Keeping track of the Universe is a real world challenge, even with todays sophisticated technology. Current interpretations of astronomical observations indicate that the age of the Universe is 13.73 (± 0.12) billion years, and that the diameter of the observable universe is at least 93 billion light years, or 8.80 × 1026 metres.
The U.S. Department of Energy has supplied a $1.6 million grant over a period of three years to fund the research of an automated method to detect astrophysical phenomena. The initiative is a collaborative effort between the three universities and is headed by Jeff Schneider, a research professor in Carnegie Mellon’s School of Computer Science.
As a solution, Schneider’s research is intended to implement several methods to have machines sort through the data. This would incorporate both data mining methods, which is the process of finding patterns within data, and machine learning methods, which would allow computers to learn and make decisions based on given data. Schneider hopes to have machines implement anomaly detection, which has them “learn” a set of data about typical objects, and compare them with data from new observations.
Schneider’s states: “We may find new kinds of objects that have never been observed before. We may find interactions that were previously unknown, such as the differing types of stars or galaxies that exist in very old or very young parts of the universe.”
Read more at THE TARTAN
Tags: Data Mining, news
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