The European Physical Journal Special Topics· 2026Q2
Exploring quantum tonality
- 1citations
- Q2SCImago
- 2026year
Short summary
A quantum harmonic oscillator model of C-major tonality generates novel musical compositions by sonifying the time-evolution of wave functions, bypassing traditional quantum measurement simulations.
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Key points
- C-major tonality's pitch-class profiles are modeled as a quantum ground state wave function.
- The time-dependent Schrödinger equation dictates the temporal evolution of these quantum states.
- Two sonification strategies are employed: stroboscopic stratification and continuous sound processes.
- The approach utilizes the full wave function evolution, not simulated quantum measurements.
AI-generated from the title and abstract; the full text is not read.
Abstract
Abstract This article reports on a series of mathe-musical experiments based on the dynamic behavior of a musical quantum model of C-major tonality. The model reinterprets empirical pitch-class profiles of tonal attraction in C-major as the probability wave function of a one-dimensional stationary ground state within a perturbed quantum harmonic oscillator. By solving the associated time-dependent Schrödinger equation, we assign specific temporal evolutions to any given initial state. We explore two distinct sonification strategies: First, the time-evolutions of various initial states—in particular deflections of the ground state and higher excited states—are used to drive a stroboscopic stratification of musical hierarchies and to set them into Minimal Music-inspired travelling note patterns. Secondly, we implement rich continuous sound processes that rely on the uninterrupted flow of the wave function. Crucially, these approaches bypass the simulation of quantum measurements; instead, they leverage the full theoretical information of the wave function’s evolution.
The authors' abstract, as published at the source. The European Physical Journal Special Topics, 2026 · DOI ↗
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Field: Computer Vision and Pattern Recognition
Computer Vision and Pattern RecognitionComputer Science