Subcritical Connectivity and Some Exact Tail Exponents in High Dimensional Percolation
@inproceedings{Chatterjee2021SubcriticalCA, title={Subcritical Connectivity and Some Exact Tail Exponents in High Dimensional Percolation}, author={Shirshendu Chatterjee and Jack Hanson and Philippe Sosoe}, year={2021} }
In high dimensional percolation at parameter p < pc, the one-arm probability πp(n) is known to decay exponentially on scale (pc − p)−1/2. We show the same statement for the ratio πp(n)/πpc(n), establishing a form of a hypothesis of scaling theory. As part of our study, we provide sharp estimates (with matching upper and lower bounds) for several quantities of interest at the critical probability pc. These include the tail behavior of volumes of, and chemical distances within, spanning clusters…
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References
SHOWING 1-10 OF 42 REFERENCES
Tree graph inequalities and critical behavior in percolation models
- Mathematics
- 1984
Various inequalities are derived and used for the study of the critical behavior in independent percolation models. In particular, we consider the critical exponent γ associated with the expected…
Strict Inequality for the Chemical Distance Exponent in Two‐Dimensional Critical Percolation
- MathematicsCommunications on Pure and Applied Mathematics
- 2020
We provide the first nontrivial upper bound for the chemical distance exponent in two‐dimensional critical percolation. Specifically, we prove that the expected length of the shortest horizontal…
High-dimensional near-critical percolation and the torus plateau
- Mathematics
- 2021
We consider percolation on Z and on the d-dimensional discrete torus, in dimensions d ≥ 11 for the nearest-neighbour model and in dimensions d > 6 for spread-out models. For Z, we employ a wide range…
The Alexander-Orbach conjecture holds in high dimensions
- Mathematics
- 2009
AbstractWe examine the incipient infinite cluster (IIC) of critical percolation in regimes where mean-field behavior has been established, namely when the dimension d is large enough or when d>6 and…
Cycle structure of percolation on high-dimensional tori
- Mathematics
- 2011
Abstract In the past years, many properties of the largest connected components of critical percolation on the high-dimensional torus, such as their sizes and diameter, have been established. The…
Restricted Percolation Critical Exponents in High Dimensions
- MathematicsCommunications on Pure and Applied Mathematics
- 2020
Despite great progress in the study of critical percolation on ℤd for d large, properties of critical clusters in high‐dimensional fractional spaces and boxes remain poorly understood, unlike the…
Mean-field critical behaviour for correlation length for percolation in high dimensions
- Mathematics
- 1990
SummaryExtending the method of [27], we prove that the corrlation length ξ of independent bond percolation models exhibits mean-field type critical behaviour (i.e. ξ(p∼(pc−p)−1/2 asp↗pc) in two…
Cycle structure of percolation on high-dimensional tori
- 2014
In the past years, many properties of the largest connected components of critical percolation on the high-dimensional torus, such as their sizes and diameter, have been established. The order of…
Random Graph Asymptotics on High-Dimensional Tori
- Mathematics
- 2005
We investigate the scaling of the largest critical percolation cluster on a large d-dimensional torus, for nearest-neighbor percolation in sufficiently high dimensions, or when d > 6 for sufficiently…