Convergence properties of optimal transport-based temporal networks

2021

Conference Paper

pio

We study network properties of networks evolving in time based on optimal transport principles. These evolve from a structure covering uniformly a continuous space towards an optimal design in terms of optimal transport theory. At convergence, the networks should optimize the way resources are transported through it. As the network structure shapes in time towards optimality, its topological properties also change with it. The question is how do these change as we reach optimality. We study the behavior of various network properties on a number of network sequences evolving towards optimal design and find that the transport cost function converges earlier than network properties and that these monotonically decrease. This suggests a mechanism for designing optimal networks by compressing dense structures. We find a similar behavior in networks extracted from real images of the networks designed by the body shape of a slime mold evolving in time.

@conference{convOT,
  title = {Convergence properties of optimal transport-based temporal networks},
  author = {Baptista Theuerkauf, Diego and De Bacco, Caterina},
  booktitle = {Complex Networks & Their Applications X },
  volume = {1},
  series = {Studies in Computational Intelligence },
  month = sep,
  year = {2021},
  doi = {10.1007/978-3-030-93409-5_48},
  month_numeric = {9}
}