Whittling I

By David Dunn


“Whittling I (2018) is the latest in a series of works—collectively titled Heuristic Automata—that utilize computer code to transcribe complex electronically generated sonic phenomena into traditional musical notation. This sonic material can be characterized as behaviors of a dynamical system consisting of a network of eight nonlinear chaotic oscillators. The dynamical behaviors of the analog network are simply passed through an equal-tempered mesh, parsing them with some preset constraints that conform to instrumental ranges. The system merely senses changes in frequency, velocity of events, and basic amplitude changes. Since the chaotic oscillator network is autonomous, the resultant behaviors are impossible to control other than the setting of initial conditions and some external perturbation from extrinsic sources or environmental conditions.

The use of the term “deterministic chaos” and the subsequent use of the word “chaos” is not a colloquial usage. This is a mathematical term that refers to a precise category of natural phenomena that is not simply random, stochastic or probabilistic. Since these “chaotic oscillators” are not conventional periodic oscillators but rather a network of circuits based upon a specific Ordinary Differential Equation, the result produces complex non-periodic (or aperiodic) acoustic waveforms. These sounds can be more appropriately described as evidence of a complex behavior in that a change in any parameter of one chaotic circuit in the network can cause a change in every other parameter of the other members of the network.

The implications for how (or why?) something that is perceptually analogous to traditional musical structures can be generated from these systems is also one of my foreground interests. While experimenting with the transcription process, I not only became impressed with the huge diversity of the resultant musical data but how reminiscent it could be of a divergent range of atonal musical “styles” associated with a number of familiar and celebrated 20th century composers. Most of these composers were either adherents of preexistent generative procedures (12-tone method) or invented their own generative processes, whether formal or intuitive. Since the Heuristic Automata compositions were all generated through the same organizational method and only differ by changes in the initial conditions of circuit settings, the similarity to the aural gestalts of other atonal composers has caused me to question whether such evocations are more than merely superficial. In other words: are the various aural characteristics and generative methods that we consistently associate with various atonal composers actually subsets of a larger organizational logic that might be formally identified?

A variety of analytical methods derived from statistics or related formal measures have been the most consistent tools used to understand deeper structural aspects of complex atonal music. The results have been both enlightening and limited. I am much more interested in asking the above question but do not know how to answer it. This is also why I refer to this project as heuristic in nature and not analytical, nor theoretical per se. Intuitively it seems that a good place to start is with a different set of tools, more specifically, those proffered by Chaos Theory as already outlined. Rather than applying these methods analytically, my approach has been to use other deterministic hyper-chaotic systems to generate new musical data that can be compared and contrasted to familiar musical artifacts. One of my guiding goals in editing and organizing the material has been to act as quickly as possible in order to optimize—or get myself out of the way of—an aural reality reminiscent of the models that I have discussed but also something that resides between rigorously notated music composition and the tradition of free improvisation.” —David Dunn