Guide to Unconventional Computing for Music

This chapter provides a broad overview of the field of unconventional computation, UComp. It includes discussion of novel hardware and embodied systems; software, particularly bio-inspired algorithms; and emergence and open-endedness.

Advances in technology have had a significant impact on the way in which we produce and consume music. The music industry is most likely to continue progressing in tandem with the evolution of electronics and computing technology. Despite the incredible power of today’s computers, it is commonly acknowledged that computing technology is bound to progress beyond today’s conventional models. Researchers working in the relatively new field of Unconventional Computing (UC) are investigating a number of alternative approaches to develop new types of computers, such as harnessing biological media to implement new kinds of processors. This chapter introduces the field of UC for sound and music, focusing on the work developed at Plymouth University’s Interdisciplinary Centre for Computer Music Research (ICCMR) in the UK. From musical experiments with Cellular Automata modelling and in vitro neural networks, to quantum computing and bioprocessing, this chapter introduces the substantial body of scientific and artistic work developed at ICCMR. Such work has paved the way for ongoing research towards the development of robust general-purpose bioprocessing components, referred to as biomemristors, and interactive musical biocomputers.

Biophysical music is a rapidly emerging area of electronic music performance. It investigates the creation of unconventional computing interfaces to directly configure the physiology of human movement with musical systems, which often are improvisational and adaptive. It draws on a transdisciplinary approach that combines neuromuscular studies, phenomenology, real-time data analysis, performance practice and music composition. Biophysical music instruments use muscle biosignals to directly integrate aspects of a performer’s physical gesture into the human–machine interaction and musical compositional strategies. This chapter will introduce the principles and challenges of biophysical music, detailing the use of physiological computing for musical performance and in particular the musical applications of muscle-based interaction.

This chapter discusses the practices of silicon luthiers, the master craftspeople of electronic music. It illustrates how the design of electronic music instruments is heavily indebted to the spirit of invention that characterized electronics research before the standardization of components, and connects them with the associated engineering methodologies relevant today. Through the presentation of various sound generation schemes and interfaces, an alternate history of electronic music is drawn at the component, interface, and system level. Musicians and designers have always questioned the limits of their devices, as well as the preconceptions of what instruments could or should be: Through the development of original interfaces and unusual synthesis methods, they offered their personal visions for the field. This chapter offers a view of how these innovators helped shape the present and many futures of music technology.

This chapter is an introduction to quantum computing in sound and music. This is done through a series of examples of research applying quantum computing and principles to musical systems. By this process, the key elements that differentiate quantum physical systems from classical physical systems will be introduced and what this implies for computation, sound, and music. This will also allow an explanation of the two main types of quantum computers being utilized inside and outside of academia.

For almost 150 years, the capacitor (discovered in 1745), the resistor (1827) and the inductor (1831) have been the only fundamental passive devices known and have formed the trinity of fundamental passive circuit elements, which, together with transistors, form the basis of all existing electronic devices and systems. There are only a few fundamental components and each of them performs its own characteristic function that is unique amongst the family of basic components. For example, capacitors store energy in an electric field, inductors store energy in a magnetic field, resistors dissipate electrical energy, and transistors act as switches and amplify electrical energy. It then happened in 1971 when Leon Chua, a professor of electrical engineering at the University of Berkeley, postulated the existence of a fourth fundamental passive circuit element, the memristor (Chua in IEEE Transactions on Circuit Theory 18(5):507–519, 1971). Chua suggested that this fourth device, which was only hypothetical at that point, must exist to complete the conceptual symmetry with the resistor, capacitor and inductor in respect of the four fundamental circuit variables such as voltage, current, charge and flux. He proved theoretically that the behaviour of the memristor could not be substituted by a combination of the other three circuit elements, hence that the memristor a truly fundamental device. This chapter is about the remarkable discovery of the “fourth fundamental passive circuit element”, the memristor. Its name is an amalgamation of the words “memory” and “resistor”, due to the memristor’s properties to act as a resistor with memory. Since the memristor belongs to the family of passive circuit elements, these will be focused here.

Slime mould Physarum polycephalum is a single-celled amoeboid organism known to possess features of a membrane-bound reaction–diffusion medium with memristive properties. Studies of oscillatory and memristive dynamics of the organism suggest a role for behaviour interpretation via sonification and, potentially, musical composition. Using a simple particle model, we initially explore how sonification of oscillatory dynamics can allow the audio representation of the different behavioural patterns of Physarum. Physarum shows memristive properties. At a higher level, we undertook a study of the use of a memristor network for music generation, making use of the memristor’s memory to go beyond the Markov hypothesis. Seed transition matrices are created and populated using memristor equations, and which are shown to generate musical melodies and change in style over time as a result of feedback into the transition matrix. The spiking properties of simple memristor networks are demonstrated and discussed with reference to applications of music making.

This chapter presents an account of our investigation into developing musical processing devices using biological components. Such work combines two vibrant areas of unconventional computing research: Physarum polycephalum and the memristor. P. polycephalum is a plasmodial slime mould that has been discovered to display behaviours that are consistent with that of the memristor: a hybrid memory and processing component. Within the chapter, we introduce the research’s background and our motives for undertaking the study. Then, we demonstrate P. polycephalum’s memristive abilities and present our approach to enabling its integration into analogue circuitry. Following on, we discuss different techniques for using P. polycephalum memristors to generate musical responses.

This chapter introduces the concept of programming using music, also known as tone-based programming (TBP). There has been much work on using music and sound to debug code, and also as a way of help people with sight problems to use development environments. This chapter, however, focuses on the use of music to actually create program code, or the use of music as program code. The issues and concepts of TBP are introduced by describing the development of the programming language IMUSIC.