- ba(1)
- www.complex-networks.net
- ba(1)

## NAME

`ba`

- Grow a Barabasi-Albert scale-free random graph

## SYNOPSIS

`ba`

`N` `m` `n0`

## DESCRIPTION

`ba`

grows an undirected random scale-free graph with `N` nodes using
the linear preferential attachment model proposed by Barabasi and
Albert. The initial network is a ring of `n0` nodes, and each new node
creates `m` new edges. The resulting graph will have a scale-free
degree distribution, whose exponent converges to `gamma=3.0`

for large
`N`.

## PARAMETERS

`N` Number of nodes of the final graph.

`m` Number of edges created by each new node.

`n0` Number of nodes in the initial (seed) graph.

## OUTPUT

`ba`

prints on STDOUT the edge list of the final graph.

## EXAMPLES

The following command:

```
$ ba 10000 3 5 > ba_10000_3_5.txt
```

creates a Barabasi-Albert scale-free graph with `N=10000` nodes, where
each new node creates `m=3` new edges and the initial seed network is
a ring of `n0=5` nodes. The edge list of the graph is saved in the
file `ba_10000_3_5.txt`

(thanks to the redirection operator `>`

).

## SEE ALSO

bb_fitness(1), dms(1), bbv(1)

## REFERENCES

A.-L. Barabasi, R. Albert, "Emergence of scaling in random
networks", Science 286, 509-512 (1999).

V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
Methods and Applications", Chapter 6, Cambridge University Press
(2017)

V. Latora, V. Nicosia, G. Russo, "Complex Networks: Principles,
Methods and Applications", Appendix 13, Cambridge University Press
(2017)

## AUTHORS

(c) Vincenzo 'KatolaZ' Nicosia 2009-2017 `<v.nicosia@qmul.ac.uk>`

.