arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1911.04444astro-ph.HEastro-ph.SR
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II型超新星II的光谱模拟。定量光谱分析的机器学习方法

Spectral modeling of type II supernovae II. A machine learning approach to quantitative spectroscopic analysis

C. Vogl, W. E. Kerzendorf, S. A. Sim, U. M. Noebauer, S. Lietzau, W. Hillebrandt

摘要:

现在有数百个公开的超新星光谱时间序列。这些数据的辐射转移模型给出了这些爆炸的物理性质,如组成,密度结构,或内在的光度的见解-这是非常宝贵的理解超新星的祖先,爆炸机制,或约束超新星距离。然而,一个详细的参数研究的可用数据已经遥不可及,由于高维的问题,再加上仍然显着的计算费用。我们通过使用机器学习仿真器来解决这个问题,机器学习仿真器是用于高维插值的算法。这些使用预先计算的训练数据集来模拟复杂代码的输出,但运行时间更短。我们提出了这样一个模拟器的应用程序与TARDIS辐射转移代码生成的合成II型超新星光谱。结果表明,相对较小的780个光谱的训练集,我们可以生成插值不确定性小于百分之一的仿真光谱。我们证明了这种方法的实用性,通过自动光谱拟合的两个著名的IIP型超新星,作为一个示例性的应用程序,我们确定超新星的距离,从光谱拟合使用定制的扩展光球方法。我们将我们的结果与以前的研究进行了比较,发现很好的一致性。这表明TARDIS光谱的仿真可能被用于对许多瞬态类进行自动和详细的分析,从而使大型数据存储库的分析触手可及。

英文摘要:

There are now hundreds of publicly available supernova spectral time series. Radiative transfer modeling of this data gives insights into the physical properties of these explosions such as the composition, the density structure, or the intrinsic luminosity---this is invaluable for understanding the supernova progenitors, the explosion mechanism, or for constraining the supernova distance. However, a detailed parameter study of the available data has been out of reach due to the high dimensionality of the problem coupled with the still significant computational expense. We tackle this issue through the use of machine-learning emulators, which are algorithms for high-dimensional interpolation. These use a pre-calculated training dataset to mimic the output of a complex code but with run times orders of magnitude shorter. We present the application of such an emulator to synthetic type II supernova spectra generated with the TARDIS radiative transfer code. The results show that with a relatively small training set of 780 spectra we can generate emulated spectra with interpolation uncertainties of less than one percent. We demonstrate the utility of this method by automatic spectral fitting of two well-known type IIP supernovae; as an exemplary application, we determine the supernova distances from the spectral fits using the tailored-expanding-photosphere method. We compare our results to previous studies and find good agreement. This suggests that emulation of TARDIS spectra can likely be used to perform automatic and detailed analysis of many transient classes putting the analysis of large data repositories within reach.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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