We identify the asymptotic distribution of the chemical distance in high-dimensional critical Bernoulli percolation. Namely, we show that the distance between the origin and a distant vertex conditioned to lie in the cluster of the origin converges in distribution when rescaled by a multiple the square of the Euclidean distance. The limiting distribution has an explicit density and coincides with the distribution of the time for a Brownian motion in Rᵈ conditioned to hit a given unit vector to reach its target. Our result follows from a general moment computation for quantities that have an additive structure across the pivotal edges on a long-range connection in percolation. In addition to the number of pivotal edges in a long connection, this also includes the effective resistance. The existence of the incipient infinite cluster limit, in a form recently established, plays a key role in the derivation of our results.
Building similarity graph...
Analyzing shared references across papers
Loading...
Shirshendu Chatterjee
The Graduate Center, CUNY
Pranav Chinmay
The Graduate Center, CUNY
Jack Hanson
The Graduate Center, CUNY
Building similarity graph...
Analyzing shared references across papers
Loading...
Chatterjee et al. (Sun,) studied this question.
synapsesocial.com/papers/68ec1be02b8fa9b2b78acfef — DOI: https://doi.org/10.48550/arxiv.2509.06236