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De Musica

Quantum Aspects of the Musical Mind

Maria Mannone, Valeria Seidita, Antonio Chella

Published Dec 10, 2024• 1 citation
Publisher

Abstract

The composer constantly makes choices: it is the composer, in fact, who chooses a melodic, rhythmic, harmonic path among the various, infinite possible paths between point A, the beginning, and point B, the end of a composition. The choice of one path over another, a local modification of a given path, can also be influenced by external factors. As it happens for the path of a charged particle in a magnetic field, the choice of the musical path can be influenced by personal style, culture, technical characteristics of the instruments, and combinations of instruments used. Even in quantum mechanics, there are “choices”: the state of a system appears as a superposition of possible eigenstates with different probability amplitudes. The act of measurement “forces” the system to choose a particular state: the observer influences the physics of the system. Like the famous example of Schrödinger’s cat, alive and dead at the same time until the box in which it is located is opened. From the choices of notes and musical paths to decision-making systems, we present some examples of the application of quantum mechanics to music. Among the applications of quantum computing, we mention a study on robots with associated musical descriptions. In particular, we consider the distributed intelligence of a swarm of robots and its possible musical description, from some existing works to our original application.

DOI
10.54103/2465-0137/21265

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The composer constantly makes choices: it is the composer, in fact, who chooses a melodic, rhythmic, harmonic path among the various, infinite possible paths between point A, the beginning, and point B, the end of a composition. The choice of one path over another, a local modification of a given path, can also be influenced by external factors. As it happens for the path of a charged particle in a magnetic field, the choice of the musical path can be influenced by personal style, culture, technical characteristics of the instruments, and combinations of instruments used. Even in quantum mechanics, there are “choices”: the state of a system appears as a superposition of possible eigenstates with different probability amplitudes. The act of measurement “forces” the system to choose a particular state: the observer influences the physics of the system. Like the famous example of Schrödinger’s cat, alive and dead at the same time until the box in which it is located is opened. From the choices of notes and musical paths to decision-making systems, we present some examples of the application of quantum mechanics to music. Among the applications of quantum computing, we mention a study on robots with associated musical descriptions. In particular, we consider the distributed intelligence of a swarm of robots and its possible musical description, from some existing works to our original application.
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.
Quantum computing and artificial intelligence, two prominent topics in science and technology, are rapidly advancing and extending their influence into numerous fields, including music. Quantum computer music, which merges the strengths of quantum computing and deep learning, heralds a new era in the integration of music creation with cutting-edge technology. The interactive quantum music composition “Spinnings—Q1 Synth Trio”, created by Brazilian composer Miranda during the QuTune project at the Interdisciplinary Centre for Computer Music Research (ICCMR), in collaboration with the University of Oxford, stands as a notable example of quantum computer music. This study adopts a case study approach to thoroughly investigate the technical creative process behind this work, covering elements such as quantum computing, quantum properties, qubits, quantum gates, and quantum circuits, gradually unveiling the mathematical logic behind quantum algorithmic composition. The results of this study indicate that quantum algorithmic composition, as an emerging approach to music creation, not only generates unique music through the characteristics of quantum computing but also offers new possibilities for the integration of music, art, and technology. By applying quantum bits, quantum gates, and quantum circuits, this research demonstrates how quantum computing can provide new theoretical foundations and practical methods for music composition. Furthermore, the study discusses how to optimize the interactive creative experience in quantum music works and how to enhance the understanding and appreciation of quantum music among a broader audience of musicians and listeners. With the continuous advancement of quantum computing technology, quantum music is poised to contribute a distinctive dimension to the global flourishing of musical culture. This research offers fresh perspectives and ideas for the development of this field.
Music, as a form of art characterized by its complexity and diversity, holds significant cultural and emotional value for humanity. Piano music, being a prominent representative, demands efficient and precise recognition and analysis of its intricate harmonic, melodic, and rhythmic patterns. Traditional computational approaches often face limitations in handling such intricate patterns. However, quantum computing, emerging as a novel computational paradigm, presents new avenues for addressing these challenges. This paper aims to explore the potentials and methodologies of quantum computing in the realm of music, particularly focusing on the intricate pattern recognition of piano music. We introduce the fundamental principles and advantages of quantum computing. Subsequently, we delve into the application of quantum algorithms in piano music analysis, specifically addressing the recognition of harmonic structures and rhythmic patterns. Finally, we envision the future trends and challenges of quantum computing technology in the realm of music. Through this research endeavor, we aim to gain deeper insights into the potential of quantum computing in the field of music and offer novel ideas and methodologies for future investigations.
Quantum computing can be employed in computer-aided music composition to control various attributes of the music at different structural levels. This article describes the application of quantum simulation to model compositional decision making, the simulation of quantum particle tracking to produce noise-based timbres, the use of basis state vector rotation to cause changing probabilistic behaviors in granular harmonic textures, and the exploitation of quantum measurement error to cause noisy perturbations of spatial soundpaths. We describe the concepts fundamental to these techniques, we provide algorithms and software enacting them, and we provide examples demonstrating their implementation in computer-generated music
Quantum computing is a branch of computer science derived from the fundamental laws of quantum mechanics, such as state superposition, multi-value logic and destructive measure. An open challenge in itself is to re-think in quantum terms classic problems and solving techniques. Another nature-inspired field is the development of swarm-based robotic applications, where the challenge is catching the fundamental laws governing swarm dynamics, such as pattern formation and target reaching. Here, we review some recent approaches on swarm dynamics, the organizational rules of which are formalized according to quantum computing. In this way, the shades of probability in decision-making for multiple-robot systems can be expressed according to the multi-value logic underlying quantum computing. In our review, specific quantum circuits are sketched to give an idea of how these problems have been faced in computational terms. The article is enriched by references to sonification, a strategy adding one more sensory dimension to data representation, a human-friendly tool to navigate the complexity of swarm-robotic movements in a given arena.This article is part of the theme issue 'The road forward with swarm systems'.
Quantum computing technology is developing at a fast pace. The impact of quantum computing on the music industry is inevitable. This paper maps the emerging field of quantum computer music. Quantum computer music investigates, and develops applications and methods to process music using quantum computing technology. The paper begins by contextualising the field. Then, it discusses significant examples of various approaches developed to date to leverage quantum computing to learn, process and generate music. The methods discussed range from rendering music using data from physical quantum mechanical systems and quantum mechanical simulations to computational quantum algorithms to generate music, including quantum AI. The ambition to develop techniques to encode audio quantumly for making sound synthesisers and audio signal processing systems is also discussed.