  A new particle swarm optimization (PSO) technique for electromagnetic
applications is proposed. The method is based on quantum mechanics rather than
the Newtonian rules assumed in all previous versions of PSO, which we refer to
as classical PSO. A general procedure is suggested to derive many different
versions of the quantum PSO algorithm (QPSO). The QPSO is applied first to
linear array antenna synthesis, which is one of the standard problems used by
antenna engineers. The performance of the QPSO is compared against an improved
version of the classical PSO. The new algorithm outperforms the classical one
most of the time in convergence speed and achieves better levels for the cost
function. As another application, the algorithm is used to find a set of
infinitesimal dipoles that produces the same near and far fields of a circular
dielectric resonator antenna (DRA). In addition, the QPSO method is employed to
find an equivalent circuit model for the DRA that can be used to predict some
interesting parameters like the Q-factor. The QPSO contains only one control
parameter that can be tuned easily by trial and error or by suggested simple
linear variation. Based on our understanding of the physical background of the
method, various explanations of the theoretical aspects of the algorithm are
presented.
