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Large Hadron Collider data to be translated for the piano

"This approach to render big data sonically might reveal properties and behaviors that would probably not be revealed with parametric sonification," researcher Eduardo Miranda said.

By Brooks Hays
Researchers are working on turning data from the Large Hadron Collider into piano music. Photo by UPI/Maximilien Brice/CERN
Researchers are working on turning data from the Large Hadron Collider into piano music. Photo by UPI/Maximilien Brice/CERN

May 30 (UPI) -- A team of particle physicists are trying their hands at musical composition.

Researchers at the University of Plymouth, in tandem with scientists at MIT and CERN in Switzerland, want to turn data generated by the Large Hadron Collider, the world's largest particle accelerator, into piano music.

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Composers at Plymouth's Interdisciplinary Centre for Computer Music Research have developed sophisticated models to turn complex data into musical scores using high-performance computers.

"We have previously worked on various sonification projects, however it does not always work for very complex data because it can result in nonsense noise," Eduardo Miranda, head of the ICCMR, said in a news release. "As such, we are championing the concept of 'musification,' using a subjective interpretation to render the information aesthetically, rather than merely scientifically."

Researchers hope this new type of translation could reveal patterns and concepts missed during traditional scientific analysis.

"This approach to render big data sonically might reveal properties and behaviors that would probably not be revealed with parametric sonification," Miranda said.

Scientists will focus on only limited subsets of data produced by LHC.

"My team enjoyed engaging with Eduardo and getting him going with the tools we developed to map music onto the ATLAS data at the Large Hadron Collider," said Joe Paradiso, director of the MIT Media Lab's Responsive Environments Group. "We're looking forward to hearing the composition he produces, leveraging his granular synthesis tools that are well-suited to being driven by data of this sort."

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