论文标题

电源时期的气泡尺寸分布模型

A bubble size distribution model for the Epoch of Reionization

论文作者

Doussot, Aristide, Semelin, Benoit

论文摘要

气泡尺寸分布是一个摘要统计数据,可以从观察到的21 cm信号中计算出从电离时代的21 cm信号进行计算。由于它仅取决于电离场,并且不限于高斯信息,因此它是一个有趣的探测器,是与完整21-CM信号的功率谱相互补的。为气泡尺寸分布设计一个灵活且可靠的理论模型为将​​其用于天体物理参数推断铺平了道路。所提出的模型是从偏移集理论以及气泡体积与气泡中折叠质量之间的功能关系构建的。与以前的模型不同,它适合任何功能关系或分布。使用参数化关系使我们能够通过对从高分辨率,完全耦合的辐射流体动力学模拟(Hirrah-21)获得的气泡尺寸分布进行最小化,以测试模型的预测能力。我们的模型能够更好地适应$ x _ {\ text {h} _ {\ text {ii}}} \ sim 1 \%$和$ 3 \%$的电离分数的数值气泡大小分布。此外,将气泡体积与对应于最佳拟合参数的崩溃质量关系(不可观察的)与数值模拟数据进行了比较。获得了良好的匹配,从我们的模型中确定了从观察到的气泡尺寸分布来推断这种关系的可能性。最后,我们提出了一种简单的算法,该算法从经验上实现了渗透过程。我们表明,它将气泡大小分配模型的可用性扩展到$ x _ {\ text {h} _ {\ text {ii}}}} \ sim 30 \%$。

The bubble size distribution is a summary statistics that can be computed from the observed 21-cm signal from the Epoch of Reionization. As it depends only on the ionization field and is not limited to gaussian information, it is an interesting probe, complementary to the power spectrum of the full 21-cm signal. Devising a flexible and reliable theoretical model for the bubble size distribution paves the way for using it for astrophysical parameters inference. The proposed model is built from the excursion set theory and a functional relation between the bubble volume and the collapsed mass in the bubble. Unlike previous models it accommodates any functional relation or distributions. Using parameterized relations allows us to test the predictive power of the model by performing a minimization best-fit to the bubble size distribution obtained from a high resolution, fully coupled radiative hydrodynamics simulations, HIRRAH-21. Our model is able to provide a better fit to the numerical bubble size distribution at ionization fraction of $x_{\text{H}_{\text{II}}} \sim 1\%$ and $3\%$ than other existing models. Moreover, the bubble volume to collapsed mass relation corresponding to the best-fit parameters, which is not an observable, is compared to numerical simulation data. A good match is obtained, confirming the possibility to infer this relation from an observed bubble size distribution using our model. Finally we present a simple algorithm that empirically implements the process of percolation. We show that it extends the usability of our bubble size distribution model up to $x_{\text{H}_{\text{II}}} \sim 30\%$.

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