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Reducing Big Data Using Ideas From Quantum Theory Makes It Easier to Interpret

Queen Mary, University of London (04/23/15) Will Hoyles

Researchers from Queen Mary University of London (QMUL) and Rovira i Virgili University have developed a new method that simplifies the way big data is represented and processed. Borrowing ideas from quantum theory, the team implemented techniques used to understand the difference between two quantum states. The researchers applied the quantum mechanical method to several large publicly available data sets, and were better able to understand which relationships in a system are similar enough to be considered redundant. The researchers say their method can significantly reduce the amount of information that has to be displayed and analyzed separately and make it easier to understand. Moreover, the approach reduces the computing power needed to process large amounts of multidimensional relational data. “We’ve been trying to find ways of simplifying the way big data is represented and processed and we were inspired by the way that the complex relationships in quantum theory are understood,” says QMUL’s Vincenzo Nicosia. “With so much data being gathered by companies and governments nowadays, we hope this method will make it easier to analyze and make sense of it, as well as reducing computing costs by cutting down the amount of processing required to extract useful information.”

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