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arXiv 2011.04513astro-ph.SRastro-ph.HE
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多恒星演化:模拟恒星、双星和多恒星系统动力学演化的总体合成算法

Multiple Stellar Evolution: a population synthesis algorithm to model the stellar, binary, and dynamical evolution of multiple-star systems

Adrian S. Hamers, Antti Rantala, Patrick Neunteufel, Holly Preece, Pavan Vynatheya

摘要:

近年来的观测显示,多星系统,如等级三星和四星系统是常见的,特别是在大质量恒星中。它们是有趣的天体物理现象的潜在来源,如紧凑的物体合并,导致超新星和引力波事件。然而,在其往往复杂的演变过程中,仍有许多不确定因素。在这里,我们提出了人口综合代码多恒星演化(MSE),旨在快速模拟恒星,二进制和多星系统的动力学演化。MSE包括许多以前的总体合成代码中不存在的新功能:(1)任意数量的恒星,只要初始系统是分层的,(2)为了有效计算引力动力学,在长期和直接N体积分之间进行动态切换,(3)处理偏心轨道中的质量传递,这通常发生在多星系统中,(4)简单处理潮汐、共包络和质量转移演化,其中吸积体是双星而不是单星,(5)考虑恒星系统内的行星,(6)包括来自经过的场星的引力扰动。MSE主要是用C++语言编写的,将公开提供,并且没有什么先决条件;提供了一个方便的Python接口。我们给出了MSE的详细描述,并说明了如何在实践中使用的代码。我们展示了它的操作中的一些例子。

英文摘要:

In recent years, observations have shown that multiple-star systems such as hierarchical triple and quadruple-star systems are common, especially among massive stars. They are potential sources of interesting astrophysical phenomena such as compact object mergers, leading to supernovae, and gravitational wave events. However, many uncertainties remain in their often complex evolution. Here, we present the population synthesis code Multiple Stellar Evolution (MSE), designed to rapidly model the stellar, binary, and dynamical evolution of multiple-star systems. MSE includes a number of new features not present in previous population synthesis codes: (1) an arbitrary number of stars, as long as the initial system is hierarchical, (2) dynamic switching between secular and direct N-body integration for efficient computation of the gravitational dynamics, (3) treatment of mass transfer in eccentric orbits, which occurs commonly in multiple-star systems, (4) a simple treatment of tidal, common-envelope, and mass transfer evolution in which the accretor is a binary instead of a single star, (5) taking into account planets within the stellar system, and (6) including gravitational perturbations from passing field stars. MSE, written primarily in the C++ language, will be made publicly available and has few prerequisites; a convenient Python interface is provided. We give a detailed description of MSE and illustrate how to use the code in practice. We demonstrate its operation in a number of examples.

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