Techniques for Quantum-Computing-Aided Algorithmic Composition: Experiments in Rhythm, Timbre, Harmony, and Space
Christopher Dobrian, Omar Costa Hamido
TL;DR
The paper addresses how quantum computing concepts can enrich algorithmic music composition by mapping decision-making to quantum-circuit operations across rhythm, timbre, harmony, and spatialization. It introduces and demonstrates methods such as rhythm generation via measurements on a fixed-event grid, noise-based timbres derived from simulated quantum tracking, probabilistic harmony through state-vector rotations, and spatial perturbations using measurement error in panning. These contributions include concrete algorithms and a Max-based implementation using the hamidoQAC toolkit, accompanied by audio examples that illustrate coherent probabilistic textures and crossfades. By linking quantum measurement ideas with stochastic musical textures, the work offers a novel paradigm for shaping musical structure and texture with controllable probabilistic behavior, with potential impact on real-time generative systems and new sonic aesthetics, e.g., through the relation $Rx = \arccos(-2P+1)$ governing probability rotations.
Abstract
Quantum computing can be employed in computer-aided music composition to control various attributes of the music at different structural levels. This article describes the application of quantum simulation to model compositional decision making, the simulation of quantum particle tracking to produce noise-based timbres, the use of basis state vector rotation to cause changing probabilistic behaviors in granular harmonic textures, and the exploitation of quantum measurement error to cause noisy perturbations of spatial soundpaths. We describe the concepts fundamental to these techniques, we provide algorithms and software enacting them, and we provide examples demonstrating their implementation in computer-generated music.