论文标题
部分可观测时空混沌系统的无模型预测
Impact of Lattice Strangeness Asymmetry Data in the CTEQ-TEA Global Analysis
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 study the impact of lattice data on the determination of the strangeness asymmetry distribution $s_-(x) \equiv s(x) - {\bar s}(x)$ in the general CTEQ-TEA global analysis of parton distribution functions (PDFs) of the proton. Firstly, we find that allowing a nonvanishing $s_-(x)$, at the initial $Q_0=1.3$~GeV scale, in a global PDF analysis leads to a CT18As fit with similar quality to CT18A. Secondly, including the lattice data in the CT18As\_Lat fit greatly reduces the $s_-$-PDF error band size in the large-$x$ region. To further reduce its error would require more precise lattice data, extended to smaller $x$ values. We take ATLAS 7 TeV $W$ and $Z$ production data, SIDIS di-muon production data, $F_3$ structure function data, E866 NuSea data, and E906 SeaQuest data as examples to illustrate the implication of CT18As and CT18As\_Lat fits. The parametrization dependence for PDF ratio $(s+\bar{s})/(\bar{u}+\bar{d})(x)$ is analyzed with CT18As2 and CT18As2\_Lat fits as results.
