With the emergence of quantum computers, a new field of algorithmic music composition has been initiated. The vast majority of previous work focuses on music generation using gate-based quantum computers. An alternative model of computation is adiabatic quantum computing (AQC), and a heuristic algorithm known as quantum annealing running in the framework of AQC is a promising method for solving optimization problems. In this chapter, we lay the groundwork of music composition using quantum annealing. We approach the process of music composition as an optimization problem. We describe the fundamental methodologies needed for generating different aspects of music including melody, rhythm, and harmony. The discussed techniques are illustrated through examples to ease the understanding. The music pieces generated using D-Wave quantum annealers are among the first examples of their kind and presented within the scope of the chapter. The text is an unedited pre-publication version of a chapter which will appear in the book "Quantum Computer Music", Miranda, E. R. (Editor).
With the emergence of quantum computers, a new field of algorithmic music composition has been initiated. The vast majority of previous work focuses on music generation using gate-based quantum computers. An alternative model of computation is adiabatic quantum computing (AQC), and a heuristic algorithm known as quantum annealing running in the framework of AQC is a promising method for solving optimization problems. In this chapter, we lay the groundwork of music composition using quantum annealing. We approach the process of music composition as an optimization problem. We describe the fundamental methodologies needed for generating different aspects of music including melody, rhythm, and harmony. The discussed techniques are illustrated through examples to ease the understanding. The music pieces generated using D-Wave quantum annealers are among the first examples of their kind and presented within the scope of the chapter. The text is an unedited pre-publication version of a chapter which will appear in the book "Quantum Computer Music", Miranda, E. R. (Editor).
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 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.
There has been tremendous progress in Artificial Intelligence (AI) for music, in particular for musical composition and access to large databases for commercialisation through the Internet.We are interested in further advancing this field, focusing on composition.In contrast to current 'blackbox' AI methods, we are championing an interpretable compositional outlook on generative music systems.In particular, we are importing methods from the Distributional Compositional Categorical (DisCoCat) modelling framework for Natural Language Processing (NLP), motivated by musical grammars.Quantum computing is a nascent technology, which is very likely to impact the music industry in time to come.Thus, we are pioneering a Quantum Natural Language Processing (QNLP) approach to develop a new generation of intelligent musical systems.This work follows from previous experimental implementations of DisCoCat linguistic models on quantum hardware.In this chapter, we present Quanthoven, the first proof-of-concept ever built, which (a) demonstrates that it is possible to program a quantum computer to learn to classify music that conveys different meanings and (b) illustrates how such a capability might be leveraged to develop a system to compose meaningful pieces of music.After a discussion about our current understanding of music as a communication medium and its relationship to natural language, the chapter focuses on the techniques developed to (a) encode musical compositions as quantum circuits, and (b) design a quantum classifier.The chapter ends with demonstrations of compositions created with the system.
There have been significant attempts previously to use the equations of quantum mechanics for generating sound, and to sonify simulated quantum processes. For new forms of computation to be utilized in computer music, eventually hardware must be utilized. This has rarely happened with quantum computer music. One reason for this is that it is currently not easy to get access to such hardware. A second is that the hardware available requires some understanding of quantum computing theory. This paper moves forward the process by utilizing two hardware quantum computation systems: IBMQASM v1.1 and a D-Wave 2X. It also introduces the ideas behind the gate-based IBM system, in a way hopefully more accessible to computerliterate readers. This is a presentation of the first hybrid quantum computer algorithm, involving two hardware machines. Although neither of these algorithms explicitly utilize the promised quantum speed-ups, they are a vital first step in introducing QC to the musical field. The article also introduces some key quantum computer algorithms and discusses their possible future contribution to computer music.
Of all novel computing methods, quantum computation (QC) is currently the most likely to move from the realm of the unconventional into the conventional. As a result some initial work has been done on applications of QC outside of science: for example music. The small amount of arts research done in hardware or with actual physical systems has not utilized any of the advantages of quantum computation (QC): the main advantage being the potential speed increase of quantum algorithms. This paper introduces a way of utilizing Grover's algorithm - which has been shown to provide a quadratic speed-up over its classical equivalent - in algorithmic rule-based music composition. The system introduced - qgMuse - is simple but scalable. Example melodies are composed using qgMuse using the ibmqx4 quantum hardware. The paper concludes with discussion on how such an approach can grow with the improvement of quantum computer hardware and software.
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.