Pseudofractal scale-free web
Abstract
We find that scale-free random networks are excellently modeled by simple deterministic graphs. Our graph has a discrete degree distribution (degree is the number of connections of a vertex), which is characterized by a power law with exponent γ=1+ln 3/ln 2. Properties of this compact structure are surprisingly close to those of growing random scale-free networks with γ in the most interesting region, between 2 and 3. We succeed to find exactly and numerically with high precision all main characteristics of the graph. In particular, we obtain the exact shortest-path-length distribution. For a large network (ln N>>1) the distribution tends to a Gaussian of width ~(ln N) centered at l¯~ln N. We show that the eigenvalue spectrum of the adjacency matrix of the graph has a power-law tail with exponent 2+γ.
- Publication:
-
Physical Review E
- Pub Date:
- June 2002
- DOI:
- arXiv:
- arXiv:cond-mat/0112143
- Bibcode:
- 2002PhRvE..65f6122D
- Keywords:
-
- 87.18.Sn;
- 05.10.-a;
- 05.40.-a;
- 05.50.+q;
- Neural networks;
- Computational methods in statistical physics and nonlinear dynamics;
- Fluctuation phenomena random processes noise and Brownian motion;
- Lattice theory and statistics;
- Condensed Matter - Statistical Mechanics
- E-Print:
- 5 pages, 3 figures