高分辨率光谱中双线光谱双星的自动检测及恒星多重性的概率分析

中文摘要 AI 辅助

对类太阳恒星的表征，包括确定这些恒星是单星还是具有恒星伴星，对于寻找太阳系外行星的任务变得越来越重要。随着像宜居世界观测站（HWO）这样的即将到来的任务，对恒星进行双星性审查并确认潜在目标是否可行是至关重要的前期科学。在本文中，我们提出了一种在高分辨率光谱中搜索双线光谱双星（SB2s）的自动算法。利用MOLUSC，我们模拟了真实的恒星种群，以量化算法探测邻近恒星周围恒星伴星的能力，并具有应用于HWO目标恒星和Gaia DR4行星宿主候选者的潜力。此外，我们探讨了探测率如何受到互补观测（如高分辨率自适应光学成像和时间序列径向速度）的影响。我们发现，仅我们的SB2探测算法就能排除46.1%的恒星质量伴星。仅高分辨率自适应光学就能排除79.6%的恒星伴星。仅径向速度巡天在5年和10年巡天中分别排除了98.4%和98.7%。当三种方法结合时，典型邻近恒星拥有恒星伴星的概率小于1%。这些方法的结合使我们能够更好地理解和解决未来巡天的目标列表。

英文摘要

The characterization of Sun-like stars, including determining whether those stars are single or have stellar companions, has become increasingly important for missions seeking planets beyond the Solar System. With upcoming missions like the Habitable Worlds Observatory (HWO) on the horizon, vetting stars for binarity and confirming potential targets as viable is essential precursor science. In this paper, we present an automated algorithm that searches for double-lined spectroscopic binaries (SB2s) in high-resolution spectra. Using MOLUSC, we simulate realistic stellar populations to quantify the capability of algorithm for detecting stellar companions around nearby stars, with potential applications to HWO target stars and Gaia DR4 planet-host candidates. In addition, we explore how the detection rate is influenced by complementary observations like high-resolution adaptive optics imaging and time-series radial velocities. We find that our SB2 detection algorithm alone can rule out 46.1% of stellar-mass companions. High-resolution adaptive optics alone rules out 79.6% of stellar companions. Radial velocity surveys alone ruled out 98.4% and 98.7% for 5-year and 10-year surveys, respectively. When all three methods are combined, the probability of a typical nearby star having a stellar companion is <1%. The combination of the methods allows us to better understand and resolve target lists for future surveys.

发表机构

• California State Polytechnic University Pomona（加州州立理工大学波莫纳分校）
• California Institute of Technology（加州理工学院）

机构由 AI 辅助整理，请以论文原文为准。