Using Swarm Intelligence To Accelerate Pulsar Timing Analysis
  We provide brief notes on a particle swarm-optimisation approach to
constraining the properties of a stochastic gravitational-wave background in
the first International Pulsar Timing Array data-challenge. The technique
employs many computational-agents which explore parameter space, remembering
their most optimal positions and also sharing this information with all other
agents. It is this sharing of information which accelerates the convergence of
all agents to the global best-fit location in a very short number of
iterations. Error estimates can also be provided by fitting a multivariate
Gaussian to the recorded fitness of all visited points.
