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Cellular Synthesis is – which explains the title – my original technique of musical composition based on a purpose-designed cellular automaton and an additive synthesizer. The aim of the project is to make it possible to create complex and rich sound structures, by controlling a large number of parameters and using the opportunities available only through computer programming. All these conditions are fulfilled while maintaining a very simple and intuitive mode, susceptible to modifications in real time and relying on various types of equipment as controllers.

In other words, Cellular Synthesis is a concept (software and a composer’s approach) which uses a finite and small (and thus easily learned and applied) set of variables and rules to obtain complex musical structures.

Due to the fact that Cellular Synthesis operates at both the generative composition (score) and audio levels, shaping the macro and micro layers of the piece by means of the same set of rules, this concept can be seen as a development on the mechanisms with which Iannis Xenakis experimented (for ex-ample, UPIC made it possible to graphical-ly shape both the visual score itself and the waveforms of the sound oscillators, which is somewhat analogous to certain features of Cellular Synthesis).

Another important thing is that a cellular automaton is by nature graphically programmable (by setting the initial status manually, e.g., by filling selected cells). This means that a cellular automaton is a compu-tational system which may be programmed even by people who cannot read or write “traditional” texts. From the musical perspective, Cellular Synthesis is a fully programmable musical instrument and notation (insofar as it works with programming languages), but it does not require writing a code (or any graph-based equivalent of a code, as in case of dataflow-based languages widely used by composers and new media artists). Cellular Synthesis is a “graphically coded” system for creating music.

The project is inspired by the research and publications of Stephen Wolfram. Wolfram studied the behavior of (mainly one-dimensional) cellular automata, formulating a series of observations and indicating their potential applications. Although my own machines were mostly based on two- and three-dimensional matrices, owing to Wolfram I was able to confirm various personal observations and solve some problems that I had experienced before (one of Wolfram’s fundamental observations says that the nature of cellular automata, makes, the results achieved with their help, not create more complex, when we complicate the automaton control rules; in other words, a set of simple rules can lead to complex patterns). In addition, Wolfram, which also seemed interesting to me, treated cellular automata not as a mathematical curiosity, but as full-fledged computing systems that could be used for specific purposes. In practice, this means that a cellular automaton can be a programming language with purely graphical data and coding rules, which does not require even literacy to create programs.

Since about 1998, I have been studying the possibility of using, for my own purposes, the algorithms describing cellular automata. There is probably nothing unusual about this, as, similarly to applications of the fractal theory, cellular automata have for a long time been within the orbit of interest of media art, and many artists have tried to use them in one way or another in their works (moreover, cellular automata are computing systems studied, for example, by computer sciences, and they are sometimes used as simulation mechanisms in economics, anthropology, and many other fields of science). A cellular automaton is built based on an n-dimensional matrix of cells that can take a finite number of states. For each cell, a set of cells known as adjacent is defined, and each cell changes its state depending on the state of its neighbors. The history of research on cellular automata is quite interesting and dates back to the 1940s and the work of Stanisław Ulam and John von Neumann at the Los Alamos National Laboratory (where the first atomic bomb was constructed). Another important name is John Conway, the inventor of the “Game of Life,” probably the best-known two-dimensional cellular automaton. In the 1980s cellular automata was extensively researched by Stephen Wolfram (Wolfram is an active researcher in the field of broadly defined computer sciences, inventor, and originator of a number of concepts and technologies, ranging from the machine understanding of language up to cryptography, and also the founder of the Mathematica program, Wolframalpha service, etc.).

I resumed working with cellular automata and sound, using additive synthesis (which involves, briefly, the creation of sound based on the manipulation of the parameters of its basic components [e.g., sinusoidal com-ponents]; generally, additive synthesis is difficult in practical use, because it requires the simultaneous handling of a giant number of synthesis track parameters, which is unintuitive and difficult to be executed “manually,” for example, when playing live). Cellular Synthesis, an artistic technique I have developed is something between the synthesis technology and a concept / tool for composers (the premiere performance of tracks based on cellular synthesis took place at the “Vox Electronica” festival in Lviv in 2014). In simplest terms, it involves the use of a cellular automaton guided by suitably established rules for the dynamic control of additive synthesis. It makes it possible to intuitively control and modify – also in real time – a large number of parameters of the additive synthesis track. Cellular Synthesis is quite difficult to assign to any traditionally understood forms of artistic expression. It is, at the same time, a task in itself, a description of the creative process, and an algorithm and its complementation in the form of a specific technology.