Musician and Mega-Machine: Compositions Driven by Real-Time Particle Collision Data from the ATLAS Detector

نویسندگان

  • Juliana Cherston
  • Ewan Hill
  • Steven Goldfarb
  • Joseph A. Paradiso
چکیده

We present a sonification platform for generating audio driven by real-time particle collision data from the ATLAS experiment at CERN. This paper provides a description of the data-to-audio mapping interfaces supported by the project’s composition tool as well as a preliminary evaluation of the platform’s evolution to meet the aesthetic needs of vastly distinct musical styles and presentation venues. Our work has been conducted in collaboration with the ATLAS Outreach team and is part of a broad vision to better harness real-time sensor data as a canvas for artistic expression. Data-driven streaming audio can be treated as a reimagined form of live radio for which composers craft the instruments but real-time particle collisions pluck the strings.

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تاریخ انتشار 2016