameter of Active Regions Distinguishing Large Eruptive and Confined Solar Flares
Publication:
The Astrophysical Journal
With the aim of investigating how the magnetic field in solar active regions (ARs) controls flare activity, i.e., whether a confined or eruptive flare occurs, we analyze 106 flares of Geostationary Operational Environmental Satellite class ≥M1.0 during 2010-2019. We calculate mean characteristic twist parameters α FPIL within the "flaring polarity inversion line" region and α HFED within the area of high photospheric magnetic free energy density, which both provide measures of the nonpotentiality of the AR core region. Magnetic twist is thought to be related to the driving force of electric current-driven instabilities, such as the helical kink instability. We also calculate total unsigned magnetic flux (ΦAR) of ARs producing the flare, which describes the strength of the background field confinement. By considering both the constraining effect of background magnetic fields and the magnetic nonpotentiality of ARs, we propose a new parameter α/ΦAR to measure the probability for a large flare to be associated with a coronal mass ejection (CME). We find that in about 90% of eruptive flares, α FPIL/ΦAR and α HFED/ΦAR are beyond critical values (2.2 × 10-24 and 3.2 × 10-24 Mm-1 Mx-1), whereas they are less than critical values in ~80% of confined flares. This indicates that the new parameter α/ΦAR is well able to distinguish eruptive flares from confined flares. Our investigation suggests that the relative measure of magnetic nonpotentiality within the AR core over the restriction of the background field largely controls the capability of ARs to produce eruptive flares.
Strong [OIII]{\lambda}5007 emission line compact galaxies in LAMOST DR9: Blueberries, Green Peas and Purple Grapes
Liu, Siqi ; Luo, A-Li ; Yang, Huan ; Shen, Shi-Yin ; Wang, Jun-Xian ; Zhang, Hao-Tong ; Zheng, Zhenya ; Song, Yi-Han ; Kong, Xiao ; Wang, Jian-Ling ; Chen, Jian-Jun
DOI:10.12149/101085
Paper Title:
Strong [OIII]{\lambda}5007 emission line compact galaxies in LAMOST DR9: Blueberries, Green Peas and Purple Grapes
Publication:
arXiv e-prints
Green Pea and Blueberry galaxies are well-known for their compact size, low mass, strong emission lines and analogs to high-z Ly{\alpha} emitting galaxies. In this study, 1547 strong [OIII]{\lambda}5007 emission line compact galaxies with 1694 spectra are selected from LAMOST DR9 at the redshift range from 0.0 to 0.59. According to the redshift distribution, these samples can be separated into three groups: Blueberries, Green Peas and Purple Grapes. Optical [MgII]{\lambda}2800 line feature, BPT diagram, multi-wavelength SED fitting, MIR color, and MIR variability are deployed to identify 23 AGN candidates from these samples, which are excluded for the following SFR discussions. We perform the multi-wavelength SED fitting with GALEX UV and WISE MIR data. Color excess from Balmer decrement shows these strong [OIII]{\lambda}5007 emission line compact galaxies are not highly reddened. The stellar mass of the galaxies is obtained by fitting LAMOST calibrated spectra with the emission lines masked. We find that the SFR is increasing with the increase of redshift, while for the sources within the same redshift bin, the SFR increases with mass with a similar slope as the SFMS. These samples have a median metallicity of 12+log(O/H) of 8.10. The metallicity increases with mass, and all the sources are below the mass-metallicity relation. The direct-derived Te-based metallicity from the [OIII]{\lambda}4363 line agrees with the empirical N2-based empirical gas-phase metallicity. Moreover, these compact strong [OIII]{\lambda}5007 are mostly in a less dense environment.
Stellar Loci. V. Photometric Metallicities of 27 Million FGK Stars Based on Gaia Early Data Release 3
Xu, Shuai ; Yuan, Haibo ; Niu, Zexi ; Yang, Lin ; Beers, Timothy C. ; Huang, Yang
DOI:10.12149/101081
Paper Title:
Stellar Loci. V. Photometric Metallicities of 27 Million FGK Stars Based on Gaia Early Data Release 3
Publication:
The Astrophysical Journal Supplement Series
We combine LAMOST DR7 spectroscopic data and Gaia EDR3 photometric data to construct high-quality giant (0.7 < (BP - RP) < 1.4) and dwarf (0.5 < (BP - RP) < 1.5) samples in the high Galactic latitude region, with precise corrections for magnitude-dependent systematic errors in the Gaia photometry and careful reddening corrections using empirically determined color- and reddening-dependent coefficients. We use the two samples to build metallicity-dependent stellar loci of Gaia colors for giants and dwarfs, respectively. For a given (BP - RP) color, a 1 dex change in [Fe/H] results in about a 5 mmag change in (BP - G) color for solar-type stars. These relations are used to determine metallicity estimates from EDR3 colors. Despite the weak sensitivity, the exquisite data quality of these colors enables a typical precision of about δ [Fe/H] = 0.2 dex. Our method is valid for FGK stars with G ≤ 16, [Fe/H] ≥ -2.5, and E(B - V) ≤ 0.5. Stars with fainter G magnitudes, lower metallicities, or larger reddening suffer from higher metallicity uncertainties. With the enormous data volume of Gaia, we have measured metallicity estimates for about 27 million stars with 10 < G ≤ 16 across almost the entire sky, including over 6 million giants and 20 million dwarfs, which can be used for a number of studies. These include investigations of Galactic formation and evolution, the identification of candidate stars for subsequent high-resolution spectroscopic follow-up, the identification of wide binaries, and to obtain metallicity estimates of stars for asteroseismology and exoplanet research.
Identify Light-curve Signals with Deep Learning Based Object Detection Algorithm. I. Transit Detection
Cui, Kaiming ; Liu, Junjie ; Feng, Fabo ; Liu, Jifeng
DOI:10.12149/101079
Paper Title:
Identify Light-curve Signals with Deep Learning Based Object Detection Algorithm. I. Transit Detection
Publication:
The Astronomical Journal
Deep learning techniques have been well explored in the transiting exoplanet field; however, previous work mainly focuses on classification and inspection. In this work, we develop a novel detection algorithm based on a well-proven object detection framework in the computer vision field. Through training the network on the light curves of the confirmed Kepler exoplanets, our model yields about 90% precision and recall for identifying transits with signal-to-noise ratio higher than 6 (set the confidence threshold to 0.6). Giving a slightly lower confidence threshold, recall can reach higher than 95%. We also transfer the trained model to the TESS data and obtain similar performance. The results of our algorithm match the intuition of the human visual perception and make it useful to find single-transiting candidates. Moreover, the parameters of the output bounding boxes can also help to find multiplanet systems. Our network and detection functions are implemented in the Deep-Transit toolkit, which is an open-source Python package hosted on Github and PyPI.
