  We perform experimental verification of the preferential attachment model
that is commonly accepted as a generating mechanism of the scale-free complex
networks. To this end we chose citation network of Physics papers and traced
citation history of 40,195 papers published in one year. Contrary to common
belief, we found that citation dynamics of the individual papers follows the
\emph{superlinear} preferential attachment, with the exponent $\alpha=
1.25-1.3$. Moreover, we showed that the citation process cannot be described as
a memoryless Markov chain since there is substantial correlation between the
present and recent citation rates of a paper. Basing on our findings we
constructed a stochastic growth model of the citation network, performed
numerical simulations based on this model and achieved an excellent agreement
with the measured citation distributions.
