https://github.com/mmdanziger/color-avoiding-percolation

Code for using color avoiding percolation for secret message passing on complex networks.
https://github.com/mmdanziger/color-avoiding-percolation

network-science percolation-theory physics

Last synced: about 1 month ago
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Code for using color avoiding percolation for secret message passing on complex networks.

• Host: GitHub
• URL: https://github.com/mmdanziger/color-avoiding-percolation
• Owner: mmdanziger
• Created: 2014-07-14T12:44:28.000Z (over 10 years ago)
• Default Branch: master
• Last Pushed: 2020-01-16T18:30:46.000Z (almost 5 years ago)
• Last Synced: 2024-03-17T12:44:38.426Z (10 months ago)
• Topics: network-science, percolation-theory, physics
• Language: C++
• Homepage:
• Size: 10.5 MB
• Stars: 0
• Watchers: 3
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
Color Avoiding Percolation

=================

This repository contains the code used for the color-avoiding percolation papers:

Hidden Connectivity in Networks with Vulnerable Classes of Nodes  

Sebastian M. Krause, Michael M. Danziger, and Vinko Zlatić  

Phys. Rev. X 6, 041022 – Published 27 October 2016  

https://doi.org/10.1103/PhysRevX.6.041022  

Color-avoiding percolation

Sebastian M. Krause, Michael M. Danziger, and Vinko Zlatić  

Phys. Rev. E 96, 022313 – Published 14 August 2017  

https://doi.org/10.1103/PhysRevE.96.022313  

Subdirectories

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`colornet` - generate a random network and use a disjoint sets based algorithm to calculate the color-avoiding connectivity  

`manycolornet` - generate a random network or read a network from a file and use BFS to calculate the color-avoiding connectivity  

`colornet_scripts` - python scripts used to load simulation results, generate plots, and calculate theoretical predictions  

`real_data` - directory for CAIDE AS data (the data is not publicly available, please contact us if you are interested in using it)  

`data_scripts` - scripts for loading the real data and plotting maps based on it  

If you use this code, please cite the original paper(s).