The orbits of Triton and Nereid and the pole orientation of Neptune from Voyager, Hubble Space Telescope, and Earth-based astrometry in 1847-2020
Yuan, Ye ; Li, Fan ; Fu, Yanning ; Chen, Jian
DOI:10.12149/101077
Paper Title:
The orbits of Triton and Nereid and the pole orientation of Neptune from Voyager, Hubble Space Telescope, and Earth-based astrometry in 1847-2020
Publication:
Astronomy and Astrophysics
Context. New observations and new planetary and satellite ephemerides provide opportunities to improve the ephemerides for Triton and Nereid as well as relevant parameters. In particular, the observations include a lot of new accurate Earth-based positions reduced with Gaia astrometic catalogs and accurate positions obtained from Hubble Space Telescope. Aims: We aim to reliably improve the ephemerides for Triton and Nereid along with some parameters by using all the available astrometric data from 1847 to 2020 and by updating the dynamical model. We also aim to improve the geometrical descriptions based on the improved orbits of the two satellites and the pole orientation of Neptune. Methods: The orbits of Triton and Nereid are determined by fitting dynamical and observational model parameters to observations in a weighted least-squares sense. The dynamical model makes use of the new ephemerides from Jet Propulsion Laboratory for planets, DE440, and those for the inner satellites of Neptune, NEP090. For completeness, in addition to the gravitational effects considered by NEP081, the model also includes perturbations from inner satellites and a revised model for the motion of the pole orientation of Neptune. Moreover, model simplifications are investigated to speed up the motion equation integration. Since the pole orientation angles of Neptune at epoch are possibly improvable according to the preliminary post-fit sensitivity analysis, these angles are adjusted together with the satellite state vectors at epoch. Linear mapping of the covariance matrix is a measure of formal uncertainties of our orbit and pole solutions. However, to obtain more reliable accuracy estimations, it is necessary to consider the uncertainties in the observations and the unadjusted model parameters. To accomplish this, a method (BR-RS) that performs bootstrap resampling of observations (BR) and random sampling of unadjusted model parameters (RS) is used. Analytical representations are fitted to the orbit and pole solutions to provide their geometric descriptions. Results: The model we use can be fitted to the observations with their estimated accuracies. The new ephemerides, FORCES-8-MAIN-2020, covering years 1600-2650 are available online in SPICE format. The orbits are well determined with the orbital uncertainties expected to be within 200 km (about 10 mas as seen from the Earth) for Triton and 1000 km (50 mas) for Nereid for the next 100 yr as estimated by the BR-RS method. In particular, the correction in the Nereid mean orbit motion from the NEP081 solution is +4.''9 yr−1, and has a BR-RS uncertainty of 0.''24 yr−1. In the fitting process, we also determine the pole orientation of Neptune. At the initial epoch 1989 September 1 TDB, the right ascension and declination of the new pole orientation referred to the International Celestial Reference System are αp = 299.°339 ± 0.°012 (formal)∕ ± 0.°014 (BR-RS) and δp = 42.°985 ± 0.°016 (formal)∕ ± 0.°045 (BR-RS), respectively. From 1800 to 2200, the motion of the pole orientation is well constrained with a BR-RS uncertainty of about 0.°01-0.°05. We also provide geometrical descriptions for the new orbits and pole orientation.
Identification of White Dwarfs from Gaia EDR3 via Spectra from LAMOST DR7
Kong, Xiao ; Luo, A. -Li
DOI:10.12149/101075
Paper Title:
Identification of White Dwarfs from Gaia EDR3 via Spectra from LAMOST DR7
Publication:
Research Notes of the American Astronomical Society
We cross-matched 1.3 million white dwarf (WD) candidates from Gaia EDR3 with spectral data from LAMOST DR7 within 3″. Applying machine learning described in our previous work, we spectroscopically identified 6190 WD objects after visual inspection. 32 detailed classes were adopted for them, including but not limited to DAB and DB+M. We estimated the atmospheric parameters for the DA and DB type WD using Levenberg-Marquardt least-squares algorithm. Finally, a catalog of WD spectra from LAMOST is provided online.
LAMOST Observations in 15 K2 Campaigns. I. Low-resolution Spectra from LAMOST DR6
Wang, Jiangtao ; Fu, Jian-Ning ; Zong, Weikai ; Smith, M. C. ; De Cat, Peter ; Shi, Jianrong ; Luo, Ali ; Zhang, Haotong ; Frasca, A. ; Corbally, C. J. ; Molenda-Żakowicz, J. ; Catanzaro, G. ; Gray, R. O. ; Wang, Jiaxin ; Pan, Yang
DOI:10.12149/101071
Paper Title:
LAMOST Observations in 15 K2 Campaigns. I. Low-resolution Spectra from LAMOST DR6
Publication:
The Astrophysical Journal Supplement Series
The Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST)-K2 (LK2) project, initiated in 2015, aims to collect low-resolution spectra of targets in the K2 campaigns, similar to the LAMOST-Kepler project. By the end of 2018, a total of 126 LK2 plates had been observed by LAMOST. After cross-matching the catalog of the LAMOST data release 6 (DR6) with that of the K2 approved targets, we found 160,619 usable spectra of 84,012 objects, most of which had been observed more than once. The effective temperature, surface gravity, metallicity, and radial velocity from 129,974 spectra for 70,895 objects are derived through the LAMOST Stellar Parameter Pipeline (LASP). The internal uncertainties were estimated to be 81 K, 0.15 dex, 0.09 dex, and 5 km s-1, respectively, when derived from a spectrum with a signal-to-noise ratio in the g band (S/Ng) of 10. These estimates are based on results for targets with multiple visits. The external accuracies were assessed by comparing the parameters of targets in common with the APOGEE and Gaia surveys, for which we generally found linear relationships. A final calibration is provided, combining external and internal uncertainties for giants and dwarfs, separately. We foresee that these spectroscopic data will be used widely in different research fields, especially in combination with K2 photometry.
Stellar Parameterization of LAMOST M Dwarf Stars
Li, Jiadong ; Liu, Chao ; Zhang, Bo ; Tian, Hao ; Qiu, Dan ; Tian, Haijun
DOI:10.12149/101069
Paper Title:
Stellar Parameterization of LAMOST M Dwarf Stars
Publication:
The Astrophysical Journal Supplement Series
The M dwarf stars are the most common stars in the Galaxy, dominating the population of the Galaxy at faint magnitudes. Precise and accurate stellar parameters for M dwarfs are of crucial importance for many studies. However, the atmospheric parameters of M dwarf stars are difficult to determine. In this paper, we present a catalog of the spectroscopic stellar parameters (Teff and [M/H]) of ∼300,000 M dwarf stars observed by both LAMOST and Gaia using the Stellar LAbel Machine (SLAM). We train a SLAM model using LAMOST spectra with APOGEE Data Release 16 labels with 2800 K < Teff < 4500K and -2 dex < [M/H] < 0.5 dex. The SLAM Teff is in agreement to within ∼50 K compared to the previous study determined by APOGEE observations, and the SLAM [M/H] agrees within 0.12 dex compared to the APOGEE observation. We also set up a SLAM model trained by the BT-Settl atmospheric model with random uncertainties (in cross validation) to 60 K and agreeing within ∼90 K compared to previous studies.
Magnetic Flux and Magnetic Non-potentiality of Active Regions in Eruptive and Confined Solar Flares
Li, Ting ; Chen, Anqin ; Hou, Yijun ; Veronig, Astrid M. ; Yang, Shuhong ; Zhang, Jun
DOI:10.12149/101067
Paper Title:
Magnetic Helicity Budget of Solar Active Regions Prolific of Eruptive and Confined Flares
Publication:
The Astrophysical Journal
This database includes a total of 719 flares (251 eruptive and 468 confined) of Geostationary Operational Environmental Satellite (GOES) class C5.0 and larger that occurred within 45 degree from the central meridian, from June 2010 until June 2019.
