Name
Abstract | ||
|---|---|---|
Critical, or scale independent, systems are so ubiquitous, that gaining theoretical insights on their nature and properties has many direct repercussions in social and natural sciences. In this report, we start from the simplest possible growth model for critical systems and deduce constraints in their growth : the well-known preferential attachment principle, and, mainly, a new law of temporal scaling. We then support our scaling law with a number of calculations and simulations of more complex theoretical models : critical percolation, self-organized criticality and fractal growth. Perhaps more importantly, the scaling law is also observed in a number of empirical systems of quite different nature : prose samples, artistic and scientific productivity, citation networks, and the topology of the Internet. We believe that these observations pave the way towards a general and analytical framework for predicting the growth of complex systems. |
Year | Venue | Field |
|---|---|---|
2012 | CoRR | Complex system,Artificial intelligence,Criticality,Scaling,The Internet,Statistical physics,Fractal,Theoretical physics,Natural science,Percolation,Machine learning,Mathematics,Preferential attachment |
DocType | Volume | Citations |
Journal | abs/1211.1361 | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Laurent Hébert-Dufresne | 1 | 38 | 7.03 |
| Antoine Allard | 2 | 29 | 5.05 |
| Louis J. Dubé | 3 | 26 | 4.66 |