论文标题
部分可观测时空混沌系统的无模型预测
Novel Increase of Superconducting Critical Temperature of an Iron-Superconductor due to Ion Implantation
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。
Energetic ion irradiation usually decreases superconducting critical temperature(Tc), with the few exceptions involving increases up to a few K only. However, our recent 2.5X10^15 Ar/cm2 irradiations by 1.5 MeV Ar6+ enhanced Tc of the single crystal Fe-superconductor Ba(Fe0.943Co0.057)2As2 by 8.2 K from its initial onset Tc of ~16.9 K as measured from the real part of the magnetic susceptibility, matching measurements from the imaginary part, electrical resistivity and magnetization. Ozaki et al. (2016) explained their Tc increase of 0.5 K in FeSe0.5Te0.5 films with the thickness (t) < the irradiating proton range (R), as due to a nanoscale compressive strain developed from radiation damage of the lattice. Here, Ar irradiation with t > R results in an Ar implanted layer in our crystal. Implanted inert gas atoms often agglomerate into high-pressure bubbles to exert a large compressive strain on the lattice. We suggest that this additional compressive strain could be the reason for such a large (~49%) Tc increase.