A nonlinear solar magnetic field calibration method for the filter-based magnetograph by the residual network
Guo, Jingjing ; Bai, Xianyong ; Liu, Hui ; Yang, Xu ; Deng, Yuanyong ; Lin, Jiaben ; Su, Jiangtao ; Yang, Xiao ; Ji, Kaifan
DOI:10.12149/101063
Paper Title:
A nonlinear solar magnetic field calibration method for the filter-based magnetograph by the residual network
Publication:
Astronomy and Astrophysics
Context. The method of solar magnetic field calibration for the filter-based magnetograph is normally the linear calibration method under weak-field approximation that cannot generate the strong magnetic field region well due to the magnetic saturation effect. Aims: We try to provide a new method to carry out the nonlinear magnetic calibration with the help of neural networks to obtain more accurate magnetic fields. Methods: We employed the data from Hinode/SP to construct a training, validation and test dataset. The narrow-band Stokes I, Q, U, and V maps at one wavelength point were selected from all the 112 wavelength points observed by SP so as to simulate the single-wavelength observations of the filter-based magnetograph. We used the residual network to model the nonlinear relationship between the Stokes maps and the vector magnetic fields. Results: After an extensive performance analysis, it is found that the trained models could infer the longitudinal magnetic flux density, the transverse magnetic flux density, and the azimuth angle from the narrow-band Stokes maps with a precision comparable to the inversion results using 112 wavelength points. Moreover, the maps that were produced are much cleaner than the inversion results. The method can effectively overcome the magnetic saturation effect and infer the strong magnetic region much better than the linear calibration method. The residual errors of test samples to standard data are mostly about 50 G for both the longitudinal and transverse magnetic flux density. The values are about 100 G with our previous method of multilayer perceptron, indicating that the new method is more accurate in magnetic calibration.
Identification of BASS DR3 Sources as Stars, Galaxies and Quasars by XGBoost
Li, Changhua ; Zhang, Yanxia ; Cui, Chenzhou ; Fan, Dongwei ; Zhao, Yongheng ; Wu, Xue-Bing ; He, Boliang ; Xu, Yunfei ; Li, Shanshan ; Han, Jun ; Tao, Yihan ; Mi, Linying ; Yang, Hanxi ; Yang, Sisi
DOI:10.12149/101065
Paper Title:
Identification of BASS DR3 Sources as Stars, Galaxies and Quasars by XGBoost
Publication:
arXiv e-prints
The Beijing-Arizona Sky Survey (BASS) Data Release 3 (DR3) catalogue was released in 2019, which contains the data from all BASS and the Mosaic z-band Legacy Survey (MzLS) observations during 2015 January and 2019 March, about 200 million sources. We cross-match BASS DR3 with spectral databases from the Sloan Digital Sky Survey (SDSS) and the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST) to obtain the spectroscopic classes of known samples. Then, the samples are cross-matched with ALLWISE database. Based on optical and infrared information of the samples, we use the XGBoost algorithm to construct different classifiers, including binary classification and multiclass classification. The accuracy of these classifiers with the best input pattern is larger than 90.0 per cent. Finally, all selected sources in the BASS DR3 catalogue are classified by these classifiers. The classification label and probabilities for individual sources are assigned by different classifiers. When the predicted results by binary classification are the same as multiclass classification with optical and infrared information, the number of star, galaxy and quasar candidates is separately 12 375 838 (P_S>0.95), 18 606 073 (P_G>0.95) and 798 928 (P_Q>0.95). For these sources without infrared information, the predicted results can be as a reference. Those candidates may be taken as input catalogue of LAMOST, DESI or other projects for follow up observation. The classified result will be of great help and reference for future research of the BASS DR3 sources.
Study on Outliers in the Big Stellar Spectral Dataset of the Fifth Data Release (DR5) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)
Lu, Yan ; Luo, A-Li ; Wang, Li-Li ; Qin, Li ; Wang, Rui ; Chen, Xiang-Lei ; Du, Bing ; Zuo, Fang ; Hou, Wen ; Chen, Jian-Jun ; Tang, Yan-Ke ; Han, Jin-Shu ; Zhao, Yong-Heng
DOI:10.12149/101061
Paper Title:
Study on Outliers in the Big Stellar Spectral Dataset of the Fifth Data Release (DR5) of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST)
Publication:
arXiv e-prints
To study the quality of stellar spectra of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) and the correctness of the corresponding stellar parameters derived by the LASP (LAMOST Stellar Parameter Pipeline), the outlier analysis method is applied to the archived AFGK stars in the fifth data release (DR5) of LAMOST. The outlier factor is defined in order to sort more than 3 million stellar spectra selected from the DR5 Stellar Parameter catalog. We propose an improved Local Outlier Factor (LOF) method based on Principal Component Analysis and Monte Carlo to enable the computation of the LOF rankings for randomly picked sub-samples that are computed in parallel by multiple computers, and finally to obtain the outlier ranking of each spectrum in the entire dataset. Totally 3,627 most outlier ranked spectra, around one-thousandth of all spectra, are selected and clustered into 10 groups, and the parameter density distribution of them conforms to the parameter distribution of LAMOST DR5, which suggests that in the whole parameter space the probability of bad spectra is uniformly distributed. By cross-matching the 3,627 spectra with APOGEE, we obtain 122 common ones. The published parameters calculated from LASP agree with APOGEE for the 122 spectra although there are bad pixels or bad flux calibrations in them. On the other hand, some outlier spectra show strong nebular contamination warning the corresponding parameters should be carefully used. A catalog and a spectral atlas of all the 3,627 outliers can be found at the link http://paperdata.china-vo.org/LY_paper/dr5Outlier/dr5Outlier_resource.zip.
A three-dimensional extinction map of the Galactic anticentre from multiband photometry
Chen, B. -Q. ; Liu, X. -W. ; Yuan, H. -B. ; Zhang, H. -H. ; Schultheis, M. ; Jiang, B. -W. ; Huang, Y. ; Xiang, M. -S. ; Zhao, H. -B. ; Yao, J. -S. ; Lu, H.
DOI:10.12149/101059
Paper Title:
A three-dimensional extinction map of the Galactic anticentre from multiband photometry
Publication:
Monthly Notices of the Royal Astronomical Society
We present a three-dimensional extinction map in the r band. The map has a spatial angular resolution, depending on latitude, between 3 and 9 arcmin and covers the entire Xuyi Schmidt Telescope Photometric Survey of the Galactic Anticentre (XSTPS-GAC) survey area of over 6000 deg2 for Galactic longitude 140 < l < 240 deg and latitude -60 < b < 40 deg. By cross-matching the photometric catalogue of the XSTPS-GAC with those of 2MASS and WISE, we have built a multiband photometric stellar sample of about 30 million stars and applied spectral energy distribution (SED) fitting to the sample. By combining photometric data from the optical to the near-infrared, we are able to break the degeneracy between the intrinsic stellar colours and the amounts of extinction by dust grains for stars with high photometric accuracy, and trace the extinction as a function of distance for low Galactic latitude and thus highly extincted regions. This has allowed us to derive the best-fitting extinction and distance information of more than 13 million stars, which are used to construct the three-dimensional extinction map. We have also applied a Rayleigh-Jeans colour excess (RJCE) method to the data using the 2MASS and WISE colour (H - W2). The resulting RJCE extinction map is consistent with the integrated two-dimensional map deduced using the best-fitting SED algorithm. However for individual stars, the amounts of extinction yielded by the RJCE method suffer from larger errors than those given by the best-fitting SED algorithm.
