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Abstract

This paper presents PhotoSing, a system that learns to generate polyphonic tunes by extracting sequencing rules from given examples. We developed a method to encode given pieces of music in terms of unique musical events, referred to as UMEs, and stochastic rules for sequencing them. Those rules are subsequently converted into representations to be processed by a photonic computer to generate new compositions. This research builds upon a previous system, QuSing, which generated monophonic tunes with superconducting quantum computing. The paper discusses the pitfalls of the previous system, the research and the solutions developed to improve them. It details the system with demonstrative musical examples and analyses.

Publication Date

2025-08-10

Publication Title

International Journal of Parallel, Emergent and Distributed Systems

Volume

40

Issue

5

ISSN

1744-5760

Acceptance Date

2025-02-21

Deposit Date

2025-03-18

Funding

This research was funded by the University of Plymouth, UK. We thank Quandela for their support and for enabling access to their photonic computing resources. There are no competing interests to declare.

Keywords

Quantum Computer Music, Artificial Intelligence, Music Technology, photonic computing, generative systems, music and AI, Quantum computer music

First Page

481

Last Page

500

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