The abstraction of musical structures (notes, melodies, chords, harmonic or rhythmic progressions, etc.) as mathematical objects in a geometrical space is one of the great accomplishments of contemporary music theory. Building on this foundation, I generalize the concept of musical spaces as networks and
derive functional principles of compositional design by the direct analysis of the network topology. This approach provides a novel framework for the analysis and
quantification of similarity of musical objects and structures, and suggests a way to relate such measures to the human perception of different musical entities. Finally,
the analysis of a single work or a corpus of compositions as complex networks provides alternative ways of interpreting the compositional process of a composer
by quantifying emergent behaviors with well-established statistical mechanics techniques. In particular, I will demonstrate how tonal harmony, or any other
compositional framework, emerges naturally as a property of the network topology.
About the speaker
About the speaker
Marco Buongiorno Nardelli is a computational physicist, composer, and media artist at the University of North Texas, a member of iARTA, the Initiative for Advanced Research in Technology and the Arts and of CEMI, the Center for Experimental Music and Intermedia, and a Parma Recordings artist. As both an Artist and a Scientist, his work is intrinsically inter-and cross-disciplinary: his work in Physics and in Art is the natural extension of his practices as a creative thinker: “At the core, I am doing the same thing; the tools that I use to achieve the end-goals are different, of course, but the conceptual framework is very similar. These two things talk to each other at a very deep level.” As a music theorist and composer, he is a pioneer in the application of complexity theories and big data analysis tools to the structure of music as a generalized mathematical space. As an artist, he is internationally recognized for his music/new media installations, and his artistic research is rooted in the duality "music as data, data as music", including the translation of scientific data and processes into sonic, and potentially artistic, material. See www.materialssoundmusic.com, www.musicntwrk.com and ermes.unt.edu for more information and to learn about his other projects.
Marco Buongiorno Nardelli is a computational physicist, composer, and media artist at the University of North Texas, a member of iARTA, the Initiative for Advanced Research in Technology and the Arts and of CEMI, the Center for Experimental Music and Intermedia, and a Parma Recordings artist. As both an Artist and a Scientist, his work is intrinsically inter-and cross-disciplinary: his work in Physics and in Art is the natural extension of his practices as a creative thinker: “At the core, I am doing the same thing; the tools that I use to achieve the end-goals are different, of course, but the conceptual framework is very similar. These two things talk to each other at a very deep level.” As a music theorist and composer, he is a pioneer in the application of complexity theories and big data analysis tools to the structure of music as a generalized mathematical space. As an artist, he is internationally recognized for his music/new media installations, and his artistic research is rooted in the duality "music as data, data as music", including the translation of scientific data and processes into sonic, and potentially artistic, material. See www.materialssoundmusic.com, www.musicntwrk.com and ermes.unt.edu for more information and to learn about his other projects.
