  In this paper, we explore the consequences of a distinction between `live'
and `dead' network nodes; `live' nodes are able to acquire new links whereas
`dead' nodes are static. We develop an analytically soluble growing network
model incorporating this distinction and show that it can provide a
quantitative description of the empirical network composed of citations and
references (in- and out-links) between papers (nodes) in the SPIRES database of
scientific papers in high energy physics. We also demonstrate that the death
mechanism alone can result in power law degree distributions for the resulting
network.
