论文标题
分析结果,用于在随机常规图上随机步行的第一学期时间的分布
Analytical results for the distribution of first-passage times of random walks on random regular graphs
论文作者
论文摘要
我们为在随机的常规图上进行了随机步行(RWS)分布的分析结果,该图是由$ n $ nodes $ c \ ge 3 $组成的。从时间的随机初始节点开始,$ t = 0 $,每次步骤$ t \ ge 1 $ a RW跳入其先前节点的随机邻居。在某些时候,RW可能会跳入一个尚未访问的节点,而在其他时间步骤中,它可能会重新访问以前访问过的节点。我们从随机初始节点$ i $ $ $ j $ j $ j $ j $ j $ j \ ne i $计算出第一票的时间的分布$ p(t _ {\ rm fp} = t)$。我们区分FP轨迹的FP轨迹的骨干遵循最短路径(SPATH)从初始节点$ i $到目标节点$ j $和FP轨迹的FP轨迹,其主链不会遵循最短路径($ \ lnot {\ lnot {\ rm rm spath} $)。更确切地说,从初始节点$ i $到目标节点$ j $的SPATH轨迹定义为轨迹,其中由沿轨迹的节点和边缘组成的子网组成是树网络。此外,此子网络上$ i $和$ j $之间的最短路径与整个网络中的路径相同。 SPATH方案可能主要是当最短节点$ i $和目标节点$ j $之间的最短路径的长度$ \ ell_ {ij} $很小。发现分析结果与从计算机模拟获得的结果非常吻合。
We present analytical results for the distribution of first-passage (FP) times of random walks (RWs) on random regular graphs that consist of $N$ nodes of degree $c \ge 3$. Starting from a random initial node at time $t=0$, at each time step $t \ge 1$ an RW hops into a random neighbor of its previous node. In some of the time steps the RW may hop into a yet-unvisited node while in other time steps it may revisit a node that has already been visited before. We calculate the distribution $P( T_{\rm FP} = t )$ of first-passage times from a random initial node $i$ to a random target node $j$, where $j \ne i$. We distinguish between FP trajectories whose backbone follows the shortest path (SPATH) from the initial node $i$ to the target node $j$ and FP trajectories whose backbone does not follow the shortest path ($\lnot {\rm SPATH}$). More precisely, the SPATH trajectories from the initial node $i$ to the target node $j$ are defined as trajectories in which the subnetwork that consists of the nodes and edges along the trajectory is a tree network. Moreover, the shortest path between $i$ and $j$ on this subnetwork is the same as in the whole network. The SPATH scenario is probable mainly when the length $\ell_{ij}$ of the shortest path between the initial node $i$ and the target node $j$ is small. The analytical results are found to be in very good agreement with the results obtained from computer simulations.