利用StarTrack模型经验确定银河系中子星--黑洞并合率
Empirical determination of the Galactic neutron star--black hole merger rate using StarTrack models
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中文总结 AI 辅助
本研究利用StarTrack模型和射电脉冲星巡天数据，确定银河系中子星--黑洞并合率上限，并预测LIGO探测率，强调FAST等望远镜的探测前景。
中文摘要 AI 辅助
在双星系统中发现与黑洞相伴的脉冲星，将为强场区域内的广义相对论检验提供独特的实验室，并为大质量恒星演化提供重要约束。我们利用射电脉冲星种群和巡天模型（在建模包PsrPopPy内），并作为原理验证，采用恒星种群合成代码StarTrack中两种不同公共包层阶段处理的演化模型，评估此类系统的可探测性前景。对于这两种模型，假设Tauris和Manchester提出的射电脉冲星波束模型，并考虑轨道运动对脉冲星可探测性的影响，鉴于当前射电巡天中未探测到任何射电脉冲星--黑洞双星系统，我们计算了银河系内中子星--黑洞系统数量的上限及相应的并合率。对于约束最强的模型，我们发现银河系并合率$< 4.3~\text{Myr}^{-1}$（95%置信度）。这些结果被外推到第五次LIGO观测运行的预期视界距离，得到的LIGO探测率估计与LIGO-Virgo-KAGRA合作组报告的最新值一致。我们的结果表明，FAST、MeerKAT和DSA灵敏度的提高为揭示这一难以捉摸的种群提供了迄今最佳前景。
英文摘要
The discovery of a pulsar in a binary system with a black hole would provide a unique laboratory for testing general relativity in the strong-field regime and offer vital constraints on massive star evolution. We assess prospects for the detectability of such systems by utilizing the radio pulsar population and survey models within the modeling package PsrPopPy and, as a proof of principle, two evolutionary models with different treatments of common-envelope phases from the stellar population synthesis code StarTrack. For these two models, assuming the radio pulsar beaming model proposed by Tauris and Manchester and accounting for the effects of orbital motion on pulsar detectability, we calculate upper limits on the number of neutron star--black hole systems in the Galaxy and the corresponding merger rate given the lack of any radio-detected pulsar--black hole binary systems in current radio surveys. For the most constraining model, we find a Galactic merger rate $< 4.3~\text{Myr}^{-1}$ (at 95\% confidence). These results are extrapolated to the expected horizon distance for the fifth LIGO observing run, leading to LIGO detection rate estimates that are consistent with the latest values reported by the LIGO-Virgo-KAGRA collaboration. Our results indicate that the increased sensitivity of FAST, MeerKAT, and DSA offers the best prospects yet for uncovering this elusive population.
发表机构
- West Virginia University（西弗吉尼亚大学）
- University of Idaho（爱达荷大学）
- Texas Tech University（德克萨斯理工大学）
- Oregon State University（俄勒冈州立大学）
- University of Wisconsin-Milwaukee（威斯康星大学密尔沃基分校）
机构由 AI 辅助整理，请以论文原文为准。
