分类： 天文学 >> 天文学 提交时间： 2023-02-19
Bo Zhang
Ying-Jie Jing
Fan Yang
Jun-Chen Wan
Xin Ji
Jian-Ning Fu
Chao Liu
Xiao-Bin Zhang
Feng Luo
Hao Tian
Yu-Tao Zhou
Jia-Xin Wang
Yan-Jun Guo
Weikai Zong
Jian-Ping Xiong
Jiao Li
摘要： We developed a convolutional neural network (CNN) model to distinguish the double-lined spectroscopic binaries (SB2s) from others based on single exposure medium-resolution spectra ($R\sim 7,500$). The training set consists of a large set of mock spectra of single stars and binaries synthesized based on the MIST stellar evolutionary model and ATLAS9 atmospheric model. Our model reaches a novel theoretic false positive rate by adding a proper penalty on the negative sample (e.g., 0.12\% and 0.16\% for the blue/red arm when the penalty parameter $\Lambda=16$). Tests show that the performance is as expected and favors FGK-type Main-sequence binaries with high mass ratio ($q \geq 0.7$) and large radial velocity separation ($\Delta v \geq 50\,\mathrm{km\,s^{-1}}$). Although the real false positive rate can not be estimated reliably, validating on eclipsing binaries identified from Kepler light curves indicates that our model predicts low binary probabilities at eclipsing phases (0, 0.5, and 1.0) as expected. The color-magnitude diagram also helps illustrate its feasibility and capability of identifying FGK MS binaries from spectra. We conclude that this model is reasonably reliable and can provide an automatic approach to identify SB2s with period $\lesssim 10$ days. This work yields a catalog of binary probabilities for over 5 million spectra of 1 million sources from the LAMOST medium-resolution survey (MRS), and a catalog of 2198 SB2 candidates whose physical properties will be analyzed in our following-up paper. Data products are made publicly available at the journal as well as our Github website.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Binary stars plays important role in the evolution of stellar populations . The intrinsic binary fraction ($f_{bin}$) of O and B-type (OB) stars in LAMOST DR5 was investigated in this work. We employed a cross-correlation approach to estimate relative radial velocities for each of the stellar spectra. The algorithm described by \cite{2013A&A...550A.107S} was implemented and several simulations were made to assess the performance of the approach. Binary fraction of the OB stars are estimated through comparing the uni-distribution between observations and simulations with the Kolmogorov-Smirnov tests. Simulations show that it is reliable for stars most of whom have $6,7$ and $8$ repeated observations. The uncertainty of orbital parameters of binarity become larger when observational frequencies decrease. By adopting the fixed power exponents of $\pi=-0.45$ and $\kappa=-1$ for period and mass ratio distributions, respectively, we obtain that $f_{bin}=0.4_{-0.06}^{+0.05}$ for the samples with more than 3 observations. When we consider the full samples with at least 2 observations, the binary fraction turns out to be $0.37_{-0.03}^{+0.03}$. These two results are consistent with each other in $1\sigma$.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
Yanjun Guo
Jiao Li
Jianping Xiong
Jiangdan Li
Luqian Wang
Heran Xiong
Feng Luo
Yonghui Hou
Chao Liu
Zhanwen Han
Xuefei Chen
摘要： Massive binaries play significant roles in many fields. Identification of massive stars, particularly massive binaries, is of great importance. In this paper, by adopting the technique of measuring the equivalent widths of several spectral lines, we identified 9,382 early-type stars from LAMOST medium-resolution survey and divided the sample into four groups, T1 ($\sim$O-B4), T2 ($\sim$B5), T3 ($\sim$B7), and T4 ($\sim$B8-A). The relative radial velocities $RV_{\rm rel}$ were calculated using the Maximum Likelihood Estimation. The stars with significant changes of $RV_{\rm rel}$ and at least larger than 15.57km s$^{-1}$ were identified as spectroscopic binaries. We found that the observed spectroscopic binary fractions for the four groups are $24.6\%\pm0.5\%$, $20.8\%\pm0.6\%$, $13.7\%\pm0.3\%$, and $7.4\%\pm0.3\%$, respectively. Assuming that orbital period ($P$) and mass ratio ($q$) have intrinsic distributions as $f(P) \propto P^\pi$ (1\textless$P$\textless1000 days) and $f(q) \propto q^\kappa$ (0.1\textless$q$\textless1), respectively, we conducted a series of Monte-Carlo simulations to correct observational biases for estimating the intrinsic multiplicity properties. The results show that the intrinsic binary fractions for the four groups are 68$\%\pm8\%$, 52$\%\pm3\%$, 44$\%\pm6\%$, and 44$\%\pm6\%$, respectively. The best estimated values for $\pi$ are -1$\pm0.1$, -1.1$\pm0.05$, -1.1$\pm0.1$, and -0.6$\pm0.05$, respectively. The $\kappa$ cannot be constrained for groups T1 and T2 and is -2.4$\pm0.3$ for group T3 and -1.6$\pm0.3$ for group T4. We confirmed the relationship of a decreasing trend in binary fractions towards late-type stars. No correlation between the spectral type and the orbital period distribution has been found yet, possibly due to the limitation of observational cadence.
点击量
待评议
点击量
下载量
评论
