Machine learning techniques in magnetic levitation problems
We present a method for calculating the stability region of a perfect diamagnet levitated in a magnetic field created by a circular current loop making use of the machine learning techniques. As an application we compute stability regions, points of stable equilibrium and stable oscillatory motions in two chip-based superconducting trap architectures used to levitate superconducting particles. Our procedure is an alternative to a full numerical scheme based on finite element methods which are expensive to implement for optimizing experimental parameters.
This work was funded by Universidad Rey Juan Carlos, Spain , Programa Propio: Analysis, modelling and simulations of singular structures in continuum models, M2604.
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