Quantum synth

Hamido, Omar Costa; Cirillo, Giovanni Amedeo; Giusto, Edoardo

doi:10.1145/3411109.3411135

Cited by 10 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such a technology promises to solve extremely complex problems beyond the capabilities of conventional supercomputers. Applications of quantum computing to the music domain is gaining momentum, as testified by the emergence of the new area of research and development on Quantum Computer Music [10], a growing number of publications on such a matter [11]- [14] and dedicated international gatherings 1 . However, thus far, there has been scarce interaction between the field of NMPs and that of quantum computing.…”

Section: Introductionmentioning

confidence: 99%

Theoretical Quantum Modeling of Improvisation in Networked Music Performances to Regulate the Behaviour of Artificial Musicians

Mannone,

Turchet

2023

2023 4th International Symposium on the Internet of Sounds

View full text Add to dashboard Cite

During collective musical performances over the network that are characterized by improvisation, a performer may face the problem of what connected musician to follow most in order to direct his/her own improvisation. This choice may be taken on the basis of different factors related to the state of the network and of the kind of the received musical signal. In this paper we investigate the possibility to adopt the mathematical formalism of Quantum Mechanics to describe some interaction phenomena occurring during improvised networked music performances. We propose a decision-making system, having a quantum circuit in its core, where the approximated decision by performers is modeled with state superposition and probability amplitudes used in quantum computing. The model considers the levels of signal clarity (i.e., audio quality related to packet losses), latency, and musical novelty (e.g., melodic or harmonic variation with respect to a previous musical sequence) as the factors that affect the decision of a performer to select another connected performer to follow. This model may be exploited to regulate the behaviour of an artificial intelligent agent playing the role of a virtual musician in the networked ensemble (via generative music techniques). This allows to create mixed human-artificial ensembles and even fully artificial ensembles in networked contexts.

show abstract