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+ba(1) -- 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>`.
+