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.TH "BA" "1" "September 2017" "www.complex-networks.net" "www.complex-networks.net"
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.SH "NAME"
\fBba\fR \- Grow a Barabasi\-Albert scale\-free random graph
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.SH "SYNOPSIS"
\fBba\fR \fIN\fR \fIm\fR \fIn0\fR
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.SH "DESCRIPTION"
\fBba\fR grows an undirected random scale\-free graph with \fIN\fR nodes using the linear preferential attachment model proposed by Barabasi and Albert\. The initial network is a ring of \fIn0\fR nodes, and each new node creates \fIm\fR new edges\. The resulting graph will have a scale\-free degree distribution, whose exponent converges to \fBgamma=3\.0\fR for large \fIN\fR\.
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.SH "PARAMETERS"
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.TP
\fIN\fR
Number of nodes of the final graph\.
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.TP
\fIm\fR
Number of edges created by each new node\.
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.TP
\fIn0\fR
Number of nodes in the initial (seed) graph\.
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.SH "OUTPUT"
\fBba\fR prints on STDOUT the edge list of the final graph\.
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.SH "EXAMPLES"
The following command:
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.IP "" 4
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.nf

    $ ba 10000 3 5 > ba_10000_3_5\.txt
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.fi
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.IP "" 0
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.P
creates a Barabasi\-Albert scale\-free graph with \fIN=10000\fR nodes, where each new node creates \fIm=3\fR new edges and the initial seed network is a ring of \fIn0=5\fR nodes\. The edge list of the graph is saved in the file \fBba_10000_3_5\.txt\fR (thanks to the redirection operator \fB>\fR)\.
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.SH "SEE ALSO"
bb_fitness(1), dms(1), bbv(1)
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.SH "REFERENCES"
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.IP "\(bu" 4
A\.\-L\. Barabasi, R\. Albert, "Emergence of scaling in random networks", Science 286, 509\-512 (1999)\.
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.IP "\(bu" 4
V\. Latora, V\. Nicosia, G\. Russo, "Complex Networks: Principles, Methods and Applications", Chapter 6, Cambridge University Press (2017)
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.IP "\(bu" 4
V\. Latora, V\. Nicosia, G\. Russo, "Complex Networks: Principles, Methods and Applications", Appendix 13, Cambridge University Press (2017)
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.IP "" 0
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.SH "AUTHORS"
(c) Vincenzo \'KatolaZ\' Nicosia 2009\-2017 \fB<v\.nicosia@qmul\.ac\.uk>\fR\.