Point spread function estimation for wide field small aperture telescopes with deep neural networks and calibration data
Jia, Peng ; Wu, Xuebo ; Li, Zhengyang ; Li, Bo ; Wang, Weihua ; Liu, Qiang ; Popowicz, Adam ; Cai, Dongmei
DOI:10.12149/101057
Paper Title:
Point spread function estimation for wide field small aperture telescopes with deep neural networks and calibration data
Publication:
Monthly Notices of the Royal Astronomical Society
The point spread function (PSF) reflects states of a telescope and plays an important role in the development of data-processing methods, such as PSF-based astrometry, photometry, and image restoration. However, for wide field small aperture telescopes (WFSATs), estimating PSF in any position of the whole field of view is hard, because aberrations induced by the optical system are quite complex and the signal-to-noise ratio of star images is often too low for PSF estimation. In this paper, we further develop our deep neural network (DNN)-based PSF modelling method and show its applications in PSF estimation. During the telescope alignment and testing stage, our method collects system calibration data through modification of optical elements within engineering tolerances (tilting and decentring). Then, we use these data to train a DNN (Tel-Net). After training, the Tel-Net can estimate PSF in any field of view from several discretely sampled star images. We use both simulated and experimental data to test performance of our method. The results show that the Tel-Net can successfully reconstruct PSFs of WFSATs of any states and in any positions of the field of view (FoV). Its results are significantly more precise than results obtained by the compared classic method - inverse distance weight interpolation. Our method provides foundations for developing deep neural network-based data-processing methods for WFSATs, which require strong prior information of PSFs.
Classification of 4XMM-DR9 sources by machine learning
Zhang, Yanxia ; Zhao, Yongheng ; Wu, Xue-Bing
DOI:10.12149/101055
Paper Title:
Classification of 4XMM-DR9 sources by machine learning
Publication:
Monthly Notices of the Royal Astronomical Society
The ESA's X-ray Multi-mirror Mission (XMM-Newton) created a new high-quality version of the XMM-Newton serendipitous source catalogue, 4XMM-DR9, which provides a wealth of information for observed sources. The 4XMM-DR9 catalogue is correlated with the Sloan Digital Sky Survey (SDSS) DR12 photometric data base and the AllWISE data base; we then get X-ray sources with information from the X-ray, optical, and/or infrared bands and obtain the XMM-WISE, XMM-SDSS, and XMM-WISE-SDSS samples. Based on the large spectroscopic surveys of SDSS and the Large Sky Area Multi-object Fiber Spectroscopic Telescope (LAMOST), we cross-match the XMM-WISE-SDSS sample with sources of known spectral classes, and obtain known samples of stars, galaxies, and quasars. The distribution of stars, galaxies, and quasars as well as all spectral classes of stars in 2D parameter space is presented. Various machine-learning methods are applied to different samples from different bands. The better classified results are retained. For the sample from the X-ray band, a rotation-forest classifier performs the best. For the sample from the X-ray and infrared bands, a random-forest algorithm outperforms all other methods. For the samples from the X-ray, optical, and/or infrared bands, the LogitBoost classifier shows its superiority. Thus, all X-ray sources in the 4XMM-DR9 catalogue with different input patterns are classified by their respective models that are created by these best methods. Their membership of and membership probabilities for individual X-ray sources are assigned. The classified result will be of great value for the further research of X-ray sources in greater detail.
Finding Quasars behind the Galactic Plane. I. Candidate Selections with Transfer Learning
Fu, Yuming ; Wu, Xue-Bing ; Yang, Qian ; Brown, Anthony G. A. ; Feng, Xiaotong ; Ma, Qinchun ; Li, Shuyan
DOI:10.12149/101051
Paper Title:
Finding Quasars behind the Galactic Plane. I. Candidate Selections with Transfer Learning
Publication:
The Astrophysical Journal Supplement Series
Quasars behind the Galactic plane (GPQs) are important astrometric references and useful probes of Milky Way gas. However, the search for GPQs is difficult due to large extinctions and high source densities in the Galactic plane. Existing selection methods for quasars developed using high Galactic latitude (high-b) data cannot be applied to the Galactic plane directly because the photometric data obtained from high-b regions and the Galactic plane follow different probability distributions. To alleviate this data set shift problem for quasar candidate selection, we adopt a transfer-learning framework at both the data and algorithm levels. At the data level, to make a training set in which a data set shift is modeled, we synthesize quasars and galaxies behind the Galactic plane based on SDSS sources and the Galactic dust map. At the algorithm level, to reduce the effect of class imbalance, we transform the three-class classification problem for stars, galaxies, and quasars into two binary classification tasks. We apply the XGBoost algorithm to Pan-STARRS1 (PS1) and AllWISE photometry for classification and an additional cut on Gaia proper motion to remove stellar contaminants. We obtain a reliable GPQ candidate catalog with 160,946 sources located at ∣b∣ ≤ 20° in the PS1-AllWISE footprint. Photometric redshifts of GPQ candidates achieved with the XGBoost regression algorithm show that our selection method can identify quasars in a wide redshift range (0 < z ≲ 5). This study extends the systematic searches for quasars to the dense stellar fields and shows the feasibility of using astronomical knowledge to improve data mining under complex conditions in the big-data era.
Photometric studies of five eclipsing binaries: RS Ser, V0449 Per, MR Del, V593 Cen, and V1095 Her
Meng, Gang ; Zhang, Li-yun ; Han, Xianming L. ; Long, Liu ; Misra, Prabhakar ; Lu, Hong-Peng ; Pi, Qingfeng ; Liu, Qiong ; Cheng, Yao ; Wang, Shuai
DOI:10.12149/101053
Paper Title:
Photometric studies of five eclipsing binaries: RS Ser, V0449 Per, MR Del, V593 Cen, and V1095 Her
Publication:
Monthly Notices of the Royal Astronomical Society
RS Ser, V449 Per, MR Del, V593 Cen, and V1095 Her are short-period eclipsing binaries. We made photometric observations on 38 nights using four 1-m-class telescopes and plotted eight light curves. We determined the spectral type of V449 Per as K0(±2)V using low-resolution spectra from the Lijiang 2.4-m telescope. We found cyclic variation in the orbital periods for RS Ser and V1095 Her, and confirmed the cyclic variation of MR Del. The periods of the hypothetical third bodies are close to the duration of observation, and the detected cycles are questionable. For V593 Cen, we followed the previously published suggestion that it probably has a black hole with a minimum mass of 3.68 M⊙. We used the orbital period decreasing at a rate of 8.2(0.1) × 10-8 d yr-1 to explain it. There are two alternative interpretations, and hence the black hole candidate of V593 Cen remains questionable because the minimum points are concentrated in four clusters. The period of V449 Per increases continuously at a rate of 9.5 × 10-8 d yr-1, which can be attributed to mass transfer from the less massive component to the more massive component. For MR Del, we used a new light curve and the published radial velocity to revise its absolute parameters. Furthermore, we revised the photometric solution of V593 Cen and confirmed it as an early-type contact binary with a higher contact factor. We obtained preliminary photometric parameters for RS Ser, V1095 Her, and V449 Per.
Galactic O-type Stars in LAMOST Data
Li, Guang-Wei
DOI:10.12149/101049
Paper Title:
Galactic O-type Stars in LAMOST Data
Publication:
The Astrophysical Journal Supplement Series
This paper reports 209 O-type stars found with LAMOST. All 135 new O-type stars discovered so far with LAMOST are given. Among them, 94 stars are first presented in this sample. There are 1 Iafpe star, 5 Onfp stars, 12 Oe stars, 1 Ofc stars, 3 ON stars, 16 double-lined spectroscopic binaries, and 33 single-lined spectroscopic binaries. All O-type stars are determined based on LAMOST low-resolution spectra (R ∼ 1800), with their LAMOST median-resolution spectra (R ∼ 7500) as supplements.
