dc.creator |
Ergun, G |
|
dc.creator |
Rodgers, GJ |
|
dc.date |
2006-10-27T14:35:57Z |
|
dc.date |
2006-10-27T14:35:57Z |
|
dc.date |
2001 |
|
dc.date.accessioned |
2022-05-25T13:06:46Z |
|
dc.date.available |
2022-05-25T13:06:46Z |
|
dc.identifier |
Physica A 303: 261-272, Sep 2001 |
|
dc.identifier |
http://www.elsevier.com/wps/find/journaldescription.cws_home/505702/description#description |
|
dc.identifier |
http://bura.brunel.ac.uk/handle/2438/310 |
|
dc.identifier.uri |
http://localhost:8080/xmlui/handle/CUHPOERS/163649 |
|
dc.description |
Three models of growing random networks with fitness dependent growth rates are analysed using the rate equations for the distribution of their connectivities. In the first model (A), a network is built by connecting incoming nodes to nodes of connectivity $k$ and random additive fitness $\eta$, with rate $(k-1)+ \eta $. For $\eta >0$ we find the connectivity distribution is power law with exponent $\gamma=<\eta>+2$. In the second model (B), the network is built by connecting nodes to nodes of connectivity $k$, random additive fitness $\eta$ and random multiplicative fitness $\zeta$ with rate $\zeta(k-1)+\eta$. This model also has a power law connectivity distribution, but with an exponent which depends on the multiplicative fitness at each node. In the third model (C), a directed graph is considered and is built by the addition of nodes and the creation of links. A node with fitness $(\alpha, \beta)$, $i$ incoming links and $j$ outgoing links gains a new incoming link with rate $\alpha(i+1)$, and a new outgoing link with rate $\beta(j+1)$. The distributions of the number of incoming and outgoing links both scale as power laws, with inverse logarithmic corrections. |
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dc.format |
316433 bytes |
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dc.format |
application/pdf |
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dc.language |
en |
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dc.publisher |
Elsevier Science |
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dc.subject |
Statistical mechanics |
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dc.subject |
Disordered systems and neural networks |
|
dc.title |
Growing random networks with fitness |
|
dc.type |
Research Paper |
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dc.coverage |
6 |
|