Chess players' fame versus their merit.

We investigate a pool of international chess title holders born between 1901 and 1943. Using Elo ratings, we compute for every player his expected score in a game with a randomly selected player from the pool. We use this figure as the player's merit. We measure players' fame as the number of Google hits. The correlation between fame and merit is 0.38. At the same time, the correlation between the logarithm of fame and merit is 0.61. This suggests that fame grows exponentially with merit.

Stochastic modeling of a serial killer.

We analyze the time pattern of the activity of a serial killer, who during 12 years had murdered 53 people. The plot of the cumulative number of murders as a function of time is of "Devil's staircase" type. The distribution of the intervals between murders (step length) follows a power law with the exponent of 1.4. We propose a model according to which the serial killer commits murders when neuronal excitation in his brain exceeds certain threshold. We model this neural activity as a branching process, which in turn is approximated by a random walk. As the distribution of the random walk return times is a power law with the exponent 1.5, the distribution of the inter-murder intervals is thus explained. We illustrate analytical results by numerical simulation. Time pattern activity data from two other serial killers further substantiate our analysis.