English

$N$-cluster correlations in four- and five-dimensional percolation

Statistical Mechanics 2020-08-03 v1

Abstract

We study NN-cluster correlation functions in four- and five-dimensional (4D, 5D) bond percolation by extensive Monte Carlo simulation. We reformulate the transfer Monte Carlo algorithm for percolation [Phys. Rev. E {\bf 72}, 016126 (2005)] using the disjoint-set data structure, and simulate a cylindrical geometry Ld1×L^{d-1}\times \infty, with the linear size up to L=512L=512 for 4D and 128128 for 5D. We determine with a high precision all possible NN-cluster exponents, for N ⁣= ⁣2N \! =\!2 and 33, and the universal amplitude for a logarithmic correlation function. From the symmetric correlator with N ⁣= ⁣2N \! = \!2, we obtain the correlation-length critical exponent as 1/ν ⁣= ⁣1.4610(12)1/\nu \! =\! 1.4610(12) for 4D and 1/ν ⁣= ⁣1.737(2)1/\nu \! =\! 1.737 (2) for 5D, significantly improving over the existing results. Estimates for the other exponents and the universal logarithmic amplitude have not been reported before to our knowledge. Our work demonstrates the validity of logarithmic conformal field theory and adds to the growing knowledge for high-dimensional percolation.

Keywords

Cite

@article{arxiv.2006.10981,
  title  = {$N$-cluster correlations in four- and five-dimensional percolation},
  author = {Xiaojun Tan and Youjin Deng and Jesper Lykke Jacobsen},
  journal= {arXiv preprint arXiv:2006.10981},
  year   = {2020}
}

Comments

Percolation, Logarithmic conformal field theory, Monte Carlo simulation

R2 v1 2026-06-23T16:27:25.104Z