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arXiv 1409.0229astro-ph.SR
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用新的星族合成程序BONNFIRES对大质量恒星转动混合的数值试验

Numerical Tests of Rotational Mixing in Massive Stars with the new Population Synthesis Code BONNFIRES

Herbert H. B. Lau, Robert G. Izzard, Fabian R. N. Schneider

摘要:

我们使用我们的新的人口合成代码BONNFIRES旋转恒星模型预测的表面丰度如何依赖于旋转混合的数值处理,如空间分辨率,时间分辨率和平均分子量梯度的计算。我们发现,即使用相同的数值处方计算扩散方程中的旋转混合系数,不同的时间步长导致的偏差的系数,因此表面丰度。我们发现,地表丰度变化10 - 100%之间的模型序列与较长的时间步长为0.001Myr的短时间步长的模型序列。具有较强表面氮富集的模型序列也具有较长的主序列寿命,因为更多的氢混合到燃烧的核心。主序列寿命的偏差可以高达20%。从数学上讲,没有数值方案可以给出完美的解决方案,除非使用无穷小的时间步长。然而,我们发现,表面丰度最终收敛在10%以内的建模序列与足够小的时间步长低于0.1Myr。旋转混合的效率取决于所实施的数值方案,并且关键地取决于平均分子量梯度的计算。平均分子量梯度的平滑函数导致更强的旋转混合。如果用于计算平均分子量梯度的离散化方案或计算配方被改变,则可能需要重新校准混合参数以拟合观察结果。如果我们要正确理解恒星旋转的基本物理学,在数值模拟旋转混合过程时,我们必须尽量减少引入恒星演化模型的不确定性。

英文摘要:

We use our new population synthesis code BONNFIRES to test how surface abundances predicted by rotating stellar models depend on the numerical treatment of rotational mixing, such as spatial resolution, temporal resolution and computation of mean molecular weight gradients. We find that even with identical numerical prescriptions for calculating the rotational mixing coefficients in the diffusion equation, different timesteps lead to a deviation of the coefficients and hence surface abundances. We find the surface abundances vary by 10-100% between the model sequences with short timestep of 0.001Myr to model sequences with longer timesteps. Model sequences with stronger surface nitrogen enrichment also have longer main-sequence lifetimes because more hydrogen is mixed to the burning cores. The deviations in main-sequence lifetimes can be as large as 20%. Mathematically speaking, no numerical scheme can give a perfect solution unless infinitesimally small timesteps are used. However, we find that the surface abundances eventually converge within 10% between modelling sequences with sufficiently small timesteps below 0.1Myr. The efficiency of rotational mixing depends on the implemented numerical scheme and critically on the computation of the mean molecular weight gradient. A smoothing function for the mean molecular weight gradient results in stronger rotational mixing. If the discretization scheme or the computational recipe for calculating the mean molecular weight gradient is altered, re-calibration of mixing parameters may be required to fit observations. If we are to properly understand the fundamental physics of rotation in stars, it is crucial that we minimize the uncertainty introduced into stellar evolution models when numerically approximating rotational mixing processes.

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