New precise positions in 2013–2019 and a catalog of ground-based astrometric observations of 11 Neptunian satellites (1847–2019) based on Gaia-DR2
Yuan, Ye ; Li, Fan ; Fu, Yanning ; Ren, Shulin
DOI:10.12149/101047
Paper Title:
New precise positions in 2013–2019 and a catalog of ground-based astrometric observations of 11 Neptunian satellites (1847–2019) based on Gaia-DR2
Publication:
Astronomy and Astrophysics
Context. Developing high-precision ephemerides for Neptunian satellites requires not only the continuation of observing campaigns but also the collection and improvement of existing observations. So far, no complete catalogs of observations of Neptunian satellites are available. Aims: We aim to provide new, precise positions, and to compile a catalog including all available ground-based astrometric observations of Neptunian satellites. The observations are tabulated in a single and consistent format and given in the same timescale, the Terrestrial Time (TT), and reference system, the International Celestial Reference System (ICRS), including necessary changes and corrections. Methods: New CCD observations of Triton and Nereid were made at Lijiang 2.4-m and Yaoan 0.8-m telescopes in 2013–2019, and then reduced based on Gaia-DR2. Furthermore, a catalog called OCNS2019 (Observational Catalog of Neptunian Satellites (2019 version)) was compiled, after recognizing and correcting errors and omissions. Furthermore, in addition to what was considered for the COSS08 catalog for eight main Saturnian satellites, all observed absolute and relative coordinates were converted to the ICRS with corrections for star catalog biases with respect to Gaia-DR2. New debiasing tables for both the modern and old star catalogs, which were previously not provided based on Gaia-DR2, are developed and applied. Treatment of missing positions of comparison bodies in conversions of observed relative coordinates are proposed. Results: OCNS2019 and the new debiasing tables are publicly available online. OCNS2019 includes 24996 observed coordinates of 11 Neptunian satellites obtained over 3741 nights from 1847 to 2019. All observations are given in TT and ICRS. The star catalog biases are removed, which are significant for Nereid and outer satellites. We obtained 880 (5% of total now available) new coordinates for Triton over 41 nights (1% of total observation nights so far), and 790 (14%) for Nereid over 47 nights (10%). The dispersions of these new positions are about 0.″03 for Triton and 0.″06 for Nereid. Conclusions: OCNS2019 should be useful in improving ephemerides for the above-mentioned objects.
Compressive Shack-Hartmann wavefront sensor based on deep neural networks
Jia, Peng ; Ma, Mingyang ; Cai, Dongmei ; Wang, Weihua ; Li, Juanjuan ; Li, Can
DOI:10.12149/101045
Paper Title:
Compressive Shack-Hartmann wavefront sensor based on deep neural networks
Publication:
Monthly Notices of the Royal Astronomical Society
The Shack-Hartmann wavefront sensor is widely used to measure aberrations induced by atmospheric turbulence in adaptive optics systems. However, if strong atmospheric turbulence exists or the brightness of guide stars is low, the accuracy of wavefront measurements will be affected. In this work, we propose a compressive Shack-Hartmann wavefront sensing method. Instead of reconstructing wavefronts with slope measurements of all subapertures, our method reconstructs wavefronts with slope measurements of subapertures that have spot images with high signal-to-noise ratio. We further propose to use a deep neural network to accelerate the wavefront reconstruction speed. During the training stage of the deep neural network, we propose to add a drop-out layer to simulate the compressive sensing process, which could increase the development speed of our method. After training, the compressive Shack-Hartmann wavefront sensing method can reconstruct wavefronts at high spatial resolution with slope measurements from only a small number of subapertures. We integrate the straightforward compressive Shack-Hartmann wavefront sensing method with an image deconvolution algorithm to develop a high-order image restoration method. We use images restored by the high-order image restoration method to test the performance of our compressive Shack-Hartmann wavefront sensing method. The results show that our method can improve the accuracy of wavefront measurements and is suitable for real-time applications.
M-subdwarf Research. II. Atmospheric Parameters and Kinematics
Zhang, Shuo ; Luo, A. -Li ; Comte, Georges ; Wang, Rui ; Li, Yin-Bi ; Du, Bing ; Hou, Wen ; Qin, Li ; Gizis, John ; Chen, Jian-Jun ; Chen, Xiang-Lei ; Lu, Yan ; Song, Yi-Han ; Zhang, Hua-Wei ; Zuo, Fang
DOI:10.12149/101043
Paper Title:
M-subdwarf Research. II. Atmospheric Parameters and Kinematics
Publication:
The Astrophysical Journal
We applied the revised M subdwarf classification criteria discussed in Zhang et al. to Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) DR7 and combined the result with the M subdwarf sample from Savcheva et al. to construct a new M subdwarf sample for further study. The atmospheric parameters for each object were derived from fitting to the PHOENIX grid, and the sources with available astrometry and photometry from Gaia DR2 were combined for further analysis. The relationship between the gravity and metallicity was explored according to the locus both in the color-absolute magnitude diagram and the reduced proper motion diagram. Objects that have both the largest gravity and the lowest metallicity are located away from the main-sequence cloud and may be considered as the intrinsic M subdwarfs, which can be classified as luminosity class VI. Another group of objects whose spectra show typical M subdwarf characteristics have lower gravity and relatively moderate metal deficiency and occupy part of the ordinary M dwarf region in both diagrams. The Galactic U, V, W space velocity components and their dispersion show that the local Galactic halo population sampled in the solar neighborhood is represented by objects of high gravity and an inconspicuous bimodal metallicity distribution, with a fraction of prograde orbits. The other M subdwarfs seem to belong in part to the thick disk component, with a significant fraction of thin disk, moderately metal-poor objects intricately mixed with them. However, selection effects, especially the favored anticenter direction of investigation in the LAMOST subsample, as well as contamination by multiplicity and parameter coupling, could play important roles and need to be investigated further.
Three-dimensional Distribution of the Interstellar Dust in the Milky Way
Guo, H. -L. ; Chen, B. -Q. ; Yuan, H. -B. ; Huang, Y. ; Liu, D. -Z ; Yang, Y. ; Li, X. -Y. ; Sun, W. -X. ; Liu, X. -W.
DOI:10.12149/101032
Paper Title:
Three-Dimensional Distribution of the Interstellar Dust in the Milky Way
Publication:
arXiv e-prints
We present a three-dimensional (3D) extinction map of the southern sky. The map covers the SkyMapper Southern Survey (SMSS) area of ∼14,000 deg2 and has spatial resolutions between 6'9 and 27'. Based on the multi-band photometry of SMSS, the Two Micron All Sky Survey, the Wide-Field Infrared Survey Explorer Survey, and the Gaia mission, we have estimated values of the r-band extinction for ∼19 million stars with the spectral energy distribution analysis. Together with the distances calculated from the Gaia data release 2 (DR2) parallaxes, we have constructed a 3D extinction map of the southern sky. By combining our 3D extinction map with those from the literature, we present an all-sky 3D extinction map, and use it to explore the 3D distribution of the Galactic dust grains. We use two different models, one consisting of a single disk and another of two disks, to fit the 3D distribution of the Galactic dust grains. The data is better fitted by a two-disk model, yielding smaller values of the Bayesian Information Criterion. The best-fit model has scale heights of 73 and 225 pc for the "thin" and "thick" dust disks, respectively.
