论文标题
部分可观测时空混沌系统的无模型预测
Analysis of Phonetic Soliton Propagation in Neutral Weyl Fermion-sea
论文作者
论文摘要
我们提出了机器学习（ML）和神经网络（NN）技术的应用，用于分析基于超声时间反转的非线性弹性波光谱法（TR-NEWS）。为了获得拓扑功能，我们采用了$（2+1）D $晶格模拟，并采用固定点（FP）操作。我们考虑7个类型循环，该循环位于$ 2D $的空间平面上，由$ e_1，e_2 $和13 b类型循环，该循环包含与$ e_1 \ wedge e_2 $平行的链接，以及 - $ e_1 \ $ e_1 \ wedge e_2 $。我们考虑在中性Weyl纺纱子的费米 - sea中传播玻色子声子，这由Clifford代数描述。通过Clifford Fourier变换将动量空间中的配置转换为真实位置空间。我们考虑没有磁滞效应的A型和具有磁滞效应的B型，以及通过ML或NN技术搜索7 A型FP动作的最佳权重和13 B型FP FP使用Monte-Carlo方法。
We propose application of Machine Learning (ML) and Neural Network (NN) technique for the analysis of ultrasonic Time Reversal based Nonlinear Elastic Wave Spectroscopy (TR-NEWS). In order to acquire topological features, we adopt the $(2+1)D$ lattice simulation with fixed point (FP) actions. We consider 7 A type loops which sit on $2D$ spacial plane spanned by $e_1, e_2$ and 13 B type loops which contain links parallel to $e_1\wedge e_2$ and to -$e_1\wedge e_2$. We consider propagation of bosonic phonons in Fermi-sea of neutral Weyl spinors which are described by Clifford algebra. Configurations in momentum space is transformed to real position space via Clifford Fourier Transform. We consider A-type without hysteresis effects and B-type with hysteresis effects, and via ML or NN technique search optimal weight of 7 A-type FP actions and 13 B-type FP actions using the Monte-Carlo method.
