论文标题
来自21 cm功率谱的电离参数的隐性可能性推断
Implicit Likelihood Inference of Reionization Parameters from the 21 cm Power Spectrum
论文作者
论文摘要
无线电干涉阵列实验（例如，电源阵列的氢时代（HERA）和平方立式阵列阵列（SKA）），很可能在不久的将来实现21 cm亮度温度功率谱的首次测量。标准MCMC分析使用明确的可能性近似来推断21 cm功率谱的电离参数。在本文中，我们提出了一种新的贝叶斯推论，其中使用密度估计无可能的推理（DELFI）通过正向模拟隐含了可能性定义了可能性。现实的效果（包括热噪声和前景回避）也适用于HERA和SKA的模拟观察结果。我们证明，此方法为电离参数恢复了准确的后验分布，并在可信参数区域的位置和大小方面优于标准MCMC分析。随着分钟级的处理时间，一旦训练了网络，该技术是对未来21 cm功率谱观察数据的科学解释的一种有希望的方法。我们的代码21cmdelfi-ps在此链接上可公开可用。
The first measurements of the 21 cm brightness temperature power spectrum from the epoch of reionization will very likely be achieved in the near future by radio interferometric array experiments such as the Hydrogen Epoch of Reionization Array (HERA) and the Square Kilometre Array (SKA). Standard MCMC analyses use an explicit likelihood approximation to infer the reionization parameters from the 21 cm power spectrum. In this paper, we present a new Bayesian inference of the reionization parameters where the likelihood is implicitly defined through forward simulations using density estimation likelihood-free inference (DELFI). Realistic effects including thermal noise and foreground avoidance are also applied to the mock observations from the HERA and SKA. We demonstrate that this method recovers accurate posterior distributions for the reionization parameters, and outperforms the standard MCMC analysis in terms of the location and size of credible parameter regions. With the minutes-level processing time once the network is trained, this technique is a promising approach for the scientific interpretation of future 21 cm power spectrum observation data. Our code 21cmDELFI-PS is publicly available at this link.
