分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Massive binary stars play a crucial role in many astrophysical fields. Investigating the statistical properties of massive binary stars is essential to trace the formation of massive stars and constrain the evolution of stellar populations. However, no consensus has been achieved on the statistical properties of massive binary stars, mainly due to the lack of a large and homogeneous sample of spectroscopic observations. We study the intrinsic binary fraction $f_{\rm b}^{\rm in}$ and distributions of mass ratio $f(q)$ and orbital period $f(P)$ of early-type stars (comprised of O-, B-, and A-type stars) and investigate their dependences on effective temperature $T_{\rm eff}$, stellar metallicity [M/H], and the projection velocity $v\sin{i}$, based on the homogeneous spectroscopic sample from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release Eight (DR8). We found that $f_{\rm b}^{\rm in}$ increases with increasing $T_\mathrm{eff}$. The binary fraction is positively correlated with metallicity for spectra in the sample. Over all the $v\sin{i}$ values we considered, the $f_{\rm b}^{\rm in}$ have constant values of $\sim$50\%. It seems that the binary population is relatively evenly distributed over a wide range of $v\sin{i}$ values, while the whole sample shows that most of the stars are concentrated at low values of $v\sin{i}$ (probably from strong wind and magnetic braking of single massive stars) and at high values of $v\sin{i}$ (likely from the merging of binary stars). Stellar evolution and binary interaction may be partly responsible for this.There are no correlations found between $\pi$($\gamma$) and $T_{\rm eff}$, nor for $\pi$($\gamma$) and [M/H]. The uncertainties of the distribution decrease toward a larger sample size with higher observational cadence.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
摘要： Massive binary stars play a crucial role in many astrophysical fields. Investigating the statistical properties of massive binary stars is essential to trace the formation of massive stars and constrain the evolution of stellar populations. However, no consensus has been achieved on the statistical properties of massive binary stars, mainly due to the lack of a large and homogeneous sample of spectroscopic observations. We study the intrinsic binary fraction $f_{\rm b}^{\rm in}$ and distributions of mass ratio $f(q)$ and orbital period $f(P)$ of early-type stars (comprised of O-, B-, and A-type stars) and investigate their dependences on effective temperature $T_{\rm eff}$, stellar metallicity [M/H], and the projection velocity $v\sin{i}$, based on the homogeneous spectroscopic sample from the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) Data Release Eight (DR8). We found that $f_{\rm b}^{\rm in}$ increases with increasing $T_\mathrm{eff}$. The binary fraction is positively correlated with metallicity for spectra in the sample. Over all the $v\sin{i}$ values we considered, the $f_{\rm b}^{\rm in}$ have constant values of $\sim$50\%. It seems that the binary population is relatively evenly distributed over a wide range of $v\sin{i}$ values, while the whole sample shows that most of the stars are concentrated at low values of $v\sin{i}$ (probably from strong wind and magnetic braking of single massive stars) and at high values of $v\sin{i}$ (likely from the merging of binary stars). Stellar evolution and binary interaction may be partly responsible for this.There are no correlations found between $\pi$($\gamma$) and $T_{\rm eff}$, nor for $\pi$($\gamma$) and [M/H]. The uncertainties of the distribution decrease toward a larger sample size with higher observational cadence.
分类： 天文学 >> 天文学 提交时间： 2023-02-19
YanJun Guo
Bo Zhang
Chao Liu
Jiao Li
JiangDan Li
LuQian Wang
ZhiCun Liu
YongHui Hou
ZhanWen Han
XueFei Chen
摘要： Massive stars play key roles in many astrophysical processes. Deriving atmospheric parameters of massive stars is important to understand their physical properties and thus are key inputs to trace their evolution. Here we report our work on adopting the data-driven technique Stellar LAbel Machine ({\tt SLAM}) with the non-LTE TLUSTY synthetic spectra as the training dataset to estimate the stellar parameters of LAMOST optical spectra for early-type stars. We apply two consistency tests to verify this machine learning method and compare stellar labels given by {\tt SLAM} with that in literature for several objects having high-resolution spectra. We provide the stellar labels of effective temperature ($T_\mathrm{eff}$), surface gravity ($\log{g}$), metallicity ([M/H]), and projected rotational velocity ($v\sin{i}$) for 3,931 and 578 early-type stars from LAMOST Low-Resolution Survey (LAMOST-LRS) and Medium-Resolution Survey (LAMOST-MRS), respectively. To estimate the average statistical uncertainties of our results, we calculated the standard deviation between the predicted stellar label and the pre-labeled published values from the high-resolution spectra. The uncertainties of the four parameters are $\sigma(T_\mathrm{eff}) = 2,185 $K, $\sigma(\log{g}) = 0.29$ dex, and $\sigma(v\sin{i}) = 11\, \rm km\,s^{-1}$ for MRS, and $\sigma(T_\mathrm{eff}) = 1,642 $K, $\sigma(\log{g}) = 0.25$ dex, and $\sigma(v\sin{i}) = 42\, \rm km\,s^{-1}$ for LRS spectra, respectively. We notice that parameters of $T_\mathrm{eff}$, $\log{g}$ and [M/H] can be better constrained using LRS spectra rather than using MRS spectra, most likely due to their broad wavelength coverage, while $v\sin{i}$ is constrained better by MRS spectra than by LRS spectra, probably due to the relatively accurate line profiles of MRS spectra.
点击量
待评议
点击量
下载量
评论
