论文标题
使用人工神经网络从边缘数据中提取21 cm全局信号
Using Artificial Neural Networks to extract the 21-cm Global Signal from the EDGES data
论文作者
论文摘要
中性氢的红移21厘米信号是在形成第一颗恒星时(宇宙黎明)到整个宇宙从完全中性变为完全离子化(恢复离子)的时期。这种中性氢的最引人注目的特征是,可以在整个频率范围内观察到它是天空平均连续签名,也可以使用干涉仪测量其波动。但是,21厘米信号非常微弱,并且由一个更明亮的银河系和半乳酸前景主导,使其成为观察性的挑战。我们已经使用了不同的物理模型来模拟21 cm全局信号的各种实现,包括与边缘21-cm信号的幅度相匹配的多余无线电背景。首先,我们使用人工神经网络(ANN)从这些模拟数据集中提取天体物理参数。然后,通过添加一个有力动机的前景模型生成模拟观察结果,并使用ANN从此类数据中提取天体物理参数。我们从模拟观察中预测的$ r^2 $得分在0.65-0.89范围内。我们已经使用此ANN来预测将边缘数据作为输入的信号参数。我们发现,重建的信号紧密模仿了报告的检测的幅度。恢复的参数可用于在高红移处推断气体的物理状态。
The redshifted 21-cm signal of neutral Hydrogen is a promising probe into the period of evolution of our Universe when the first stars were formed (Cosmic Dawn), to the period where the entire Universe changed its state from being completely neutral to completely ionized (Reionization). The most striking feature of this line of neutral Hydrogen is that it can be observed across an entire frequency range as a sky-averaged continuous signature, or its fluctuations can be measured using an interferometer. However, the 21-cm signal is very faint and is dominated by a much brighter Galactic and extra-galactic foregrounds, making it an observational challenge. We have used different physical models to simulate various realizations of the 21-cm Global signals, including an excess radio background to match the amplitude of the EDGES 21-cm signal. First, we have used an artificial neural network (ANN) to extract the astrophysical parameters from these simulated datasets. Then, mock observations were generated by adding a physically motivated foreground model and an ANN was used to extract the astrophysical parameters from such data. The $R^2$ score of our predictions from the mock-observations is in the range of 0.65-0.89. We have used this ANN to predict the signal parameters giving the EDGES data as the input. We find that the reconstructed signal closely mimics the amplitude of the reported detection. The recovered parameters can be used to infer the physical state of the gas at high redshifts.