论文标题
部分可观测时空混沌系统的无模型预测
PNO: A Promising Deep-UV Nonlinear Optical Material with Extremely High Second Harmonic Generation Effect
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。
In this work, the polar tetrahedron [PN$_2$O$_2$] was revealed as a new deep-ultraviolet (deep-UV) nonlinear optically active unit. Accordingly, a thermodynamically stable compound (PNO) consisting of the polar [PN$_2$O$_2$] units was predicted and suggested as a promising candidate of deep-UV nonlinear optical (NLO) material. Compared with other deep-UV materials known to date, PNO possesses the strongest second harmonic generation (SHG) coefficient (about 6 times that of KH$_2$PO$_4$ (KDP)). Moreover, its three-dimensional connectivity endows it with good mechanical and thermal properties. Therefore, PNO should be a new option for non-$π$-conjugated deep-UV NLO materials.
