论文标题
部分可观测时空混沌系统的无模型预测
The partonic origin of multiplicity scaling in heavy and light flavor jets
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。
It has recently been shown that a KNO-like scaling is fulfilled inside the jets, which indicates that the KNO scaling is violated by complex vacuum-QCD processes outside the jet development, such as single and double parton scattering or softer multiple-parton interactions. In the current work we investigated the scaling properties of heavy-flavor jets using Monte-Carlo simulations. We found that while jets from leading-order flavor-creation processes exhibit a flavor-dependent pattern, heavy-flavor jets from production in the parton shower follow the inclusive-jet pattern. This suggests that the KNO-like scaling is driven by initial hard parton production and not by processes in the later stages of the reaction.
