Artificial spin ice is a self-organising system of interacting nanomagnets which exhibits interesting and complex behaviour. In this paper we put the art in artificial spin ice, presenting a novel mapping from a dynamical state trajectory to MIDI music for an ensemble of instruments. An evolutionary algorithm is used to search for new artificial spin ice geometries of higher musical quality, making use of Zipfian and entropic measures. Geometries of high fitness were discovered, and music resulting from the best geometry found is presented alongside this paper. Aside from the primary outcome of producing novel music, this unique viewpoint of artificial spin ice could allow for a more intuitive observation of its dynamical properties, interpreting their state trajectories through the medium of music.

Arrangements of nanomagnets known as artificial spin ices show great potential for use in unconventional computation. The majority of exploratory work done in this area considers just a small handful of well studied geometries (nanomagnetic arrangements), and uses them as if they were a black box. Here we detail a novel representation of artificial spin ice geometries, which lends itself to the tuning and evolutionary search of geometries. Using our representation we present geometries tuned to exhibit a desired computational or meta-material property. This is the first example of such a search performed on artificial spin ice.