Gaia DR3 AstroSpectroSB1双星系统的伴星质量：一个贝叶斯前向建模框架
Companion masses of Gaia DR3 AstroSpectroSB1 binaries: a Bayesian forward-modelling framework
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中文总结 AI 辅助
提出贝叶斯前向建模框架，利用盖亚DR3数据估计AstroSpectroSB1双星系统伴星质量，在1035个系统中验证并推断出113个可靠伴星质量，为后续观测提供候选。
中文摘要 AI 辅助
盖亚数据发布3（Gaia DR3）通过为大量非单星提供联合的天体测量和光谱轨道解，极大地扩展了对未分辨双星系统的研究。我们提出了一个贝叶斯前向建模框架，用于估计Gaia DR3 AstroSpectroSB1系统中的伴星质量。该方法对每个双星的物理参数进行采样，预测相应的天体测量Thiele-Innes常数和光谱轨道系数，并使用盖亚发布的全协方差矩阵评估其似然。引入了一个关于主星质量的外部先验，以解决单线系统中分量质量与轨道倾角之间的剩余简并。我们将此框架应用于1035个AstroSpectroSB1系统，其主星质量估计取自Gaia DR3的astrophysical_parameters表。其中，760个系统也有盖亚报告的两个分量质量估计，用作验证样本。其余275个系统构成一个推断样本，用于估计较暗的、未分辨伴星的质量。对于后验收敛良好的系统，推断参数再现了盖亚的轨道观测量，而验证样本中恢复的伴星质量与盖亚估计一致。在推断样本中，我们发现了113个收敛良好的系统，其伴星质量得到了有意义的推断。我们发现该群体以普通恒星为主，同时存在一个较小的高质量尾部，可能包含大质量白矮星或其他致密天体候选体。我们的框架提供了一种可扩展的方法，用于将盖亚AstroSpectroSB1解转换为伴星质量后验分布，识别适合进行针对性后续观测的有前景的系统，并为预期在Gaia DR4中获得的更大、更精确的轨道样本做准备。
英文摘要
Gaia Data Release 3 (DR3) has substantially expanded the study of unresolved binaries by providing combined astrometric and spectroscopic orbital solutions for a large sample of non-single stars. We present a Bayesian forward-modelling framework for estimating companion masses in Gaia DR3 \texttt{AstroSpectroSB1} systems. The method samples the physical parameters of each binary, predicts the corresponding astrometric Thiele-Innes constants and spectroscopic orbital coefficients, and evaluates their likelihood using the full covariance matrix published by Gaia. An external prior on the primary mass is incorporated to resolve the remaining degeneracy between the component masses and orbital inclination in single-lined systems. We apply this framework to 1035 \texttt{AstroSpectroSB1} systems with primary-mass estimates drawn from the Gaia DR3 \texttt{astrophysical\_parameters} table. Of these, 760 systems also have Gaia-reported estimates for both component masses and are used as a validation sample. The remaining 275 systems constitute an inference sample for which the mass of the fainter, unresolved companion is estimated. For systems with well converged posteriors, the inferred parameters reproduce the Gaia orbital observables, while the companion masses recovered for the validation sample are consistent with the Gaia estimates. In the inference sample we find 113 well converged systems for which the companion masses are meaningfully inferred. We find that the population is dominated by ordinary stars, together with a smaller high-mass tail that may contain massive white dwarfs or other compact-object candidates. Our framework provides a scalable approach for converting Gaia AstroSpectroSB1 solutions into companion-mass posterior distributions, identifying promising systems for targeted follow-up, and preparing for the larger and more precise orbital samples anticipated with Gaia DR4.
发表机构
- Indian Institute of Technology Madras（印度马德拉斯理工学院）
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