论文标题
HII星系的可靠校准，使用宇宙天文序列和人工神经网络
A Reliable Calibration of HII Galaxies Hubble Diagram with Cosmic Chronometers and Artificial Neural Network
论文作者
论文摘要
通过距离指示器校准的HII星系（HIIGX）的$ L-σ$关系是用于测量哈勃常数$ H_0 $的可靠标准蜡烛。最直接的校准技术将它们与同一星系的第一层梯子锚定。最近，已提出了另一种使用宇宙学模型独立的宇宙天元器（CC）作为校准器的有前途的方法。我们通过消除有关宇宙平坦度的假设并使用非参数人工神经网络进行数据重建过程来促进这一技术。我们观察到宇宙曲率密度参数与$ L-σ$关系的斜率之间的相关性，从而提高了校准的可靠性。使用校准的Hiigx Hubble图，我们获得了IA型超新星哈勃图，而无需传统的假设约为$ h_0 $。最后，我们得到$ h_0 = 65.9 _ { - 2.9}^{+3.0} \ Mathrm {km s^{ - 1} mpc^{ - 1}} $，与最新的planck18测量兼容。
The $L-σ$ relation of HII galaxies (HIIGx) calibrated by a distance indicator is a reliable standard candle for measuring the Hubble constant $H_0$. The most straightforward calibration technique anchors them with the first tier of distance ladders from the same galaxies. Recently another promising method that uses the cosmological model-independent Cosmic Chronometers (CC) as a calibrator has been proposed. We promote this technique by removing the assumptions about the cosmic flatness and using a non-parametric Artificial Neural Network for the data reconstruction process. We observe a correlation between the cosmic curvature density parameter and the slope of the $L-σ$ relation, thereby improving the reliability of the calibration. Using the calibrated HIIGx Hubble diagram, we obtain a Type Ia Supernovae Hubble diagram free of the conventional assumption about $H_0$. Finally we get a value of $H_0=65.9_{-2.9}^{+3.0} \mathrm{km s^{-1} Mpc^{-1}}$, which is compatible with latest Planck18 measurement.
