Field optimisation using an analytic model feedback technique

When optimizing the field distribution in a magnet, the usual method is to make trial and error changes to the magnet geometry and/or current distributions, until an optimum solution is found. Using this method the number of iterations required to find a solution depends not only on the complexity of the problem but also on user experience. The initial changes are therefore random or semirandom, and convergence may take many iterations or not be possible. A method is proposed which substitutes for the random changes a simple analytical model, so that feedback is positive and convergence is fast. The method has been applied to quadrupole and dipole geometries, and has been used to minimize unwanted harmonics and to introduce controlled quantities of harmonics.<>