论文标题
关于超新星绝对大小的稳定性的鲁棒性：非参数重建\＆贝叶斯方法
On the Robustness of the Constancy of the Supernova Absolute Magnitude: Non-parametric Reconstruction \& Bayesian approaches
论文作者
论文摘要
在这项工作中，我们使用非参数重建技术（NRT）测试了超新星绝对幅度$ m_b $的坚固性。我们将光度距离参数$ d_l（z）$分离从巴里昂声学振荡（BAO）数据集中，并从观察到的距离模量$μ（z）$中取消扩展部分。因此，绝对幅度和哈勃常数$ h_0 $之间的堕落性被$ m_b $与拖动epoch $ r_d $的声音范围之间的变性所取代。强加$ r_d $ value时，会产生$ m_b（z）= m_b +Δm_b（z）$ value nrt。我们使用模型独立的人工神经网络（ANN）技术和高斯过程（GP）回归进行各自的重建。对于ANN，我们推断$ M_B = -19.22 \ PM0.20 $，对于GP，我们得到$ M_B = -19.25 \ PM0.39 $，是从延迟时间测量中使用声音范围时的全部分配的平均值。这些估计提供了一个$ 1 \，σ$的可能性，即在较高的红移处有一个滋扰参数$Δm_b（z）$的可能性。我们还使用马尔可夫链蒙特卡洛（MCMC）技术测试了不同的已知滋扰模型，该模型表现出对恒定模型的强烈偏爱，但不可能单一单一的偏爱模型。
In this work, we test the robustness of the constancy of the Supernova absolute magnitude $M_B$ using Non-parametric Reconstruction Techniques (NRT). We isolate the luminosity distance parameter $d_L(z)$ from the Baryon Acoustic Oscillations (BAO) data set and cancel the expansion part from the observed distance modulus $μ(z)$. Consequently, the degeneracy between the absolute magnitude and the Hubble constant $H_0$, is replaced by a degeneracy between $M_B$ and the sound horizon at drag epoch $r_d$. When imposing the $r_d$ value, this yields the $M_B(z) = M_B + δM_B(z)$ value from NRT. We perform the respective reconstructions using the model independent Artificial Neural Network (ANN) technique and Gaussian processes (GP) regression. For the ANN we infer $M_B = -19.22\pm0.20$, and for the GP we get $M_B = -19.25\pm0.39$ as a mean for the full distribution when using the sound horizon from late time measurements. These estimations provide a $1\,σ$ possibility of a nuisance parameter presence $δM_B(z)$ at higher redshifts. We also tested different known nuisance models with the Markov Chain Monte Carlo (MCMC) technique which showed a strong preference for the constant model, but it was not possible not single out a best fit nuisance model.
