论文标题
有条件神经条件流的Lyman-α附近的完全概率的类星体连续预测
Fully probabilistic quasar continua predictions near Lyman-α with conditional neural spline flows
论文作者
论文摘要
在类星体光谱中中性氢的红色阻尼翅的测量提供了早期宇宙中电离时代的探测。这样的量化需要对莱曼$ $α$（ly $α$）的内在连续图进行精确且无偏的估计，这是一项艰巨的任务，鉴于高度可变的ly $α$排放概况。在这里，我们介绍了一种完全概率的方法来进行内在的连续预测。我们将问题作为条件密度估计任务构图，并明确对合理的蓝色侧连续图（$ 1190 \ \ unicode {xc5} \leqλ_{\leqλ_ {\ text {rest}}} <1290 \ \ \ \ \ unicode {xc5} $）条件（xc5} $）条件（$ 12990） \ unicode {xc5} \leqλ_ {\ text {rest}} <2900 \ \ unicode {xc5} $）使用归一化流量。我们的方法达到了最先进的精度和准确性，可以在不到十分之一的一秒钟内对一千个合理的连续性进行采样，并且可以通过Monte Carlo采样对蓝色侧连续性提供置信区间。我们在两个$ z> 7 $ quasars中测量阻尼机翼效应，并估算每种氢的体积平均中性少量，找到$ \ bar {x} _ \ text {hi} = 0.304 \ pm 0.042 \ pm 0.042 $ for ulas j1120+0641（$ z = 7.09 $）和$ \ bar} Ulas J1342+0928（$ Z = 7.54 $）的0.133 $。
Measurement of the red damping wing of neutral hydrogen in quasar spectra provides a probe of the epoch of reionization in the early Universe. Such quantification requires precise and unbiased estimates of the intrinsic continua near Lyman-$α$ (Ly$α$), a challenging task given the highly variable Ly$α$ emission profiles of quasars. Here, we introduce a fully probabilistic approach to intrinsic continua prediction. We frame the problem as a conditional density estimation task and explicitly model the distribution over plausible blue-side continua ($1190\ \unicode{xC5} \leq λ_{\text{rest}} < 1290\ \unicode{xC5}$) conditional on the red-side spectrum ($1290\ \unicode{xC5} \leq λ_{\text{rest}} < 2900\ \unicode{xC5}$) using normalizing flows. Our approach achieves state-of-the-art precision and accuracy, allows for sampling one thousand plausible continua in less than a tenth of a second, and can natively provide confidence intervals on the blue-side continua via Monte Carlo sampling. We measure the damping wing effect in two $z>7$ quasars and estimate the volume-averaged neutral fraction of hydrogen from each, finding $\bar{x}_\text{HI}=0.304 \pm 0.042$ for ULAS J1120+0641 ($z=7.09$) and $\bar{x}_\text{HI}=0.384 \pm 0.133$ for ULAS J1342+0928 ($z=7.54$).
