论文标题
通过网络混乱的D1-D5黑洞动力学
Chaotic D1-D5 Black Hole Dynamics through Networks
论文作者
论文摘要
这项工作研究了通过网络方法控制两个电荷D1-D5黑洞的不同微骨之间的过渡，其中系统的微晶格被定义为网络节点，而它们之间的过渡则定义为边缘。发现该网络的拉普拉斯矩阵的特征性（用微晶系统的汉密尔顿人都鉴定出来）与随机矩阵的一般高斯正交集合的最接近邻居间距分布完全相同。根据BGS，即Bohigas，Giannoni和Schmit的猜想，这形成了D1-D5微分动力学混乱特征的证据。通过观察到，拉普拉斯矩阵的第一/最小非零特征值的倒数与系统的对数成正比，从而进一步加强了这一证据。由Sekino和Susskind撰写，这意味着D1-D5黑洞微晶体的动力学不仅是混乱的，而且是自然界中最快的扰动者。
This work studies dynamics controlling the transition between different microstates of two charge D1-D5 black holes by network methods, in which microstates of the system are defined as network nodes, while transitions between them are defined as edges. It is found that the eigenspectrum of this network's Laplacian matrix, which is identified with Hamiltonians of the microstate system, has completely the same Nearest-Neighbor Spacing Distribution as that of general Gaussian Orthogonal Ensemble of Random Matrices. According to the BGS, i.e. Bohigas, Giannoni and Schmit conjecture, this forms evidence for chaotic features of the D1-D5 microstate dynamics. This evidence is further strengthened by observations that inverse of the first/minimal nonzero eigenvalue of the Laplacian matrix is proportional to logarithms of the microstate number of the system. By Sekino and Susskind, this means that dynamics of the D1-D5 black hole microstates are not only chaotic, but also the fastest scrambler in nature.
