Rubik’s cube transformation networks
Abstract
Weighted networks can be constructed from the transformation of the Rubik’s Cube with the edge weight as the distance between same colored cubes. Six networks were constructed for each step needed to return the cube to its fixed state. It has been observed that the state of one network affect the other six networks. It has also been shown that the network measures such as the average clustering coefficient, betweenness centrality and average nearest neighbor degree increase as the Rubik’s Cube is being rotated back to its fixed state.