Multidimensional sound spatialization by means of chaotic dynamical systems

We present an instrument that explores an algorithmic sound spatialization system developed with the SuperCollider programming language. We consider the implementation of spatial multidimensional panning through the simultaneous use of polygonal shaped horizontal and vertical loudspeaker array. This framework uses chaotic dynamical systems to generate discrete data series from the orbit of any specific system, which in this case is the logistic equation. The orbits will create the path of the general panning structure form vectors of R, containing entries from data series of different orbits from a specific dynamical system. Such vectors, called system vectors and create ordered paths between those points or system vectors. Finally, interpolating that result with a fixed sample value, we obtain specific and independent multidimensional panning trajectories for each speaker array and for any number of sound sources.