Stars radiate energy stored in their magnetic fields in the form of stellar flares, and the dynamics of a system that causes flare events can be well-described by the sequence of times between flare events, known as waiting times. From the stellar intensity data collected by the Kepler satellite, the waiting time sequences of different stars is created by finding sudden elevations in the light curve above a certain threshold. The mutual information, which measures the information within a data set, is then calculated for the original data as well as for surrogate data sets created by random permutations of waiting times within regions with constant flaring rates. Comparing the mutual information of the actual waiting times against the mutual information of the surrogate waiting times, we find that there is a significant elevation in the mutual information of the original data set, and thus our information theory analysis indicates a dependence between successive flares. This increased mutual information is due to the clustering of flares, evidenced by comparing the cumulative distribution function (CDF of successive flares in the original data set with the CDF of flares in the surrogate sequences.
Available at: http://works.bepress.com/jay-johnson/90/