Turing patterns and complexity: challenges and possibilities for sonification

Abstract

Taking a reaction-diffusion-generated Turing pattern—whether in one, two, or three dimensions—and allowing for the interaction of multiple patterns within the same domain, three methods of sonification are discussed; these are arranged as a continuum of increasing fidelity to the underlying process rather than as distinct categories. The first quantizes the pattern for additive synthesis; the second extracts global descriptors—density, gradient, anisotropy, entropy—and maps them onto perceptual parameters using non-linear techniques and fuzzy logic; the third treats the pattern as a movement law for a sound object, a concept linked to the notion of the "hyper-gesture." A neuro-fuzzy system that learns from environmental sound descriptors positions the mapping process between the second and third models, linking the operation to the specific context The theoretical foundations are examined, ranging from the relationship with algorithmic complexity and Varèse’s framework of "organized sound" to the affinity—based on ecocentric values—with Walter Branchi’s ecological sensibility.