Characterisation of the Degree of Musical Non-Markovianity

Abstract

As an aid for musical analysis, in computational musicology mathematical andinformatics tools have been developed to characterise quantitatively some aspectsof musical compositions. A musical composition can be attributed by ear a certainamount of memory. These results are associated with repetitions and similarities ofthe patterns in musical scores. To higher variations, a lower amount of memory isperceived. However, the musical memory of a score has never been quantitativelydefined. Here we aim to give such a measure following an approach similar tothat used in physics to quantify the memory (non-Markovianity) of open quantumsystems. We apply this measure to some existing musical compositions, showingthat the results obtained via this quantifier agree with what one expects by ear.The musical non-Markovianity quantifier can thus be used as a new tool that canaid quantitative musical analysis. It can also lead to future quantum computingcontrollers to manipulate structures in the framework of generative music.

Keywords

memory, non-markovianity, open quantum systems, pattern repetitions, computational musicology

How to Cite

Mannone, M. & Compagno, G., (2022) “Characterisation of the Degree of Musical Non-Markovianity”, Journal of Creative Music Systems 6(1). doi: https://doi.org/10.5920/jcms.975

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Authors

Maria Mannone (Ca' Foscari University of Venice)
Giuseppe Compagno (University of Palermo)

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Creative Commons Attribution 4.0

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This article has been peer reviewed.

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