A cellular automaton model of pulsar glitches is described , based on the superfluid vortex unpinning paradigm .
Recent analyses of pulsar glitch data suggest that glitches result from scale-invariant avalanches ( ) , which are consistent with a self-organized critical system ( SOCS ) .
A cellular automaton provides a computationally efficient means of modelling the collective behaviour of up to 10 ^ { 16 } vortices in the pulsar interior , whilst ensuring that the dominant aspects of the microphysics are not lost .
The automaton generates avalanche distributions that are qualitatively consistent with a SOCS and with glitch data .
The probability density functions of glitch sizes and durations are power laws , and the probability density function of waiting times between successive glitches is Poissonian , consistent with statistically independent events .
The output of the model depends on the physical and computational paramters used .
The fitted power law exponents for the glitch sizes ( a ) and durations ( b ) decreases as the strength of the vortex pinning increases .
Similarly the exponents increase as the fraction of vortices that are pinned decreases .
For the physical and computational parameters considered , one finds -4.3 \leq a \leq - 2.0 and -5.5 \leq b \leq - 2.2 , and mean glitching rates in the range 0.0023 \leq \lambda \leq 0.13 in units of inverse time .