Polynomial lower bound on the effective resistance for the one‐dimensional critical long‐range percolation

Abstract In this work, we study the critical long‐range percolation (LRP) on , where an edge connects and independently with probability 1 for and with probability for some fixed . Viewing this as a random electric network where each edge has a unit conductance, we show that with high probability the effective resistances from the origin 0 to and from the interval to (conditioned on no edge joining and ) both have a polynomial lower bound in . Our bound holds for all and thus rules out a potential phase transition (around ) which seemed to be a reasonable possibility.

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Publication Details

Journal
Communications on Pure and Applied Mathematics
Published
2025-01-27
DOI
https://doi.org/10.1002/cpa.22243
Primary Topic
Stochastic processes and statistical mechanics
Type
article
Field-Weighted Citation Impact
0.00

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article

Polynomial lower bound on the effective resistance for the one‐dimensional critical long‐range percolation

Jian Ding, Zherui Fan, Lu‐Jing Huang
Communications on Pure and Applied Mathematics
Stochastic processes and statistical mechanics
article

Polynomial lower bound on the effective resistance for the one‐dimensional critical long‐range percolation

Jian Ding, Zherui Fan, Lu‐Jing Huang
article en

Abstract

Abstract In this work, we study the critical long‐range percolation (LRP) on , where an edge connects and independently with probability 1 for and with probability for some fixed . Viewing this as a random electric network where each edge has a unit conductance, we show that with high probability the effective resistances from the origin 0 to and from the interval to (conditioned on no edge joining and ) both have a polynomial lower bound in . Our bound holds for all and thus rules out a potential phase transition (around ) which seemed to be a reasonable possibility.

Communications on Pure and Applied MathematicsVol. 78(7)
Fujian Normal University (CN), Peking University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 96%
Stochastic processes and statistical mechanics
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