  Statistical distributions with heavy tails are ubiquitous in natural and
social phenomena. Since the entries in heavy tail have disproportional
significance, the knowledge of its exact shape is very important. Citations of
scientific papers form one of the best-known heavy tail distributions. Even in
this case there is a considerable debate whether citation distribution follows
the log-normal or power-law fit. The goal of our study is to solve this debate
by measuring citation distribution for a very large and homogeneous data. We
measured citation distribution for 418,438 Physics papers published in
1980-1989 and cited by 2008. While the log-normal fit deviates too strong from
the data, the discrete power-law function with the exponent $\gamma=3.15$ does
better and fits 99.955% of the data. However, the extreme tail of the
distribution deviates upward even from the power-law fit and exhibits a
dramatic "runaway" behavior. The onset of the runaway regime is revealed
macroscopically as the paper garners 1000-1500 citations, however the
microscopic measurements of autocorrelation in citation rates are able to
predict this behavior in advance.
