percolationbased
Percolationbased describes methods, models, or frameworks that rely on percolation theory to study connectivity in systems where components may be randomly present, active, or failed. In percolation theory, objects such as sites on a lattice or edges of a graph are occupied with a probability p, and researchers study the resulting clusters of connected components. A central feature is the emergence of a macroscopic, or spanning, cluster at a critical probability p_c, signaling a phase transition in the system’s connectivity. The term is used across disciplines to denote approaches inspired by or built on these ideas rather than a single algorithm.
Key concepts in percolationbased work include site and bond percolation, random graphs, and the notion of a
Applications of percolationbased methods span several fields. In materials science and porous media, they model flow
Methods commonly used include Monte Carlo simulations, analytical results for regular lattices, and renormalization or finite-size
See also: percolation theory, site percolation, bond percolation, random graphs, phase transition, bootstrap percolation, network science.