论文标题
建立二元种群综合的现实爆炸格局
Towards a Realistic Explosion Landscape for Binary Population Synthesis
论文作者
论文摘要
涉及大量恒星的人群合成研究中的关键成分是确定它们是爆炸还是爆炸。尽管大型恒星的最终命运对崩溃开始时的核心结构很敏感,但现有的二元种群合成研究并未达到核心崩溃。取而代之的是,他们采用简单的处方来推断他们的最终命运,而不知道Presupernova核心结构。我们通过独立于恒星的其余部分来处理碳氧(CO)核心来探索该问题的潜在解决方案。使用隐式流体力学代码开普勒,我们从各种初始条件范围内计算了3496个副核心模型的广泛网格,每种条件都从碳点火到核心爆发。最终的核心结构,因此爆炸性在非单调方面变化,并敏感地取决于副核心的质量和初始组成。尽管裸核并不是嵌入大型恒星中的核心的完美替代品,但我们的模型与MESA以及完整的氢气和氦气恒星计算进行了很好的比较。我们的结果可用于从共同核心特性的种群综合估计值中推断出前诺娃的核心结构,从而根据现代中微子驱动的爆炸模拟的结果来确定最终结果。为IIB型超新星祖细胞提供了样本应用。我们所有的模型均可在https://doi.org/10.5281/zenodo.3785377上找到。
A crucial ingredient in population synthesis studies involving massive stars is the determination of whether they explode or implode in the end. While the final fate of a massive star is sensitive to its core structure at the onset of collapse, the existing binary population synthesis studies do not reach core-collapse. Instead, they employ simple prescriptions to infer their final fates without knowing the presupernova core structure. We explore a potential solution to this problem by treating the carbon-oxygen (CO) core independently from the rest of the star. Using the implicit hydrodynamics code KEPLER, we have computed an extensive grid of 3496 CO-core models from a diverse range of initial conditions, each evolved from carbon ignition until core-collapse. The final core structure, and thus the explodability, varies non-monotonically and depends sensitively on both the mass and initial composition of the CO-core. Although bare CO-cores are not perfect substitutes for cores embedded in massive stars, our models compare well both with MESA and full hydrogenic and helium star calculations. Our results can be used to infer the presupernova core structures from population synthesis estimates of CO-core properties, thus to determine the final outcomes based on the results of modern neutrino-driven explosion simulations. A sample application is presented for a population of Type-IIb supernova progenitors. All of our models are available at https://doi.org/10.5281/zenodo.3785377.