论文标题
High-Z Sudoku：用于识别强大（子）MM红移的诊断工具
High-z Sudoku: A diagnostic tool for identifying robust (sub)mm redshifts
论文作者
论文摘要
储层计算是预测湍流的有力工具，其简单的架构具有处理大型系统的计算效率。然而，其实现通常需要完整的状态向量测量和系统非线性知识。我们使用非线性投影函数将系统测量扩展到高维空间，然后将其输入到储层中以获得预测。我们展示了这种储层计算网络在时空混沌系统上的应用，该系统模拟了湍流的若干特征。我们表明，使用径向基函数作为非线性投影器，即使只有部分观测并且不知道控制方程，也能稳健地捕捉复杂的系统非线性。最后，我们表明，当测量稀疏、不完整且带有噪声，甚至控制方程变得不准确时，我们的网络仍然可以产生相当准确的预测，从而为实际湍流系统的无模型预测铺平了道路。
We present methods to (i) graphically identify robust redshifts using emission lines in the (sub)mm regime, (ii) evaluate the capabilities of different (sub)mm practices for measuring spectroscopic redshifts, and (iii) optimise future (sub)mm observations towards increasing the fraction of robust redshifts. Using this publicly-available code (https://github.com/tjlcbakx/redshift-search-graphs), we discuss scenarios where robust redshifts can be identified using both single- and multiple-line detections, as well as scenarios where the redshift remains ambiguous, even after the detection of multiple lines. Using the redshift distribution of (sub)mm samples, we quantify the efficiencies of various practices for measuring spectroscopic redshifts, including interferometers, as well as existing and future instruments specifically designed for redshift searches. Finally, we provide a method to optimise the observation strategy for future (sub)mm spectroscopic redshift searches with the Atacama Large Millimetre/submillimetre Array, where 2 mm proves indispensable for robust redshifts in the z = 2 - 4 region.