Data-driven image restoration with option-driven learning for big and small astronomical image data sets
Jia, Peng ; Ning, Ruiyu ; Sun, Ruiqi ; Yang, Xiaoshan ; Cai, Dongmei
DOI:10.12149/101041
Paper Title:
Data--driven Image Restoration with Option--driven Learning for Big and Small Astronomical Image Datasets
Publication:
arXiv e-prints
Image restoration methods are commonly used to improve the quality of astronomical images. In recent years, developments of deep neural networks and increments of the number of astronomical images have evoked a lot of data-driven image restoration methods. However, most of these methods belong to supervised learning algorithms, which require paired images either from real observations or simulated data as training set. For some applications, it is hard to get enough paired images from real observations and simulated images are quite different from real observed ones. In this paper, we propose a new data-driven image restoration method based on generative adversarial networks with option-driven learning. Our method uses several high-resolution images as references and applies different learning strategies when the number of reference images is different. For sky surveys with variable observation conditions, our method can obtain very stable image restoration results, regardless of the number of reference images.
591 High-velocity Stars in the Galactic Halo Selected from LAMOST DR7 and Gaia DR2
Li, Yin-Bi ; Luo, A. -Li ; Lu, You-Jun ; Zhang, Xue-Sen ; Li, Jiao ; Wang, Rui ; Zuo, Fang ; Xiang, Maosheng ; Ting, Yuan-Sen ; Marchetti, Tommaso ; Li, Shuo ; Wang, You-Fen ; Zhang, Shuo ; Hattori, Kohei ; Zhao, Yong-Heng ; Zhang, Hua-Wei ; Zhao, Gang
DOI:10.12149/101038
Paper Title:
591 High-velocity Stars in the Galactic Halo Selected from LAMOST DR7 and Gaia DR2
Publication:
The Astrophysical Journal Supplement Series
In this paper, we report 591 high-velocity star candidates (HiVelSCs) selected from over 10 million spectra of Data Release 7 (DR7) of the Large Sky Area Multi-object Fiber Spectroscopic Telescope and the second Gaia data release, with three-dimensional velocities in the Galactic rest frame larger than 445 km s-1. We show that at least 43 HiVelSCs are unbound to the Galaxy with escape probabilities larger than 50%, and this number decreases to eight if the possible parallax zero-point error is corrected. Most of these HiVelSCs are metal-poor and slightly α-enhanced inner halo stars. Only 14% of them have [Fe/H] > -1, which may be the metal-rich "in situ" stars in the halo formed in the initial collapse of the Milky Way or metal-rich stars formed in the disk or bulge but kinematically heated. The low ratio of 14% implies that the bulk of the stellar halo was formed from the accretion and tidal disruption of satellite galaxies. In addition, HiVelSCs on retrograde orbits have slightly lower metallicities on average compared with those on prograde orbits; meanwhile, metal-poor HiVelSCs with [Fe/H] < -1 have an even faster mean retrograde velocity compared with metal-rich HiVelSCs. To investigate the origins of HiVelSCs, we perform orbit integrations and divide them into four types, i.e., hypervelocity stars, hyper-runaway stars, runaway stars and fast halo stars. A catalog for these 591 HiVelSCs, including radial velocities, atmospheric parameters, Gaia astrometric parameters, spatial positions, and velocities, etc., is available in the China-VO PaperData Repository at doi:10.12149/101038.
A Catalog of Short Period Spectroscopic and Eclipsing Binaries Identified from the LAMOST and PTF Surveys
Yang, Fan ; Long, Richard J. ; Shan, Su-Su ; Zhang, Bo ; Guo, Rui ; Bai, Yu ; Bai, Zhongrui ; Cui, Kai-Ming ; Wang, Song ; Liu, Ji-Feng
DOI:10.12149/101036
Paper Title:
A Catalog of Short Period Spectroscopic and Eclipsing Binaries Identified from the LAMOST and PTF Surveys
Publication:
The Astrophysical Journal Supplement Series
Binaries play key roles in determining stellar parameters and exploring stellar evolution models. We build a catalog of 88 eclipsing binaries with spectroscopic information, taking advantage of observations from both the Large Sky Area Multi-Object fiber Spectroscopic Telescope and the Palomar Transient Factory surveys. A software pipeline is constructed to identify binary candidates by examining their light curves. The orbital periods of binaries are derived from the Lomb-Scargle method. The key distinguishing features of eclipsing binaries are recognized by a new filter, Flat Test. We classify the eclipsing binaries by applying a Fourier analysis on the light curves. Among all the binary stars, 13 binaries are identified as eclipsing binaries for the first time. The catalog contains the following information: the position, primary eclipsing magnitude and time, eclipsing depth, the number of photometry and radial velocity observations, largest radial velocity difference, binary type, the effective temperature of the observable star Teff, and surface gravity of the observable star log g. The false-positive probability is calculated by using both a Monte Carlo simulation and real data from the Sloan Digital Sky Survey Stripe 82 Standard Catalog. The binaries in the catalog are mostly with a period of less than one day. The period distribution shows a 0.22 day cutoff, which is consistent with the low probability of an eclipsing binary rotating with such a period.
Central velocity dispersion catalogue of LAMOST-DR7 galaxies
Napolitano, Nicola R. ; D'Ago, Giuseppe ; Tortora, Crescenzo ; Zhao, Gang ; Luo, A. -Li ; Tang, Baitian ; Zhang, Wei ; Zhang, Yong ; Li, Rui
DOI:10.12149/101034
Paper Title:
Central velocity dispersion catalogue of LAMOST-DR7 galaxies
Publication:
Monthly Notices of the Royal Astronomical Society
The Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) is a major facility to carry out spectroscopic surveys for cosmology and galaxy evolution studies. The seventh data release of the LAMOST ExtraGAlactic Survey (LEGAS) is currently available and including redshifts of 193 361 galaxies. These sources are spread over $\sim 11\, 500$ deg2 of the sky, largely overlapping with other imaging (SDSS and HSC) and spectroscopic (BOSS) surveys. The estimated depth of the galaxy sample, r ∼ 17.8, the high signal-to-noise ratio, and the spectral resolution R = 1800, make the LAMOST spectra suitable for galaxy velocity dispersion (VD) measurements, which are invaluable to study the structure and formation of galaxies and to determine their central dark matter content. We present the first estimates of central VD of $\sim 86\, 000$ galaxies in LAMOST footprint. We have used a wrap-up procedure to perform the spectral fitting using PPXF, and derive VD measurements. Statistical errors are also assessed by comparing LAMOST VD estimates with the ones of SDSS and BOSS over a common sample of $\sim 51\, 000$ galaxies. The two data sets show a good agreement, within the statistical errors, in particular when VD values are corrected to 1 effective radius aperture. We also present a preliminary mass-σ relation and find consistency with previous analyses based on local galaxy samples. These first results suggest that LAMOST spectra are suitable for galaxy VD measurements to complement the available catalogues of galaxy internal kinematics in the Northern hemisphere. We plan to expand this analysis to next LAMOST data releases.
Magnetic Flux of Active Regions Determining the Eruptive Character of Large Solar Flares
Li, Ting ; Hou, Yijun ; Yang, Shuhong ; Zhang, Jun ; Liu, Lijuan ; Veronig, Astrid M.
