Universal properties of growing networks
β Scribed by P.L Krapivsky; B Derrida
- Publisher
- Elsevier Science
- Year
- 2004
- Tongue
- English
- Weight
- 250 KB
- Volume
- 340
- Category
- Article
- ISSN
- 0378-4371
No coin nor oath required. For personal study only.
β¦ Synopsis
Networks growing according to the rule that every new node has a probability p k of being attached to k preexisting nodes, have a universal phase diagram and exhibit power-law decays of the distribution of cluster sizes in the non-percolating phase. The percolation transition is continuous but of inΓΏnite order and the size of the giant component is inΓΏnitely di erentiable at the transition (though of course non-analytic). At the transition the average cluster size (of the ΓΏnite components) is discontinuous.
π SIMILAR VOLUMES
Hava Siegelmann and Eduardo Sontag have shown that recurrent neural networks using the linear-bounded sigmoid are computationally universal. We show that this remains true if the linear-bounded sigmoid is replaced by any function in a fairly large class.