Rapid algorithm for identifying backbones in the two-dimensional percolation model
Wei-Guo Yin, Ruibao Tao
Abstract
We present a rapid algorithm for identifying the current-carrying backbone in the percolation model. It applies to general two-dimensional graphs with open boundary conditions. Complemented by the modified Hoshen-Kopelman cluster labeling algorithm, our algorithm identifies dangling parts using their local properties. For planar graphs, it finds the backbone almost four times as fast as Tarjan's depth-first-search algorithm, and uses the memory of the same size as the modified Hoshen-Kopelman algorithm. Comparison with other algorithms for backbone identification is addressed.
Create a lesson
Related papers
Coupling spherical p-spin systems
Riccardo Cipolloni, Leticia F. Cugliandolo
Bias-Induced Crossover in Absolute Capacity of Dense Associative Memory
Yuto Sakurai, Takeaki Shimokawa, Kazunori Iwata et al.
Latent kinetic Ising models of neural spike trains
Davide Ghio, David Saad
Nonlocal Magic across the Many-Body Localization Crossover
Shan-Zhong Li, Zhi Li
Statistical levels and spatial modes of Fock-space heterogeneity in many-body localization crossovers
Yu-Jing Liu, Chen Cheng
Disorder-Tailored Delocalization
Yeongjun Kim, Supriyo Ghosh, Sergej Flach