DOI:10.12149/101030
Paper Title:
Magnetic Flux of Active Regions Determining the Eruptive Character of Large Solar Flares
Publication:
The Astrophysical Journal
We establish the largest eruptive/confined flare database to date and analyze 322 flares of Geostationary Operational Environmental Satellite class M1.0 and larger that occurred during 2010-2019, i.e., almost spanning all of solar cycle 24. We find that the total unsigned magnetic flux ( ${{\rm{\Phi }}}_{\mathrm{AR}}$ ) of active regions (ARs) is a key parameter governing the eruptive character of large flares, with the proportion of eruptive flares exhibiting a strong anticorrelation with ${{\rm{\Phi }}}_{\mathrm{AR}}$ . This means that an AR containing a large magnetic flux has a lower probability that the large flares it produces will be associated with a coronal mass ejection (CME). This finding is supported by the high positive correlation we obtained between the critical decay index height and ${{\rm{\Phi }}}_{\mathrm{AR}}$ , implying that ARs with a larger ${{\rm{\Phi }}}_{\mathrm{AR}}$ have a stronger magnetic confinement. Moreover, the confined flares originating from ARs larger than $1.0\times {10}^{23}$ Mx have several characteristics in common: stable filament, slipping magnetic reconnection, and strongly sheared post-flare loops. Our findings reveal new relations between the magnetic flux of ARs and the occurrence of CMEs in association with large flares. The relations obtained here provide quantitative criteria for forecasting CMEs and adverse space weather, and have important implications for "superflares" on solar-type stars and stellar CMEs.
Optimal probabilistic catalogue matching for radio sources
Fan, Dongwei ; Budavári, Tamás ; Norris, Ray P. ; Basu, Amitabh
DOI:10.12149/101026
Paper Title:
Optimal probabilistic catalogue matching for radio sources
Publication:
Monthly Notices of the Royal Astronomical Society
Cross-matching catalogues from radio surveys to catalogues of sources at other wavelengths is extremely hard, because radio sources are often extended, often consist of several spatially separated components, and often no radio component is coincident with the optical/infrared host galaxy. Traditionally, the cross-matching is done by eye, but this does not scale to the millions of radio sources expected from the next generation of radio surveys. We present an innovative automated procedure, using Bayesian hypothesis testing, that models trial radio-source morphologies with putative positions of the host galaxy. This new algorithm differs from an earlier version by allowing more complex radio-source morphologies, and performing a simultaneous fit over a large field. We show that this technique performs well in an unsupervised mode.
Unveiling the Hierarchical Structure of Open Star Clusters: The Perseus Double Cluster
Yu, Heng ; Shao, Zhengyi ; Diaferio, Antonaldo ; Li, Lu
DOI:10.12149/101022
Paper Title:
Unveiling the Hierarchical Structure of Open Star Clusters: The Perseus Double Cluster
Publication:
The Astrophysical Journal
We introduce a new kinematic method to investigate the structure of open star clusters. We adopt a hierarchical clustering algorithm that uses the celestial coordinates and the proper motions of the stars in the field of view of the cluster to estimate a proxy of the pairwise binding energy of the stars and arrange them in a binary tree. The cluster substructures and their members are identified by trimming the tree at two thresholds, according to the σ-plateau method. Testing the algorithm on 100 mock catalogs shows that, on average, the membership of the identified clusters is (91.5 ± 3.5)% complete and the fraction of unrelated stars is (10.4 ± 2.0)%. We apply the algorithm to the stars in the field of view of the Perseus double cluster from the Data Release 2 of Gaia. This approach identifies a single structure, Sub1, that separates into two substructures, Sub1-1 and Sub1-2. These substructures coincide with h Per and χ Per: the distributions of the proper motions and the color-magnitude diagrams of the members of Sub1-1 and Sub1-2 are fully consistent with those of h Per and χ Per reported in the literature. These results suggest that our hierarchical clustering algorithm can be a powerful tool to unveil the complex kinematic information of star clusters.
Night-time measurements of astronomical seeing at Dome A in Antarctica
Ma, Bin ; Shang, Zhaohui ; Hu, Yi ; Hu, Keliang ; Wang, Yongjiang ; Yang, Xu ; Ashley, Michael C. B. ; Hickson, Paul ; Jiang, Peng
DOI:10.12149/101020
Paper Title:
Night-time measurements of astronomical seeing at Dome A in Antarctica
Publication:
Nature
Seeing—the angular size of stellar images blurred by atmospheric turbulence—is a critical parameter used to assess the quality of astronomical sites at optical/infrared wavelengths. Median values at the best mid-latitude sites are generally in the range of 0.6-0.8 arcseconds1-3. Sites on the Antarctic plateau are characterized by comparatively weak turbulence in the free atmosphere above a strong but thin boundary layer4-6. The median seeing at Dome C is estimated to be 0.23-0.36 arcseconds7-10 above a boundary layer that has a typical height of 30 metres10-12. At Domes A and F, the only previous seeing measurements have been made during daytime13,14. Here we report measurements of night-time seeing at Dome A, using a differential image motion monitor15. Located at a height of just 8 metres, it recorded seeing as low as 0.13 arcseconds, and provided seeing statistics that are comparable to those at a height of 20 metres at Dome C. This indicates that the boundary layer was below 8 metres for 31 per cent of the time, with median seeing of 0.31 arcseconds, consistent with free-atmosphere seeing. The seeing and boundary-layer thickness are found to be strongly correlated with the near-surface temperature gradient. The correlation confirms a median thickness of approximately 14 metres for the boundary layer at Dome A, as found from a sonic radar16. The thinner boundary layer makes it less challenging to locate a telescope above it, thereby giving greater access to the free atmosphere.
Constraining the Milky Way Mass Profile with Phase-space Distribution of Satellite Galaxies
Li, Zhao-Zhou ; Qian, Yong-Zhong ; Han, Jiaxin ; Li, Ting S. ; Wang, Wenting ; Jing, Y. P.
DOI:10.12149/101018
Paper Title:
Constraining the Milky Way Mass Profile with Phase-space Distribution of Satellite Galaxies
Publication:
The Astrophysical Journal
We estimate the Milky Way (MW) halo properties using satellite kinematic data including the latest measurements from Gaia DR2. With a simulation-based 6D phase-space distribution function (DF) of satellite kinematics, we can infer halo properties efficiently and without bias, and handle the selection function and measurement errors rigorously in the Bayesian framework. Applying our DF from the EAGLE simulation to 28 satellites, we obtain an MW halo mass of $M={1.23}_{-0.18}^{+0.21}\times {10}^{12}{M}_{\odot }$ and a concentration of $c={9.4}_{-2.1}^{+2.8}$ with the prior based on the M-c relation. The inferred mass profile is consistent with previous measurements but with better precision and reliability due to the improved methodology and data. Potential improvement is illustrated by combining satellite data and stellar rotation curves. Using our EAGLE DF and best-fit MW potential, we provide much more precise estimates of the kinematics for those satellites with uncertain measurements. Compared to the EAGLE DF, which matches the observed satellite kinematics very well, the DF from the semi-analytical model based on the dark-matter-only simulation Millennium II (SAM-MII) over-represents satellites with small radii and velocities. We attribute this difference to less disruption of satellites with small pericenter distances in the SAM-MII simulation. By varying the disruption rate of such satellites in this simulation, we estimate a ∼5% scatter in the inferred MW halo mass among hydrodynamics-based simulations.
Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide-field Small Aperture Telescopes
Jia, Peng ; Liu, Qiang ; Sun, Yongyang
DOI:10.12149/101016
Paper Title:
Detection and Classification of Astronomical Targets with Deep Neural Networks in Wide-field Small Aperture Telescopes
Publication:
The Astronomical Journal
Wide-field small aperture telescopes are widely used for optical transient observations. Detection and classification of astronomical targets in observed images are the most important and basic step. In this paper, we propose an astronomical target detection and classification framework based on deep neural networks. Our framework adopts the concept of the Faster R-CNN and uses a modified Resnet-50 as a backbone network and a feature pyramid network to extract features from images of different astronomical targets. To increase the generalization ability of our framework, we use both simulated and real observation images to train the neural network. After training, the neural network could detect and classify astronomical targets automatically. We test the performance of our framework with simulated data and find that our framework has almost the same detection ability as that of the traditional method for bright and isolated sources and our framework has two times better detection ability for dim targets, albeit all celestial objects detected by the traditional method can be classified correctly. We also use our framework to process real observation data and find that our framework can improve 25% detection ability than that of the traditional method when the threshold of our framework is 0.6. Rapid discovery of transient targets is quite important and we further propose to install our framework in embedded devices such as the Nvidia Jetson Xavier to achieve real-time astronomical targets detection and classification abilities.
SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey
Wang, Rui ; Luo, A. -Li ; Chen, Jian-Jun ; Hou, Wen ; Zhang, Shuo ; Zhao, Yong-Heng ; Li, Xiang-Ru ; Hou, Yong-Hui ; LAMOST MRS Collaboration
DOI:10.12149/101012
Paper Title:
SPCANet: Stellar Parameters and Chemical Abundances Network for LAMOST-II Medium Resolution Survey
Publication:
The Astrophysical Journal
The fundamental stellar atmospheric parameters (Teff and log g) and 13 chemical abundances are derived for medium-resolution spectroscopy from Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Medium Resolution Survey (MRS) data sets with a deep-learning method. The neural networks we designed, named SPCANet, precisely map LAMOST MRS spectra to stellar parameters and chemical abundances. The stellar labels derived by SPCANet have precisions of 119 K for Teff and 0.17 dex for log g. The abundance precision of 11 elements including [C/H], [N/H], [O/H], [Mg/H], [Al/H], [Si/H], [S/H], [Ca/H], [Ti/H], [Cr/H], [Fe/H], and [Ni/H] are 0.06 ∼ 0.12 dex, while that of [Cu/H] is 0.19 dex. These precisions can be reached even for spectra with signal-to-noise ratios as low as 10. The results of SPCANet are consistent with those from other surveys such as APOGEE, GALAH, and RAVE, and are also validated with the previous literature values including clusters and field stars. The catalog of the estimated parameters is available at doi:10.12149/101012.
PSF-NET: A Nonparametric Point-spread Function Model for Ground-based Optical Telescopes
Jia, Peng ; Wu, Xuebo ; Yi, Huang ; Cai, Bojun ; Cai, Dongmei
DOI:10.12149/101014
Paper Title:
PSF-NET: A Nonparametric Point-spread Function Model for Ground-based Optical Telescopes
Publication:
The Astronomical Journal
Ground-based optical telescopes are seriously affected by atmospheric turbulence induced aberrations. Understanding properties of these aberrations is important both for instrument design and image restoration method development. Because the point-spread function can reflect performance of the whole optic system, it is appropriate to use the point-spread function to describe atmospheric turbulence induced aberrations. Assuming point-spread functions induced by the atmospheric turbulence with the same profile belong to the same manifold space, we propose a nonparametric point-spread function -- PSF-NET. The PSF-NET has a cycle convolutional neural network structure and is a statistical representation of the manifold space of PSFs induced by the atmospheric turbulence with the same profile. Testing the PSF-NET with simulated and real observation data, we find that a well trained PSF-NET can restore any short exposure images blurred by atmospheric turbulence with the same profile. Besides, we further use the impulse response of the PSF-NET, which can be viewed as the statistical mean PSF, to analyze interpretation properties of the PSF-NET. We find that variations of statistical mean PSFs are caused by variations of the atmospheric turbulence profile: as the difference of the atmospheric turbulence profile increases, the difference between statistical mean PSFs also increases. The PSF-NET proposed in this paper provides a new way to analyze atmospheric turbulence induced aberrations, which would benefit the development of new observation methods for ground-based optical telescopes.
The Separation Distribution of Ultrawide Binaries across Galactic Populations

DOI:10.12149/101010
Paper Title:
The Separation Distribution of Ultrawide Binaries across Galactic Populations
Publication:
The Astrophysical Journal Supplement Series
We have compiled an extensive catalog of candidate wide binaries selected from Gaia DR2 in the solar neighborhood with distances $d<4$~kpc, following a procedure similar to that of El-Badry & Rix(2018). This initial candidate catalog consists of 807,611 possible binaries. Its contamination rates are lower than 10% at $a<20,000$~AU; however, the contamination rates quickly increase beyond 20,000~AU, until up to 100% at the largest separation bin, i.e., a = 1.0 pc. To address this, we subsequently applied additional selection criteria, tailored towards three kinematically-selected, presumably pure subsamples: 4361 disk-like, 10090 intermediate, and 4351 halo-like binaries.
LAMOST Medium Resolution Survey Radial Velocity Catalog
Wang, R. ; Luo, A. -L. ; Chen, J. -J. ; Bai, Z. -R. ; Chen, L. ; Chen, X. -F. ; Dong, S. -B. ; Du, B. ; Fu, J. -N. ; Han, Z. -W. ; Hou, J. -L. ; Hou, Y. -H. ; Hou, W. ; Jiang, D. -K. ; Kong, X. ; Li, L. -F. ; Liu, C. ; Liu, J. -M. ; Qin, L. ; Shi, J. -R. ; Tian, H. ; Wu, H. ; Wu, C. -J. ; Xie, J. -W. ; Zhang, H. -T. ; Zhang, S. ; Zhao, G. ; Zhao, Y. -H. ; Zhong, J. ; Zong, W. -K. ; Zuo, F.
DOI:10.12149/101008
Paper Title:
Properties of Radial Velocities Measurement Based on LAMOST-II Medium-resolution Spectroscopic Observations
Publication:
The Astrophysical Journal Supplement Series
The radial velocity (RV) is a basic physical quantity that can be determined through the Doppler shift of the spectrum of a star. The precision of the RV measurement depends on the resolution of the spectrum we used and the accuracy of wavelength calibration. In this work, radial velocities of the Large Sky Area Multi-Object Fibre Spectroscopic Telescope-II (LAMOST-II) medium-resolution (R ∼ 7500) spectra are measured for 1,594,956 spectra (each spectrum has two wavebands) through matching with templates. A set of RV standard stars are used to recalibrate the zero point of the measurement, and some reference sets with RVs derived from medium-/high-resolution observations are used to evaluate the accuracy of the measurement. By comparing with reference sets, the accuracy of our measurement can get 0.0277 km s-1 with respect to radial velocities of standard stars. The intrinsic precision is estimated with the multiple observations of single stars, which can be achieved to 1.36 km s-1, 1.08 km s-1, and 0.91 km s-1 for the spectra at signal-to-noise levels of 10, 20, and 50, respectively.
Solar Image Restoration with the CycleGAN Based on Multi-fractal Properties of Texture Features
Jia, Peng ; Huang, Yi ; Cai, Bojun ; Cai, Dongmei
DOI:10.12149/101006
Paper Title:
Solar Image Restoration with the CycleGAN Based on Multi-fractal Properties of Texture Features
Publication:
The Astrophysical Journal
Texture is one of the most obvious characteristics in solar images and it is normally described by texture features. Because textures from solar images of the same wavelength are similar, we assume that texture features of solar images are multi-fractals. Based on this assumption, we propose a pure data-based image restoration method: with several high-resolution solar images as references, we use the Cycle-Consistent Adversarial Network to restore blurred images of the same steady physical process, in the same wavelength obtained by the same telescope. We test our method with simulated and real observation data and find that our method can improve the spatial resolution of solar images, without loss of any frames. Because our method does not need a paired training set or additional instruments, it can be used as a post-processing method for solar images obtained by either seeing-limited telescopes or telescopes with ground-layer adaptive optic systems.