Characterization of the degree of Musical non-Markovianity

As an aid for musical analysis, in computational musicology mathematical and informatics tools have been developed to quantitatively characterize some aspects of musical compositions. To a musical composition can be attributed by ear a certain amount of memory. This results associated to repetitions and similarities of the patterns in musical scores. To higher variations, a lower amount of memory is perceived.However musical memory of a score has never been quantitatively de-fined. Here we aim to give such a measure following an approach similar to that used in Physics to quantify the memory (non-Markovianity) of open quantum systems. We have applied this measure to some existing musical compositions, showing that 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 can aid quantitative musical analysis. It can also lead to future quantum computing controllers to manipulate structures in the framework of generative music.