English

Energy-Weighted Site Percolation in Two Dimensions

Statistical Mechanics 2026-05-19 v1 Disordered Systems and Neural Networks

Abstract

We study a generalization of two-dimensional site percolation by assigning an energy cost ε\varepsilon to bonds between nearest-neighbor occupied sites. This leads to a competition between entropy-driven cluster growth and energetic suppression (or enhancement) of connectivity. Varying ε\varepsilon continuously interpolates between dense ferromagnetic-like clusters, ordinary classical percolation, and a dilute regime of minimally connected isolated clusters. Using Monte Carlo simulations and real-space renormalization-group (RG) methods, we show that bond energy shifts the percolation threshold smoothly. We define an energy-weighted correlation length that remains finite at the classical site occupation threshold (pc(ε=0)p_c(\varepsilon=0)) and shrinks with increasing ε\varepsilon, capturing the energetic suppression of large-scale connectivity. The cluster size distribution exhibits an energy-dependent cutoff that drives the transition from percolation-like clusters to isolated clusters. A real-space RG with Kadanoff block recursions reveals a systematic evolution of the correlation-length exponent ν\nu from ν=1/2\nu=1/2 (dense clusters) to ν=4/3\nu=4/3 (classical percolation), approaching ν=1\nu=1 (minimally connected isolated clusters), in agreement with Coulomb-gas predictions for loop models where bond energy renormalizes loop fugacity. For large values of ε\varepsilon (isotropic case), the suppression of nearest-neighbor bonds results in the emergence of antiferromagnetic sub-lattice ordering at high densities. Additionally, anisotropic bond energies lead to directionally selective cluster growth. Finally, we also discuss a lattice gas RG approach and scenarios where bond energy is renormalized across different scales.

Keywords

Cite

@article{arxiv.2605.18312,
  title  = {Energy-Weighted Site Percolation in Two Dimensions},
  author = {Sayan Sircar and Kabir Ramola},
  journal= {arXiv preprint arXiv:2605.18312},
  year   = {2026}
}

Comments

24 pages, 18 figures

R2 v1 2026-07-22T07:18:59.634Z