This work demonstrates how equilibrium measures within the framework of Schr¨odinger random walks on networks can be leveraged to compute key network parameters such as the Mean First Passage Time (MFPT) and Kemeny's constant by expressing these parameters in terms of generalized inverses of the associated M-matrix.
Á. Carmona, A. Encinas, M. J. Jiménez et al.· The Electronic Journal of Li...· 0 citations
We show sharpness of the phase transition for a nearest-neighbour percolation model on $\mathbb Z^d$, where vertices carry independent types and the percolation probability of edges depends on the type of the adjacent vertices. Our proof uses the OSSS inequality and adapts to our setup the method developed in Duminil-C...
In this paper, we prove that the fluctuations of the graph distance and the effective resistance on the trace of a random walk in four and five dimensions converge in distribution to a stable law. In previous work, the first and second authors proved that the corresponding fluctuations converge to a Gaussian distributi...
A. Adhikari, Izumi Okada, D. Shiraishi· 0 citations
The stochastic block model is a widely studied model of community structure in networks. Here we study the component structure and percolation properties of networks generated from this model and its variants, using exact methods based on probability generating functions. In particular, we derive expressions for the si...
Random walks with long-range jumps can drive superdiffusive transport, replacing ordinary diffusion with an effective long-range kinetic operator. Such superdiffusive kinetics is also central to critical phenomena, notably the self-avoiding walk with long-range jump statistics, or L\'evy-SAW. This work investigates how...